Describe a time you pushed back on using AI for something. How did you make the case, and what happened?
What they are really testing: Judgment and spine. In a hype cycle, the engineer who can say no with reasons is worth more than the one who says yes to everything, and the question tests whether the pushback was reasoned analysis or reflexive conservatism.
A real interview question
Describe a time you pushed back on using AI for something. How did you make the case, and what happened?
What most people say
drag me
“Leadership wanted a chatbot everywhere and I said we should be careful because AI makes mistakes, eventually we scoped it down.”
The pushback has no content. "AI makes mistakes" is a bumper sticker, not an analysis: no error-cost reasoning, no alternative offered, and "eventually scoped down" hides whether this person influenced anything.
The follow-ups they ask next
What if leadership had overruled you and demanded full auto-send?
Disagree and commit with the risk documented: ship with the strongest guardrails available, per-category rollout, kill-switch, sampling review, and the promotion metrics still instrumented so reality gets a vote quickly.
How do you avoid becoming the person who always says no to AI ideas?
Keep a visible yes record, name the criteria that would flip each no, and bring proposals of your own. Credibility to block comes from having shipped.
What the interviewer is listening for
- Steelmans the proposal before opposing part of it
- Quantifies the risk instead of gesturing at AI mistakes
- Counter-proposes a measured path with promotion criteria, then reports the numbers
What sinks the answer
- Pushback was vibes-based caution with no analysis
- No alternative offered, pure blocking
- Cannot say what the outcome data showed
If you genuinely do not know
Say this instead of freezing. Reasoning out loud from what you do know beats silence every single time, and a good interviewer is listening for exactly that.
“Frame it as [what they wanted and why it was appealing], [the risk in numbers, not vibes], [the counter-proposal that kept the value with a promotion criterion], and [what the data eventually showed about your call].”
Keep going with behavioural
Junior
This field changes monthly. Tell me about a time something you had built became outdated fast, and how you handled it.
Mid
Tell me about a time an AI feature you shipped behaved badly in production. What happened and what did you change?
Mid
Tell me about a technical decision you got wrong on an AI project. How did you find out, and what did you do?
Mid
Describe a time you were pressured to ship an AI feature before you thought it was ready. What did you do?
Senior
Tell me about a time your eval data said one thing and an important stakeholder insisted the opposite. How did you resolve it?
Senior
Tell me about an AI feature that worked technically but users did not adopt or trust. What did you learn?
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