Product design question
Bay area is going to be hosting the soccer world cup in 2026. Design a futuristic vending machine which will be used inside these stadiums. During the design, also touch upon how many of them would you need per stadium?
- Product design
- Hard
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What this question tests
Tests creative product design constrained by a real event context, requiring specific user needs rather than generic futuristic ideas.
How to approach it
- Clarify the goal: revenue per machine, queue relief, or brand experience.
- Segment users at the event into international tourists, local fans, and families with kids.
- Identify pain points at the venue: long lines, cash and currency friction, dietary needs, and language barriers.
- Design core features: contactless multi-currency payment, a multilingual interface, and dynamic inventory restocked from real-time demand data.
- Add one differentiator tied to 2026, such as QR-based reorder for return visits, rather than gimmicks.
- Define success as transactions per hour and reduced queue time versus staffed stands.
What a strong answer includes
- Ties futuristic to a real operational win, faster throughput and shorter lines, instead of pure novelty.
- Addresses the international crowd specifically with multi-language and multi-currency support.
- Uses illustrative numbers as assumptions: assume 80,000 attendees per match, needing 200 transactions an hour per machine to matter.
- Flags placement and restocking logistics as the real constraint, not the technology.
Common mistakes
- Designing a flashy concept with no tie to actual crowd size or logistics.
- Ignoring payment and currency friction for an international audience.
- Treating restocking and logistics as out of scope.
Likely follow-up questions
- How many machines would you need per stadium and why?
- How do you handle a machine running out of stock mid-match?
- What's the business model, sales, ads, or sponsorship?
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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