pdombroski

KIOSK LLM Wiki

A practical LLM wiki pattern for vibe-coded apps, AI-built products, and high-trust software systems.

Inspired by Andrej Karpathy's original LLM Wiki.

This is a simpler, gist-native version of the KIOSK idea. It is designed to be copy-pasted into an AI coding agent like Lovable, Cursor, Claude Code, Codex, or similar. The goal is to communicate the concept clearly enough that the agent can build a primitive but useful version directly in your repo.

The original LLM wiki idea is about giving LLMs a persistent knowledge layer instead of making them rediscover everything through RAG every time. KIOSK keeps that idea, but adapts it for codebases, documentation-heavy products, AI-assisted development, and high-compliance software.

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.