Product design question
How would you design a futuristic shoe?
- Epifi
- Product design
- Easy
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Tests scoped, forward-looking product design for a physical consumer product, requiring a specific user need rather than generic futurism.
How to approach it
- Narrow scope: pick one real, high-value use case, like adaptive fit and injury prevention for runners, rather than a vague futuristic-features list.
- Segment on recreational and amateur runners who lack access to professional biomechanic analysis but care about performance and injury prevention.
- Identify the pain point: ill-fitting shoes and poor gait awareness contribute to common running injuries, and runners rarely get professional gait analysis.
- Design a shoe with embedded sensors tracking gait, pressure distribution and stride pattern, paired with an app giving real-time form feedback and injury-risk alerts.
- Define success as reported injury-rate reduction among users and engagement with the app's coaching feedback over a training season.
What a strong answer includes
- Grounds futuristic technology in a concrete, valuable use case, injury prevention, rather than novelty for its own sake.
- Targets a specific underserved segment, amateur runners without access to professional gait analysis.
- Picks a meaningful outcome metric, injury reduction, over a vanity metric like units sold.
Common mistakes
- Listing flashy futuristic features, like self-lacing or light-up soles, with no real user problem behind them.
- Ignoring how the sensor data would be validated as clinically or practically meaningful for the user.
Likely follow-up questions
- How would you validate the sensor data's accuracy against real biomechanic research?
- How would you price this against premium running shoes already on the market?
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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