Frank West frank-west-iii

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.

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

	import { Controller } from '@hotwired/stimulus'

	const BANNED_NODES = ['com-1password-button', 'com-1password-menu']
	export default class extends Controller {
	connect () {
	this.observer = new window.MutationObserver(mutations => {
	mutations.forEach(mutation => {
	mutation.addedNodes.forEach(node => {
	if (BANNED_NODES.includes(node.nodeName.toLowerCase())) {
	node.remove()

	require_relative "./linked_list.rb"
	require_relative "./set.rb"

	# Here we monkey patched LinkedList to add a method
	# that allows us to remove vertices in constant time.
	class LinkedList
	# Removes the node that is right next
	# to the specified node.
	# Complexity O(1).
	def remove_next prev_node