Tell me about a time you changed how your team -- not just yourself -- works with AI. What did you introduce or build, how did you handle both the skeptics and the people who leaned on it too heavily, and what is measurably different about how the team works now?
The interviewer is looking for: shared artifacts you left behind rather than advice you gave, how you moved people at both extremes of the adoption curve, evidence of a workflow that was rebuilt end to end, and honest accounting of what did not take hold.
Note: this is distinct from a general change-management story -- the substance must be AI practice, and the interviewer wants the artifacts and conventions, not just the persuasion.
How to approach it
- Hint 1
The interviewer is assessing Scaling, the senior end of the AI signal areas: can you turn a personal workflow into team capability? I told people about my setup is the failure mode. They want durable artifacts -- a shared rules file or repo, a prompt or skill library, conventions for what goes to AI and what stays manual -- and evidence that other people's work actually changed.
- Hint 2
Choose an effort where you met resistance from both directions, because that is where the judgment shows. The skeptic who thinks it produces slop usually needs a pairing session on their own hardest task, not a demo. The over-relier merging unread output needs a review convention or a CI gate, not a lecture. Pick a story with a workflow you rebuilt end to end -- code review, incident postmortems, backlog grooming, onboarding -- rather than a tool you merely recommended.
- Hint 3
Use CARL and lead with the stakes: what was slow, inconsistent, or risky about how the team worked before. Keep the actions in first person -- the we-disease is fatal on adoption stories, because everything interesting is what you personally built and ran. Name the artifacts by what they are, describe the retro or feedback loop that kept them alive, and land on a result that includes both adoption and quality. Be honest about the piece that nobody used; a fairy-tale rollout reads as distance from the work.
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