The AI tooling landscape changes fast. How do you stay current, and tell me about one thing you learned recently that actually changed how you work.
The interviewer is looking for: the specific sources you follow rather than a general claim of keeping up, a real cadence of hands-on experiments, and concrete evidence that something you learned changed your practice rather than just your opinions.
How to approach it
- Hint 1
The underlying assessment is Growth: whether you learn by doing or only by reading. Passive consumption -- I follow AI news, I read Twitter -- reads as no signal at all. The interviewer wants named sources, a rhythm of actual experiments, and one thing that changed as a result.
- Hint 2
Prepare three specifics before you answer: the sources you genuinely use (particular newsletters, release notes and changelogs, papers, practitioners you follow, an internal channel), how you try things on a real cadence (a Friday afternoon on a throwaway branch, a recurring low-stakes task you use as a benchmark), and one concrete change that stuck. Pick the change carefully -- something with a before and after, like a workflow you retired, a verification step you added, or a tool you tried and deliberately rejected.
- Hint 3
Keep it tight: sources, cadence, then spend most of your ninety seconds on the one change -- what you tried, what you expected, what actually happened, and what you do differently now. Mentioning something you evaluated and dropped is a strength, because it shows you test claims instead of collecting tools. Avoid a list of every model release you can name; breadth without a single applied change is the failure mode here.
Ready to answer it out loud?
Record your answer in 1:30 and Preptile scores it 1–10 with specifics — what landed, what you skipped, and what to say next time.
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