AI & Technical question
Suppose Glean wants to launch a new answer-generation experience in core search. How would you define the MVP and rollout plan given enterprise constraints around permissions, citations, latency, model choice, and admin controls? What would need to be true before you scaled it broadly?
- Glean
- AI & Technical
- Hard
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What this question tests
Tests defining a scoped MVP and rollout plan for a high-stakes enterprise AI feature under real permissions, latency, and trust constraints.
How to approach it
- Scope the MVP narrowly: answer generation limited to a subset of content types and a controlled pilot group of customers first, not a full core-search replacement.
- Require permissions-aware retrieval from day one, since an answer generated from content the user should not see is a launch blocker, not a fast-follow.
- Require inline citations back to source documents so users can verify answers, rather than shipping opaque generated text.
- Set a latency budget for the answer-generation path that does not degrade the existing fast search experience for users who do not need generated answers.
- Give admins explicit control to disable answer generation per workspace or content type, since enterprise trust requires an opt-out, not just an opt-in.
- Define what must be true before scaling broadly: permission-leak rate near zero in pilot, citation accuracy above a set bar, and latency within budget.
What a strong answer includes
- Treats permissions-aware retrieval as a launch blocker, not a fast-follow, correctly reflecting the highest enterprise risk in this feature.
- Requires citations as a core trust mechanism rather than an optional nice-to-have.
- States concrete scale-gate criteria, near-zero permission leaks and a citation-accuracy bar, rather than a vague 'once it's ready' plan.
Common mistakes
- Treating citations or admin controls as fast-follow items instead of launch requirements.
- No explicit criteria for when to scale beyond the pilot group.
Likely follow-up questions
- How would you test for permission leaks before the pilot goes live?
- What would you do if latency and answer quality trade off directly?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 1: Foundations: the model and the decisions it forces on you
- Chapter 8: Evals: define good and make the number defensible
- Chapter 6: Agents and agentic architecture