Strategy question
Sales wants a roadmap commitment to close a major enterprise AI deployment this quarter, but Engineering argues the requested functionality is too bespoke and would create long-term platform drag. As the primary product partner to GTM leadership, how would you evaluate the opportunity, make the decision, and align Sales, Engineering, and executive stakeholders around it?
- Scale AI
- Strategy
- Hard
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What this question tests
Whether you can evaluate a bespoke-versus-platform tradeoff rigorously and align Sales, Engineering, and executives around a defensible decision under deadline pressure.
How to approach it
- Get specific on the request: what exactly is being asked for, how much of it is truly one-off versus adjacent to an existing or planned platform capability.
- Quantify the opportunity: deal size, strategic value of the account, and whether closing it unlocks a broader market segment or is genuinely a one-off.
- Quantify the platform-drag risk with Engineering: how much ongoing maintenance the bespoke work would create, and whether a scoped version could satisfy the deal without the full custom build.
- Look for a middle path first, a reduced-scope version that meets the customer's core need without the parts that create long-term drag, before accepting a binary build-or-lose framing.
- Bring Sales, Engineering, and executives together with the quantified tradeoff, not a private recommendation, so the decision has visible buy-in and the reasoning survives scrutiny later.
- Make the call and document the reasoning, including any commitment about whether the accepted work will later be generalized into the platform, so it does not become invisible one-off debt.
What a strong answer includes
- Looks for a scoped middle path before accepting the binary framing Sales and Engineering are stuck in.
- Quantifies both the deal opportunity and the platform-drag cost with real numbers rather than treating it as a values debate.
- Brings the tradeoff to all three stakeholders transparently instead of deciding privately and announcing the outcome.
- Documents whether accepted bespoke work will later be generalized, preventing invisible technical debt.
Common mistakes
- Treating this as a binary yes-to-Sales or no-to-Engineering decision without exploring a scoped middle path.
- Making the decision without quantifying both the deal value and the platform-drag cost.
- No documentation of the decision's reasoning, making it hard to defend or revisit later.
Likely follow-up questions
- How would you quantify platform drag when Engineering's estimate is itself uncertain?
- What would you do if Sales insists on the full scope and Engineering refuses any version of it?
- How would you evaluate whether this decision was right after the fact?
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More questions from Scale AI
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovering and Sizing AI Opportunities
- Chapter 9: Measuring AI Product Economics
- Chapter 14: Interviewing for AI PM Roles