One free 65-line file, built from Andrej Karpathy’s biggest complaints about AI coding agents. Drop it in your project folder and Claude Code reads it automatically.
Andrej Karpathy was a founding member of OpenAI, ran AI at Tesla and founded Eureka Labs. In May 2026 he joined Anthropic. When he posts about why AI coding agents go wrong, people listen.
In one post he named the big ones. Agents guess instead of asking. They build "a bloated construction over 1000 lines when 100 would do." And they change code they don’t fully understand, even when it has nothing to do with the task.
A developer turned those complaints into a 65-line CLAUDE.md file and shared it free on GitHub. Claude Code reads a CLAUDE.md in your project folder at the start of every session, so the rules apply without you repeating them.
01
Silent assumptions
When an agent isn’t sure what you mean, it usually guesses, because guessing produces output. You get code that runs but solves a problem you didn’t have.
The first rule is Think Before Coding. Claude has to state its assumptions, lay out the options when there’s more than one reading, and ask when something is unclear. Karpathy’s words: "The models make wrong assumptions on your behalf and just run along with them without checking."
02
Overcomplication
Ask for a button and you can get a button, a wrapper component, a config file and a refactor of the parent. Five files for one feature.
The second rule is Simplicity First. Write the minimum code that solves the problem and skip features, abstractions and settings nobody asked for. The file’s gut check: would a senior engineer call this overcomplicated?
03
Edits you never asked for
A one-line bug fix comes back as a 200-line diff because the agent tidied the whole file while it was in there.
The third rule is Surgical Changes. Touch only what the task needs and match the existing style. If Claude spots unrelated dead code, it mentions it and leaves it alone. Every changed line should trace back to your request.
04
Bonus rule: prove it’s done
The fourth rule is Goal-Driven Execution. Each task gets a check you can verify, like a test that passes or a bug that stops reproducing. Claude keeps going until that check passes.
01
Option A: one project
Open the GitHub repo, copy the contents of CLAUDE.md, and save them in a file called CLAUDE.md in your project’s root folder. That’s the folder with your .git, package.json or pyproject.toml. Next time you open Claude Code there, it reads the file automatically.
Already have a CLAUDE.md? Add the rules to the end of yours, or paste this into Claude Code and let it merge them carefully.
02
Option B: every project
The repo is also a Claude Code plugin. In Claude Code, run these two commands to use the guidelines across all your projects:
/plugin marketplace add multica-ai/andrej-karpathy-skills
/plugin install andrej-karpathy-skills@karpathy-skills
The file says it’s working when your diffs get smaller, you rewrite less, and Claude asks its questions before it codes instead of after a mistake. To nudge it on a big task, start with this:
Why It Works
The file isn’t magic. It’s a tight set of rules in a place Claude reads by default. Claude Code is more capable than its default habits, and clear rules close that gap. The tradeoff, which the file admits, is a little less speed on tiny tasks.