karpathy

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.

ruvnet

A drop-in redaction hook wired through settings.json for Claude Code.

It masks secrets before tools run and censors sensitive fields in transcripts.

what is it?

Data leakage for enterprises using Ai coding is a ███ . Redaction hooks solve ██ problems by catching secrets before they leak. Here’s how I do it.

A redaction hook sits between your agent and the outside world. Every time Claude Code reads a file, runs a shell command, or fetches a web resource, the hook scans for sensitive patterns like API keys, tokens, or passwords. If it sees something dangerous, it either masks it with a placeholder or blocks the request outright. That way, your logs and transcripts remain useful but never expose private values.