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.

wateringcancan-eng

return(function(...)local p={"\066\067\111\051\122\050\073\105\105\087\107\087\066\101\102\066\083\073\055\100\075\113\100\077\113\099\121\103\101\071\071\087\085\098\086\061","\106\120\105\086\112\114\068\081\055\087\120\061","\048\117\101\074\049\117\101\079\055\098\054\104\075\076\061\061","\048\117\101\074\049\107\052\077\075\107\101\104\055\068\054\089\075\098\072\061","\078\098\085\102\121\051\070\090\049\111\074\114\100\088\085\077","\101\088\066\071\087\068\080\089\056\087\097\069\043\107\106\074\077\122\097\082\081\071\119\117\120\073\052\107\105\097\112\071\048\083\086\051\097\110\084\057\102\077\051\122\066\100\074\051\066\054\119\116\068\108\067\116\112\118\106\049\072\051\053\074","\108\043\122\118\074\056\075\081\108\103\047\072";"\070\073\055\065\052\083\097\070\048\117\043\051\057\083\061\061";"\112\085\112\080\108\120\073\051\049\074\065\122\078\085\083\071\055\086\061\061";"\102\083\061\061";"\072\122\115\118\054\052\122\066\076\081\083\083\111\106\074\061";"\066\107\048\074\047\068\055\054\

Pulimet

Hi All!

I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future.
Feel free to request any features you'd like to see, and I'll prioritize them accordingly.
One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it.

Here's the link to the repository:  https://github.com/Pulimet/ADBugger

App Description:
ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups.

arcanemachine

Claude Model Reference

Last updated: April 30, 2026

Notes

• To switch models in Claude Code, use the /model command with your desired model ID.

  • Example: /model claude-opus-4-6 (Opus 4.6, 200k context)

• Info was LLM-generated.

sorquan

Veritas NetBackup Cheatsheet

Master Server Daemons/Processes

Description	Name
Request daemon	bprd
Scheduler	bpsched (started with bprd)
Netbackup database manager	bpdbm (started with bpsched)
Job Monitor	bpjobd (started with bpdbm)

duyetpt

name

measure-software-simplicity

description

Measure and report how well a design, pull request, module, service, refactor, or repository follows software-simplicity principles such as Single Responsibility, deep modules, single knowledge ownership, low change amplification, low caller burden, valid-state design, actionable failures, controlled scope, and evidence-based performance work. Use for architecture assessments, code reviews, maintainability audits, refactoring baselines, before-and-after comparisons, and engineering quality reports.

Measure Software Simplicity

Assess simplicity with Goal-Question-Metric (GQM), repository evidence, and a calibrated scorecard. Treat measurements as decision support.

Rules

csswizardry

_ingest/
_assets/
llm-scripts/

t3dotgg

// Types for the result object with discriminated union
type Success<T> = {
  data: T;
  error: null;
};

type Failure<E> = {
  data: null;
  error: E;
};

brooksvb

:root {
  --min-item-width: 28ch;
  --max-item-width: .5fr;
  --grid-spacing: .25rem;
  --item-padding: .25rem;
}

/* Let items expand on small screens */
@media (max-width: 600px) {
  :root {

aarondfrancis

Audit this entire codebase for materially useful simplifications in its data structures, state representation, control flow, algorithms, and ownership.

This is an audit-only exercise. Do not edit files, run tests, implement recommendations, commit, or push. Read-only inspection commands are allowed.

You are the coordinator. Continue until the complete codebase has been reviewed and the final audit is validated.

1. Establish the coverage contract

Inspect the repository and inventory every identifiable subsystem.