Strategy question
Forward-deployed teams and sales bring in a steady stream of enterprise requests, custom dashboards, data exports, QA workflows, and model-specific controls. As PM for the Agent Data Platform, how would you decide which requests remain bespoke, which should become configurable platform features, and how those decisions should shape the roadmap?
- Sierra
- Strategy
- Medium
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What this question tests
Platform product judgment for a PM fielding constant custom requests: can you decide what earns generalized configurability versus what stays a one-off, and let that shape the roadmap deliberately.
How to approach it
- Categorize incoming requests by type: dashboards, exports, QA workflows, model-specific controls, and look for repeated shape within each category, not just repeated volume.
- Ask two questions per request: would two or more other customers likely want this, and does building it generally cost meaningfully more than a one-off.
- Configurable platform features win when the underlying need is common but the specifics vary, for example a dashboard builder instead of five custom dashboards.
- Bespoke stays bespoke when the request is truly account-specific or when demand is too early to justify generalized investment.
- Let the ratio of bespoke to platform requests coming from sales and forward-deployed teams inform roadmap weighting each quarter, rather than reacting request by request.
What a strong answer includes
- Uses a repeatable two-question test (likely repeat demand, generalization cost) instead of case-by-case gut calls.
- Gives a concrete example, like a dashboard builder replacing one-off dashboards, showing the platform pattern in practice.
- Connects the categorization directly to roadmap weighting, closing the loop from request to plan.
Common mistakes
- Builds every popular request as a one-off instead of asking whether it generalizes.
- No criteria for saying no to a request that seems reasonable but does not generalize.
Likely follow-up questions
- How would you handle a request from your biggest account that does not generalize well.
- How often would you revisit the bespoke-versus-platform categorization.
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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