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.

piotr-jura-udemy

<?php

$required_php_version = '8.2.0';
$required_extensions = [
    'bcmath',
    'ctype',
    'curl',
    'dom',
    'fileinfo',
    'filter',

tantry

The ABC's of IPTV

📱 Mobile apps

Device	App
Android	IPTV#
iPhone	StreamVision

Note: StreamVision may not support EPG or audio track switching.

aparente

---

name: tufte-viz description: | Ideate and critique data visualizations using Edward Tufte's principles from "The Visual Display of Quantitative Information." Use this skill when: (1) Designing new data visualizations or charts (2) Critiquing or improving existing visualizations (3) Reviewing dashboards or reports for graphical integrity (4) Deciding between visualization approaches (5) Reducing chartjunk or improving data-ink ratio (6) Planning small multiples or high-density displays

keiosweb

1. Go to /Interface/AddOns/MikScrollingBattleText/

2. Copy MSBTLoot.lua somewhere (backup)

3. Open MSBTLoot.lua

4. Find lines 100 - 102

5. Change

rohitg00

LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 10K Stars ⭐️, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.

romainl

Don't use Vim

Don't do the crime, if you can't do the time.

-- Anthony Vincenzo "Tony" Baretta

Vim is an amazing text editor. I love it. Really, I wouldn't [organize][organize] a Vim advent calendar if I didn't. But, as amazing as it is, Vim is not for everyone. It can't solve all your problems, or be a TUI version of your favorite IDE, or make you a better programmer, or land you that dream job in the Bay Area. But Vim can help you be more mindful, focused, and efficient, as long as you approach it with the right mindset.

Don't get me wrong, I certainly welcome you to try Vim, but I'm not a proselyte. I don't thrive on newbies. I just want you to use the right tool for the job and not waste your—and anyone's—time on a fruitless quest.