Product design question
Design a new feature for Twitter that improves the new user’s experience.
- Product design
- Medium
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What this question tests
Tests product design focused specifically on new-user onboarding, requiring the candidate to identify the unique cold-start problem versus improving the product for existing users.
How to approach it
- Clarify the pain point: new Twitter users face an empty or confusing timeline and don't know who to follow or how the conversational format works, leading to early drop-off.
- Identify the core new-user job: quickly build a timeline that feels alive and relevant, and understand the basic mechanics (replies, Retweets, threads) without being overwhelmed.
- Propose a solution: an interactive onboarding flow that has the user pick 5-8 interests, suggests accounts to follow based on those interests, and includes a short interactive tutorial showing how to reply/Retweet on a sample Tweet.
- Address a common failure mode: generic 'follow these celebrities' suggestions feel irrelevant, so ground suggestions in specific stated interests plus early behavior (who they engage with in the first session).
- Sequence the flow to avoid overload: don't front-load every feature at once, instead surface features contextually (e.g., explain threads the first time the user opens one).
- Define success: Day-1 to Day-7 retention for new users who complete onboarding versus those who skip it, and number of accounts followed in the first session as a leading indicator.
What a strong answer includes
- Focuses specifically on the cold-start problem (empty timeline, unclear mechanics) rather than general Twitter improvements unrelated to new users.
- Proposes contextual, just-in-time education instead of front-loading a lengthy tutorial that increases drop-off.
- Grounds follow suggestions in both stated interests and early behavioral signals, addressing a known weakness of generic onboarding.
- Defines success using new-user-specific retention cohorts (Day-1 to Day-7) rather than platform-wide metrics.
Common mistakes
- Proposing a generic feature improvement unrelated to the new-user cold-start problem.
- Overloading the onboarding flow with too many steps, which itself causes drop-off.
- No new-user-specific success metric, using overall platform metrics instead.
Likely follow-up questions
- How would you personalize this differently for someone coming from an ad campaign versus organic sign-up?
- How would you know if onboarding is too long?
- How would you test different versions of the follow-suggestion algorithm?
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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