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.

kaaquist

Langgraph Supervisor with A2A Agent

A2A seems to be a great new way to connect agents. But how do I get an A2A Agent to be part of my already existing Langgraph supervisor setup?

(WIP)
Ever since Google announced the new A2A protocol to communicate between Agents across business or internally between business compartments. I have been trying to find a great way to integrate the A2A into my existing setup of Langgraph supervisor.

In a nutshell, if we take the classic example of a math agent and a research agent that gets “controlled” by a supervisor agent.

joshbuchea

Semantic Commit Messages

See how a minor change to your commit message style can make you a better programmer.

Format: <type>(<scope>): <subject>

<scope> is optional

Example

massie

/*
 * Copyright (c) 2013. Regents of the University of California
 *
 * 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
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software