diagnosis

Low adoption has four usual causes: people don't see it, don't need it, try it and don't trust it, or find it in the wrong place. Each has a cheap test, and the interviewer wants you to run them before redesigning.

Retrieval failures look like model failures to users. This question tests whether you can locate the failure precisely and choose fixes in the order that pays, rather than swapping models.

Use feature parity, time-aware holdouts and delayed outcomes to decide what needs fixing before requesting another training run.

A diagnosis question with five plausible causes. Strong candidates rank them by likelihood and name the cheapest check for each instead of reciting all five.

AI features are unusually good at producing engagement that is actually friction. The question tests whether you can tell the two apart in the data.