Strategy question
You inherit Vault with strong customer interest but limited engineering capacity. How would you set Vault’s product vision and a 12-month roadmap across file management, AI search/Q&A, document extraction, secure sharing, and platform investments like permissions, indexing, and integrations? Walk through your prioritization framework, major bets, and what you would explicitly defer.
- Harvey
- Strategy
- Hard
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What this question tests
Tests setting a product vision and prioritized 12-month roadmap across five capability areas with limited engineering capacity, and defending explicit deferrals.
How to approach it
- Assess current signal across file management, AI search and Q&A, document extraction, secure sharing, and platform investments, using customer usage data and the loudest recurring feature requests.
- Identify the platform investments, permissions, indexing, integrations, that block or slow every other capability, since a weak permission model undermines trust in search and sharing alike.
- Sequence platform investment early even though it's less visible, since AI search and Q&A quality and trust depend on solid indexing and permissioning underneath.
- Prioritize AI search and Q&A as the primary differentiated bet after the platform foundation, since it's most aligned with why customers adopt an AI product over a plain file store.
- Defer explicitly: advanced document extraction workflows and expanded secure sharing features, framing them as valuable but sequenced after the higher-leverage platform and search investments.
- Set 12-month milestones per quarter, and build in a checkpoint to re-prioritize the deferred areas based on customer feedback once the platform and search bets are live.
What a strong answer includes
- Sequences unglamorous platform investment, permissions and indexing, before the flashier AI search feature, since it underpins trust in everything else.
- Picks AI search and Q&A as the primary differentiated bet, tying it explicitly to why customers choose an AI-native product.
- Explicitly defers document extraction and secure sharing, naming them rather than silently dropping them, and gives a reason tied to leverage.
- Builds a checkpoint to revisit deferred areas after the foundational bets ship, rather than a fixed, unchangeable 12-month plan.
Common mistakes
- Chasing the most requested feature first without checking whether platform foundations can support it reliably.
- Trying to advance all five areas simultaneously with a lean team, diluting progress everywhere.
- Deferring capabilities silently instead of communicating the tradeoff and reasoning to stakeholders.
Likely follow-up questions
- How would you decide if the platform investment is taking too long relative to search?
- What would move document extraction up the roadmap earlier than planned?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop