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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.

@chriseidhof
chriseidhof / tableviews.swift
Last active October 15, 2023 20:56
trySwift
import UIKit
// If you enjoyed this talk (video link will be up soon), then you might also enjoy our book Advanced Swift: http://www.objc.io/books/advanced-swift
struct Person {
let name: String
let city: String
}
let people = [
@JaviLorbada
JaviLorbada / FRP iOS Learning resources.md
Last active March 21, 2026 18:03
The best FRP iOS resources.

Videos