Product design question
Glean wants Enterprise Intelligence to move beyond reactive search into proactive insights. What is the first leader-facing use case you would prioritize, and how would you justify it over adjacent options? Walk through the customer pain, why Glean is uniquely suited to solve it, the MVP workflow you would ship first, and the business outcomes you would use to decide whether to double down.
- Glean
- Product design
- Hard
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What this question tests
Tests strategic prioritization for a new product direction, moving from reactive search to proactive insight, with a clear MVP and go or no go criteria.
How to approach it
- Ground the choice in a specific pain, for example leaders repeatedly searching for stalled project status instead of being told proactively.
- Explain why Glean specifically is positioned to solve it, since it already indexes the cross system data needed.
- Compare against adjacent options, for example a generic productivity digest, and explain why the chosen use case has clearer evidence.
- Define the MVP narrowly, a weekly proactive summary of at risk projects for one leader role, not a general platform.
- Set outcomes for doubling down, such as a target share of leaders acting on a surfaced insight within two quarters.
What a strong answer includes
- Grounds the use case in a specific, named customer pain rather than a broad proactive insights vision, which makes the prioritization concrete.
- Explains Glean's unique advantage, its existing cross system index, rather than treating this as a feature any competitor could build equally fast.
- Names the adjacent option it beat and why, for example a generic activity digest lost out because it lacked a clear action.
- Sets a numeric double down threshold up front, such as twenty percent of pilot leaders acting weekly, so the decision is not gut feel later.
Common mistakes
- Proposing a broad proactive insights vision without picking one specific, testable first use case.
- Skipping the explanation of why Glean is uniquely suited, which is what separates this from a generic BI dashboard pitch.
Likely follow-up questions
- What would you do if the pilot showed high engagement but leaders said the insights felt obvious?
- How would you decide between two equally promising leader facing use cases?
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More questions from Glean
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