Your company wants to add generative AI to its core product. How would you decide what to build and how to launch it responsibly?
What the interviewer wants to hear
- Start from user problems where AI is clearly better
- Evaluate quality, risks and failure modes with eval sets
- Model costs and pricing
- Design for trust: transparency, control, human fallback
- Staged rollout with monitoring, feedback and safeguards
Model answer
I would start with problems, not the technology. I look for jobs where AI is clearly better than existing approaches, such as summarising long documents or drafting routine replies, and where mistakes are tolerable or easy to catch. For each candidate I prototype quickly and build an evaluation set from real examples, measuring accuracy, harmful outputs and edge cases against clear quality bars. I model unit economics, because each request has a real cost, and decide pricing, limits or model choice accordingly. The design must build calibrated trust: label AI content, show sources, let users edit and undo, and offer a human fallback. Privacy and data use must be clear and approved by legal. Then I launch gradually with a beta, monitoring quality, cost and feedback, and keep improving the evaluations as we learn.
Can you answer it under time pressure?
Take a timed hard round and get scored on every answer.
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