karpathy-methodology

Q: How do I install karpathy-methodology?

Run npx skills add https://github.com/learnprompt/andrej-karpathy-skills --skill karpathy-methodology in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/karpathy-methodology/ (personal) or .claude/skills/karpathy-methodology/ (project).

by learnpromptAI & Agents

Apply Andrej Karpathy AI methodology and principles from his 2023-2026 insights. Use this skill when the user wants to apply Karpathy-style thinking, needs guidance on agentic engineering, LLM knowledge bases, minimalist coding, understanding-first principles, or any of the 14 core methodologies distilled from his work. Also triggers on: "karpathy method", "karpathy approach", "karpathy way", "AK style", "like karpathy does", "karpathy principles", or when user asks how Karpathy would approach any programming or AI problem.

Installs: 137
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/learnprompt/andrej-karpathy-skills --skill karpathy-methodology

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads karpathy-methodology automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Karpathy Methodology — 14 Core Skills

Distilled from Andrej Karpathy's most-liked posts on X (2023–2026), his LLM Wiki Gist, and the multica-ai/andrej-karpathy-skills repo. Source: https://x.com/karpathy | https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f

This skill is the master index. When invoked, either:

Apply the specific sub-methodology relevant to the user's current task, or
Guide the user to the right one from the 14 below.

The 14 Methodologies

#	Skill Name	One-line Essence
1	`karpathy-agentic-engineering`	Orchestrate agents with clear tasks and verifiable success criteria
2	`karpathy-llm-wiki`	Let LLM maintain your knowledge base; you do the exploring
3	`karpathy-llm-simulator`	Ask LLM to simulate expert debate, not give one opinion
4	`karpathy-minimalism`	200 lines of pure Python beats 50 npm packages
5	`karpathy-vibe-to-agentic`	Vibe coding raises the floor; agentic engineering raises the ceiling
6	`karpathy-autoresearch`	Agent loops on git branches; you only change the prompt
7	`karpathy-output-evolution`	Text → Markdown → HTML → rendered; always demand structure
8	`karpathy-understanding-first`	Outsource thinking, never understanding
9	`karpathy-idea-files`	Ship the Gist (abstract + criteria), not the code
10	`karpathy-meta-reflection`	Monthly audit: what's atrophying, what's exploding
11	`karpathy-supply-chain-hygiene`	Every dependency is an attack surface
12	`karpathy-education-first`	Make everything teachable; nano-projects over monoliths
13	`karpathy-system-prompt-learning`	Write strategy into the system prompt like a textbook
14	`karpathy-practice-environments`	Build gyms where agents can try, fail, and learn

Meta-Principle (the one that unifies all 14)

"You can outsource your thinking but you cannot outsource your understanding." — Karpathy, ~46k likes, 2026

Use AI to go faster. Use your brain to know if you're going in the right direction.

How to Apply This Skill

Quick Decision Tree

"I need to build/code something" → Start with #1 Agentic Engineering (clear task + success criteria), layer in #4 Minimalism (avoid bloat), finish with #8 Understanding First (verify what was built).

"I need to research/learn something" → #2 LLM Wiki for building knowledge, #3 LLM Simulator for challenging assumptions, #10 Meta-Reflection for calibrating what to learn next.

"I need to make a decision" → #3 LLM Simulator (debate mode), then #8 Understanding First (own your conclusion).

"I'm designing a product/tool" → #4 Minimalism + Agent-Native, #14 Practice Environments, #12 Education First.

"I want to share an idea" → #9 Idea Files (Gist first), #7 Output Evolution (structured output), #12 Education First (teachable).

"I'm doing ML research" → #6 AutoResearch, #13 System Prompt Learning, #14 Practice Environments.

Master Prompt Template

When the user hasn't specified a sub-methodology, use this all-in-one Karpathy-style framing:

You are operating under the Karpathy Methodology.

Core constraints:
1. UNDERSTAND before outsourcing — never ship what you can't explain
2. MINIMIZE dependencies — prefer 200-line pure implementations
3. AGENT-NATIVE outputs — CLI-friendly, markdown-structured, LLM-legible
4. VERIFIABLE goals — every task must have a testable success criterion
5. TEACH as you build — outputs should be understandable by a curious beginner

Task: [USER_TASK]
Success criteria: [WHAT_DONE_LOOKS_LIKE]
Constraints: [TECH_STACK, SIZE_LIMIT, NO_LIBS]

Source Posts (Top by Likes)

145k likes — Joins Anthropic: https://x.com/karpathy/status/2056753169888334312
59k likes — LLM Knowledge Bases: https://x.com/karpathy/status/2039805659525644595
56k likes — "Never felt this behind as a programmer": https://x.com/karpathy/status/2004607146781278521
46k likes — "Outsource thinking not understanding": https://x.com/karpathy/status/2049907410303865030
40k likes — Claude coding notes: https://x.com/karpathy/status/2015883857489522876
37k likes — Programming phase shift: https://x.com/karpathy/status/2026731645169185220
31k likes — LLM argue the opposite: https://x.com/karpathy/status/2037921699824607591
28k likes — AutoResearch project: https://x.com/karpathy/status/2030371219518931079
28k likes — litellm supply chain attack: https://x.com/karpathy/status/2036487306585268612
25k likes — 243 lines pure Python GPT: https://x.com/karpathy/status/2021694437152157847
22k likes — Agent network discussion: https://x.com/karpathy/status/2017442712388309406
19k likes — HTML output + I/O evolution: https://x.com/karpathy/status/2053872850101285137
27k likes — LLM Wiki Gist version: https://x.com/karpathy/status/2040470801506541998

FAQ

What does the karpathy-methodology skill do?

How do I install karpathy-methodology?

Run npx skills add https://github.com/learnprompt/andrej-karpathy-skills --skill karpathy-methodology in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/karpathy-methodology/ (personal) or .claude/skills/karpathy-methodology/ (project).

Which AI agents can use karpathy-methodology?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is karpathy-methodology safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains karpathy-methodology?

It is published by learnprompt in learnprompt/andrej-karpathy-skills. It has 137 recorded installs.