AI generates code fast. If you commit every AI-generated change to your main branch, you will regret it. Here is the git workflow I use to keep AI code safe and reviewable.
What is the safest git workflow for AI-generated code?
Create a feature branch for every AI session. Commit after every prompt that changes more than 2 files. This creates a decision log — you can see exactly what each prompt produced. If a prompt introduces a bug, you revert just that commit. I use the prompt as the commit message. This makes the git log a searchable record of what the AI did.
How do you review AI code in a pull request?
Review the diff as if a junior developer wrote it. Check for: hardcoded secrets, missing error handling, SQL injection points, and overly complex solutions. The AI tends to over-engineer simple problems. I add a review step before every merge: ask the AI to review its own code first, then read the summary, then approve or request changes.
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