How do you use AI to review code, and how do you check its comments?
Suggested answer
The interviewer wants to know whether you use AI as a controlled second reviewer rather than a judge, and whether you keep your own ability to read code.
I review the code myself first, and only then ask the AI. If I look at the AI's list first, I get anchored to it and only judge what it brings up, instead of searching on my own. When I review by myself, I use the familiar frame: design, functionality and edge cases, complexity, tests, naming (Google has a guide on what to look at in a review).
When I ask the AI, I require every comment to come with the relevant line, a specific input that causes the problem, and a severity, so there is something I can run. Then I check each comment: I write a small probe, or run that input, and see whether the bug is real. This step matters because AI can be wrong while sounding very sure, for example claiming that a function will throw an error when it quietly returns a wrong value. Environment-dependent bugs, like time zones, need to be tried in more than one configuration.
Finally I keep a record of every review: what I caught first, what only the AI caught, and what the AI got wrong. The "only the AI caught" column tells me which kinds of bugs I am weak at.
Bonus points: mention that AI lacks the context for design questions (should we add this feature right now?), so treat its answers on design as opinions, and that you never paste API keys or customer data into a prompt.