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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.

@spencerwooo
spencerwooo / termiWidget.js
Last active September 18, 2025 05:20
🍋 TermiWidget - Terminal-like Widget for iOS 14, made with Scriptable.
// Variables used by Scriptable.
// These must be at the very top of the file. Do not edit.
// icon-color: orange; icon-glyph: quote-right;
// Change these to your usernames!
const user = "spencer"
const jike = "4DDA0425-FB41-4188-89E4-952CA15E3C5E"
const telegram = "realSpencerWoo"
const github = "spencerwooo"
# Video: http://rubyhoedown2008.confreaks.com/08-chris-wanstrath-keynote.html
Hi everyone, I'm Chris Wanstrath.
When Jeremy asked me to come talk, I said yes. Hell yes. Immediately. But
then I took a few moments and thought, Wait, why? Why me? What am I supposed
to say that's interesting? Something about Ruby, perhaps. Maybe the
future of it. The future of something, at least. That sounds
keynote-y.