Explore all 6 guides related to Code Review Prompt Generator.
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AI-written code usually compiles and passes a quick test while hiding the real risks — a missing auth check, a destructive update, an untested edge case. Here's a review path that surfaces them before you merge.
You finished an AI-assisted fix and sent your teammate a bare diff — so they skim and approve, or burn an hour reconstructing the context you had. Prepare a code-change review packet: the intent, the must-not-change behavior, the risks, and the tests you didn't run.
Code you can refactor on a quiet afternoon. A field you shipped is somebody else's dependency — you don't fix it, you version it. What an hour of contract review buys: method semantics, a truthful error model, retries, authorization, and compatibility you didn't mean to promise.
The code compiles, the tests pass, and it doesn't look like anything else in the repo. "Follow our conventions" is a wish: yours aren't written down, they're spread across nine hundred files that disagree. Here's how to extract the real rules and test them.
Four hundred lines of login code and a yes-or-no. You can read every line, find nothing, and still be wrong — because what will hurt you is in the file nobody opened alongside it: a session that outlives a logout, a reset that leaves the old one working.
Ask AI to "review this for performance" and you get a tidy list of smells with no idea which one production actually spends time on. Here is how to review code for performance with AI so each finding is tied to a workload, ranked by evidence, and marked with the measurement that would confirm it.