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.

yrashk

Inferal Workspace Architecture: How We Work at Inferal

(Blog version available at https://inferal.com/blog/workspace-architecture/)

Update: Inferal Workspace is going open source!

Your org's brain that AI can use

This is not our core product. This document describes our internal operating environment - how we run the company. We share it to show the environment you'd join and demonstrate our philosophy in action. For what we're building, see What We're Building below.

accentinteractive

<?php
/**
 * Dump helper. Functions to dump variables to the screen, in a nicley formatted manner.
 * @author Joost van Veen
 * @version 1.0
 */
if (!function_exists('dump')) {
    function dump ($var, $label = 'Dump', $echo = TRUE)
    {
        // Store dump in variable