This question is increasingly common. The interviewer is checking two things: that you're fluent with modern tooling, and that you exercise judgment — you're not pasting AI output blindly into production.

How to frame it: AI is a multiplier, you're still the engineer

Talk about where it helps and how you stay in control.

Where it speeds me up

• Boilerplate — scaffolding components, config, repetitive CRUD.
• Tests — generating test cases for a function, then I review for the cases it missed.
• Refactors and migrations — mechanical transformations across files.
• Unfamiliar APIs — faster than docs-diving for a first pass.
• Rubber-ducking — explaining a bug to it often surfaces the answer.

How I stay in control

• I review every line. AI output is a draft, not a commit. I read it like a PR from a junior — it's often subtly wrong, outdated, or over-engineered.
• I verify correctness and security — especially anything touching auth, input handling, or dependencies (it hallucinates packages).
• I never paste secrets, credentials, customer data, or proprietary code into public AI tools — that's a data-leak risk and often a policy violation.
• I own the output. "The AI wrote it" is never an excuse for a bug.
• For anything I don't understand, I make sure I understand it before it ships — otherwise I can't maintain or debug it.

STAR-ish example

On a recent migration I used Cursor to convert ~40 class components to hooks. It handled the mechanical 80% in an afternoon; I reviewed each diff and hand-fixed the lifecycle edge cases it got wrong (cleanup logic, refs). What would've been a week was two days — but I still read and understood every change.

The two red flags to avoid

• Dismissing it — "I don't use AI, I write everything myself" reads as out of touch.
• Trusting it blindly — "I just accept the suggestions" reads as someone who'll ship hallucinated, insecure code.

The hireable answer is in the middle: leverage with judgment.

Senior framing

The senior take: AI changes the speed of producing code but not the engineer's responsibility for correctness, security, and maintainability. You use it to eliminate drudgery and move faster on the mechanical 80%, while spending your saved time on the 20% that needs real judgment — architecture, edge cases, trade-offs. And you're crisp about the data-handling boundaries.