Product design question
What feature would you add to a self-driving car to make it a more attractive purchase?
- Product design
- Easy
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What this question tests
Tests basic product sense on an emerging category, picking one concrete feature tied to a real adoption barrier rather than a generic wish list.
How to approach it
- Clarify the target buyer: an early-mainstream car buyer weighing a self-driving car against a traditional one, not a tech-enthusiast early adopter.
- Identify the core barrier: trust in the car's judgment in ambiguous situations, and a feeling of losing control during the drive.
- Propose a transparent real-time explanation layer, a visible readout of why the car slowed down or changed lanes, to build trust through explainability.
- Address the trade-off: too much information could distract or overwhelm, so keep it glanceable and optional to expand.
- Consider a complementary feature: a simple confidence indicator showing the car's certainty level, letting the driver intervene when confidence is low.
- Define success: buyer trust scores in test drives, and reduction in manual takeover frequency over time as trust builds.
What a strong answer includes
- Identifies trust, not convenience features, as the core barrier for self-driving car adoption, showing real market understanding.
- Proposes a specific, buildable feature, an explainability readout, rather than a generic make-it-safer answer.
- Addresses the information-overload trade-off explicitly, showing UX judgment.
- Defines success with a trust-related metric tied directly to the adoption barrier, not just feature usage.
Common mistakes
- Proposing generic comfort features like better seats or entertainment that ignore the real adoption barrier of trust.
- Ignoring the risk of information overload when adding real-time explanatory data.
Likely follow-up questions
- How would you test whether explainability actually increases trust versus just adding noise?
- How would this feature differ for a nervous first-time buyer versus a repeat buyer?
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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