Product design question

Design an algorithm for an elevator during COVID-19.

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

Designing an algorithmic system that balances safety constraints with normal operational efficiency.

Clarify the goal: minimize close contact and crowding in elevators during a pandemic while keeping wait times reasonable.
Define constraints: a maximum occupancy per car well below normal capacity, and spacing rules between passengers.
Design the algorithm: batch requests by direction and destination floor to minimize stops and shared trips among strangers, prioritizing single-party or same-household groups per car.
Add a queuing and signage system so people can see estimated wait and occupancy before boarding, reducing crowding at the door.
Weigh the trade-off explicitly: stricter occupancy limits increase safety but increase wait times and building throughput pressure, especially at rush hour.
Define success metrics: average wait time under capacity limits, and occupancy compliance rate.

Names a concrete occupancy rule, e.g. capping at 2 to 4 people per car depending on car size, as an explicit assumption.
Proposes grouping same-party requests together to reduce unnecessary stranger contact, a specific and testable mechanism.
Gives an illustrative trade-off, e.g. average wait time rising from 30 seconds to 90 seconds under the new limit, marked as an assumption.
Addresses rush hour separately, since fixed occupancy limits could create serious lobby crowding without a queuing plan.

Designing only the elevator logic without addressing lobby crowding and queuing.
Ignoring the explicit trade-off between safety and wait time or throughput.

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