Product design question
How would you improve YouTube?
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Ability to find a real user pain point in a mature product and propose a focused improvement, not a feature dump.
How to approach it
- Pick a user segment, for example casual viewers versus creators, since 'improve YouTube' means different things to each.
- State a real pain point for that segment, such as difficulty finding a specific moment inside a long video.
- Prioritize this over a list of unrelated ideas, since one deep improvement beats five shallow ones in an interview.
- Propose a solution: AI generated chapter markers and a visual scrub bar showing scene changes.
- Explain why this matters: reduces search time and increases completion rate for long form content.
- Define success as watch time on videos over 20 minutes and search within video usage rate.
What a strong answer includes
- Picks one specific segment and pain point instead of a scattershot list of unrelated feature ideas.
- Ties the proposal to a business outcome, more watch time on long videos, which YouTube's ad model rewards.
- Gives an illustrative number, e.g. assumes a 10 percent increase in completion for videos with auto generated chapters.
- Considers the creator side too, noting chapters could also boost mid roll ad placement opportunities.
Common mistakes
- Listing five unrelated improvements with no depth on any single one.
- Not specifying which user segment the improvement serves.
- No success metric tied to the proposed change.
Likely follow-up questions
- How would you measure if this actually helped users?
- What tradeoff would creators push back on?
- What would you build first if you could only ship one thing?
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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