Product design question

Design a self driving car.

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Tests product design breadth for a complex, multi-stakeholder system, requiring the candidate to scope down rather than design everything.

Scope down to the passenger experience rather than the full autonomy stack, since that is the PM-appropriate layer.
Segment on solo commuters, families, and accessibility-focused riders like visually impaired passengers.
Identify pain points: trust in the vehicle's decisions, in-ride comfort, and handling edge cases like construction or emergency vehicles gracefully.
Design a passenger dashboard showing the car's reasoning in real time, what it sees and why it's slowing down, plus simple controls like pull over or request human support.
Define success as rider trust score via survey, ride completion without manual intervention requests, and repeat ridership.

Explicitly scopes the huge prompt down to passenger experience rather than attempting to design the entire autonomy stack.
Centers trust-building, a real-time reasoning display, as the key UX problem specific to self-driving, unlike a normal rideshare UX.
Addresses accessibility-focused riders as a distinct segment, not an afterthought.

Trying to design the full technical autonomy system, sensors and ML, instead of scoping to a PM-appropriate layer.
Not addressing the unique trust problem self-driving introduces versus a human-driven ride.

Chapters of the AI PM course that teach what this question tests.