decision making

A judgment call with no default answer. Principal-level candidates segment the users, price the value, check the strategic role, and make a decision with a dated review rather than a vague 'improve it'.

Opinions about prompts are cheap. A small grid of prompts by models on fifty real examples turns a debate into a table, and the interviewer wants to see you build it.

A working prototype is the start of the decision, not the end. The interviewer wants evidence on value, feasibility at real quality, cost, risk and strategic fit, and a decision rule set before the evidence arrives.

Stopping work is one of the hardest PM decisions, and AI projects need it often because feasibility is uncertain. Panels want evidence, criteria, timing and care for the team.

A common behavioural prompt with an AI twist: model capability itself is uncertain. A good answer turns ambiguity into small, time-boxed experiments with clear decisions at the end.

A principal-level behavioural question. Panels want to see how you built alignment across leaders with different incentives, used evidence and clear decision rights, and carried the decision through to adoption.

Most decisions should be fast; a few should be slow. Show that you classified the decision first, and that you turned one irreversible step into several reversible ones where you could.