AI Mock Interview
Time boxed product design, execution and strategy mocks with rubric grading on structure, prioritization and tradeoff clarity, plus written feedback you can iterate on.
Open AI Mock InterviewInterviewOra feeds you the right framework the moment a question lands. Product design, strategy, execution, estimation and behavioral answers structured the way Google, Meta and Stripe expect them.

Three tools that turn product sense from a vibe into a repeatable structure.
Time boxed product design, execution and strategy mocks with rubric grading on structure, prioritization and tradeoff clarity, plus written feedback you can iterate on.
Open AI Mock InterviewSits silently above Zoom, Meet or Teams. Streams the right framework, the metric tree and the recommendation scaffold the moment the panel finishes the prompt.
Where smart PMs lose loops, and what senior signal sounds like instead.
You hear 'design a feature for X' and immediately list three features, skipping users, goals and success metrics. The interviewer scores you as junior.
Two minutes of clarifying questions, pick a user segment, state the goal in one sentence, then prioritize three solutions against an explicit metric.
Engagement drops 8 percent and you spitball causes for ten minutes. No segmentation, no funnel, no hypothesis ranking, so you never name the root cause.
Internal vs external, then segment by platform, geo and cohort. Walk the funnel top to bottom. Rank hypotheses by likelihood and ease to validate.
Market sizing collapses into messy multiplication, you pick population numbers from nowhere and the partner cannot follow your assumptions.
State your top down or bottom up choice, anchor each assumption out loud, round numbers to one significant figure, sanity check against a known benchmark.
Five rounds, one copilot. Structure on every answer, every time.
Product design gets CIRCLES. Strategy gets Porter or 3C. Execution gets a metric tree. Surfaced contextually, never name dropped, with the prompts to fill it in.
Pros and cons surfaced as you speak so you can pick a recommendation with conviction instead of rambling about three equally weighted options.
Market sizing, revenue and capacity math broken into clean assumptions and round numbers a partner will accept, with a sanity check against a known benchmark.
STAR stories grounded in your real launches, scoped for Google, Meta, Amazon, Microsoft or Stripe rubrics, with the metric and the tradeoff baked into every answer.
Eight things to lock in before you sit down for a PM loop.
Two you use daily, one in the company's space. Be able to name three user pain points, the north star metric and one feature you would ship next.
CIRCLES for design, AARRR for growth, RICE for prioritization, North Star metric trees for execution, Porter Five Forces for strategy. Practice naming the right one in 10 seconds.
DAU equals new plus retained plus resurrected, broken down by platform, geo and cohort. Rehearse it on three real products until it is muscle memory.
Market size for a B2B SaaS, revenue for a marketplace, infrastructure cost for a feature. Bottom up, top down and capacity math, round numbers.
Launch you led, conflict with engineering, ambiguous problem, hard prioritization call, failure with a learning and influence without authority. Each under three minutes.
Pull two specific product or business facts you can drop into your strategy and behavioral answers. This is the single fastest signal of preparation.
One product design, one execution. Score yourself on structure, prioritization, metric clarity and recommendation strength. Re run any below 4 out of 5.
APM bullets show launches. Senior PM bullets show metrics. GPM bullets show org level impact. Strip the rest. Match keywords to the JD.
One free real interview, no credit card required.