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.

luciditee

/*
 * Unity Batch Burner: A script designed to reduce static mesh draw calls automatically in scenes
 * with a large amount of static geometry entities.
 * 
 * Copyright 2016-2017 Will Preston & Die-Cast Magic Studios, LLC.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *

keijiro

using UnityEngine;
using System.Collections;
using System.IO;
using System.Runtime.InteropServices;

public class PhotoTaker : MonoBehaviour
{
    // Screenshot file settings.
    public string temporaryFileName = "temp.png";
    public string androidStoragePath = "/mnt/sdcard/TestCameraApp";

hisasann

using System;
using UnityEngine;
using System.Collections;

public class CachingLoadExample : MonoBehaviour
{
    void Start ()
    {
        // Clear Cache
        Caching.CleanCache();

esskar

#include <stdio.h>
#include <Windows.h>

struct Name
{	
	char FirstName[100];
	char LastName[100];
	char *Array[3];
};