Product design question
How would you further improve YouTube's share feature?
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What this question tests
Tests incremental feature improvement on a high-frequency, low-glamour utility feature.
How to approach it
- Identify the friction: sharing a video often loses context, no timestamp, no reason why it's being shared.
- Segment sharing to a messaging app from sharing to social media, since context needs differ.
- Identify the pain point: the recipient doesn't know what part of a long video to watch or why it was sent.
- Propose default timestamp-anchored share links, an optional short note attached to the share, and smarter share-sheet ranking by who you share with most.
- Define success as click-through rate on shared links, watch time of the shared segment, and repeat-share rate.
What a strong answer includes
- Identifies the specific friction, lost context on long videos, instead of a generic make-sharing-easier answer.
- Proposes a lightweight annotation mechanic that increases the recipient's reason to click.
- Ties the metric to recipient behavior, not just sender-side sharing volume.
Common mistakes
- Proposing a full share-sheet redesign without identifying the core friction, context loss.
- Giving no clear success metric tied to recipient behavior.
Likely follow-up questions
- How would you measure whether added context actually increases watch-through?
- Would you make timestamp-sharing default or opt-in?
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- Enhance the YouTube experience for creators.Google · Product design · Easy
- Design a learning experience product for YouTube.YouTube · Product design · Easy
- How would you increase the frequency of YouTube (visits/week/user)?YouTube · Product design · Easy
- How would you improve battery life on YouTube mobile without making changes to the UI/UX?YouTube · Product design · Easy
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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