I've been doing a lot of "vibe coding" with Claude Code and Codex. The frustrating pattern is that I'll ask for one small change, then later discover that the agent modified files or logic I wasn't expecting. By then, I may not remember exactly what changed or when. Besides using Git, are there good ways to maintain an AI coding activity log, restrict the agent's scope, or review its changes incrementally? Or is this simply a drawback of letting coding agents work autonomously?
3 Answers
A diff tells you what changed, but you still need to verify that the change behaves correctly. Run unit tests, integration tests, linters, and—when appropriate—runtime checks or logs. The important part is not finding a magical replacement for review; it’s making the agent’s work small, observable, and easy to roll back.
Git is still the main tool for this. Treat the agent like a junior developer—or like any other script that changes your code. Work on a separate branch, review the diff after each meaningful prompt, run tests, and create commits yourself once you understand the changes. Branch protection, pull requests, and code-owner reviews can add another safety layer.
That makes sense. My main issue has been waiting too long before checking the diff, so I’m going to review and commit in smaller steps instead.
You can also limit the agent’s permissions. Tell it which files or directories it may modify, and keep important areas read-only unless you explicitly approve changes. A project instructions file can record design decisions, conventions, and rules such as ‘always explain modified files’ or ‘never commit without approval.’ That gives you both an audit trail and clearer boundaries.
Exactly. If the agent changes several unrelated files for a supposedly small request, that’s usually a signal to stop, inspect the reasoning, and either narrow its permissions or revert and try again.