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LLM Wiki

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.

The core idea

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.

- After making changes, ALWAYS make sure to start up a new server so I can test it.
- Always look for existing code to iterate on instead of creating new code.
- Do not drastically change the patterns before trying to iterate on existing patterns.
- Always kill all existing related servers that may have been created in previous testing before trying to start a new server.
- Always prefer simple solutions
- Avoid duplication of code whenever possible, which means checking for other areas of the codebase that might already have similar code and functionality
- Write code that takes into account the different environments: dev, test, and prod
- You are careful to only make changes that are requested or you are confident are well understood and related to the change being requested
- When fixing an issue or bug, do not introduce a new pattern or technology without first exhausting all options for the existing implementation. And if you finally do this, make sure to remove the old implementation afterwards so we d
@yifanzz
yifanzz / code-editor-rules.md
Created December 17, 2024 00:01
EP12 - The One File to Rule Them All

[Project Name]

Every time you choose to apply a rule(s), explicitly state the rule(s) in the output. You can abbreviate the rule description to a single word or phrase.

Project Context

[Brief description ]

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