Product design question
How would you improve Discord?
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What this question tests
Tests product sense on a community-driven chat platform, where server health and moderation matter as much as feature polish.
How to approach it
- Segment Discord users: small friend-group servers, large public community servers, and gaming-focused servers, since needs differ sharply.
- Identify a pain point for large public servers: discovery and onboarding, new members often join and get lost with no clear entry point.
- Propose a fix: a structured 'welcome path' with recommended channels and roles based on stated interests, reducing new-member drop-off.
- Consider a second angle: better moderation tooling (AI-assisted spam/toxicity detection) for large servers, since moderation burden is a known pain point.
- Define success: new-member day-7 retention on servers using the welcome path, and reduction in moderator-reported spam volume.
What a strong answer includes
- Segments by server type and size, since a fix for a 10-person friend server is irrelevant to a 100,000-member community.
- Targets onboarding into large servers specifically, a well-known real pain point (new members lurking silently or leaving).
- Uses an illustrative number, e.g. assume 50% of new joiners never send a message in their first week, to motivate the welcome-path fix.
- Adds moderation tooling as a second, distinct improvement, showing awareness Discord's core challenge is community health, not just features.
Common mistakes
- Proposing generic chat features (more emojis, themes) without addressing onboarding or moderation, Discord's actual pain points.
- Treating all servers as the same instead of segmenting by size and purpose.
Likely follow-up questions
- How would you measure whether the welcome path actually increased engagement versus just directing traffic?
- How would you balance automated moderation against false positives silencing real users?
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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