Product design question
Design a Google product for the Olympics.
- Product design
- Hard
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What this question tests
Tests time-boxed, high-visibility event product design, requiring a scoped idea tied to Google's real existing assets rather than a new platform.
How to approach it
- Clarify the constraint: this is a temporary, high-traffic event, so the product should extend existing Google surfaces, Search and Maps, rather than launching a standalone new app.
- Segment on casual fans following the Olympics through search and news, the largest audience, rather than hardcore sports-only viewers.
- Identify the pain point: schedules, live scores, and venue logistics are scattered across many sources during a short, intense event window.
- Design a Search and Maps integration: live schedules and scores surfaced directly in Search results, plus Maps venue navigation, transit info and crowd-level guidance for in-person attendees.
- Define success as Search query volume served directly without a click-out, and Maps usage by attendees navigating Olympic venues.
What a strong answer includes
- Correctly scopes to Google's existing high-traffic surfaces, Search and Maps, instead of proposing a slow-to-build standalone app for a short event window.
- Names a real logistics pain point, scattered schedules and venue navigation, grounded in what a global event like this actually needs.
- Separates the at-home fan use case from the in-person attendee use case, addressing both distinctly.
Common mistakes
- Proposing an entirely new standalone app for a short, one-time event window, unrealistic given the build timeline.
- Ignoring the in-person attendee's logistics needs and focusing only on at-home content consumption.
Likely follow-up questions
- How would you handle real-time score accuracy and latency during live events?
- How would you sunset this after the Olympics end without wasting the engineering investment?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop