Product design question
Design an online news service that provides curated news content that can be trusted by the masses.
- Microsoft
- Product design
- Hard
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What this question tests
Product design addressing a trust and misinformation problem in media, requiring both a curation mechanism and a trust-building signal.
How to approach it
- Identify the core problem: users don't know which sources to trust amid misinformation, and existing aggregators often optimize for engagement over accuracy.
- Define the target user: a news consumer overwhelmed by conflicting sources who wants a single, credible daily digest rather than an infinite algorithmic feed.
- Design the curation mechanism: a hybrid of professional editorial review and cross-source verification, flagging stories confirmed by multiple independent, established outlets.
- Design the trust signal: visible source-credibility ratings and clear labeling of opinion versus reported fact, giving users transparency into why a story is surfaced.
- Define success as a user-reported trust score via periodic survey and repeat daily usage, with a guardrail against optimizing purely for time spent.
What a strong answer includes
- Explicitly rejects a pure engagement-optimized algorithm in favor of a trust-first curation mechanism.
- Names a concrete trust signal, source-credibility labeling, rather than just saying 'curated by experts.'
- Chooses a trust metric as primary, with an explicit guardrail against engagement-driven sensationalism.
Common mistakes
- Designing a standard personalized news-feed algorithm, the exact engagement-optimized model that erodes trust.
- No mechanism for source verification or credibility signaling, leaving 'trusted' an unsubstantiated claim.
Likely follow-up questions
- How would you handle a story where credible sources disagree?
- How would you fund this without engagement-driven ad pressure compromising the curation?
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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