- 🍎 macOS with Homebrew installed
- 💻 Terminal (zsh)
| #!/bin/bash | |
| # ============================================================================== | |
| # A simple script to link a local Git repository to a new remote on GitHub | |
| # and push the initial 'main' branch. | |
| # | |
| # INSTRUCTIONS: | |
| # 1. Make sure you have initialized a Git repository (`git init`). | |
| # 2. Add and commit your files (`git add .` and `git commit -m "Initial commit"`). | |
| # 3. Replace the URL with your own repository's URL. |
| # push an existing repository from the command line | |
| git remote add origin https://github.com/username/reponame | |
| git branch -M main | |
| git push -u origin main |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.