Product design question
Design a v1 Enterprise Intelligence experience for a department leader at a large company. Be specific about the main dashboard, the top 2-3 insights it should surface, what actions the leader can take from each insight, and what evidence or context you would show so the user trusts the recommendation enough to act.
- Glean
- Product design
- Hard
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What this question tests
Tests product design skill for a v1 leader facing analytics dashboard, including insight selection, actionability, and evidence based trust.
How to approach it
- Pick a concrete persona, for example a VP of Engineering at a mid size company, since a generic leader is too broad to design for.
- Choose two to three high leverage insights, for example team burnout risk, delivery risk, and knowledge gaps surfacing in search.
- Lay out the dashboard as cards, each with a headline metric, trend direction, and a one line explanation of why it matters now.
- Attach a specific action to each insight, for example a one click way to message the at risk team lead.
- Show the underlying evidence behind each insight, such as source tickets, so the leader can verify before acting.
- Define v1 success as the share of surfaced insights that lead to an action within a week.
What a strong answer includes
- Picks a specific, named persona and company context instead of a generic leader, which grounds every later design choice.
- Limits to two or three insights, explaining why more would overwhelm a leader who checks occasionally, not daily.
- Pairs every insight with an action and its evidence, for example a burnout signal next to workload data and a direct outreach action.
- Proposes action rate, not pageviews, as the core v1 metric, since a dashboard viewed but not acted on has failed its purpose.
Common mistakes
- Designing too many insights, which dilutes attention for an occasional user.
- Showing an insight without evidence, so the leader has no way to verify it before acting.
Likely follow-up questions
- How would you decide which insight to cut if you could only ship one?
- What would make a leader stop trusting an insight after using it a few times?
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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