Strategy question
Two near-term customer commitments pull the platform in different directions: one requires stronger auth and secure-by-default deployment into a constrained environment, while another needs better agent runtime primitives to improve forward-deployed team velocity. Engineering capacity is fixed and both asks are only partially specified. How would you sequence the work, what framework would you use to make the call, and how would you explain that decision differently to platform engineers, FD PMs, and executives?
- Scale AI
- Strategy
- Hard
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What this question tests
Tests structured prioritization under fixed capacity with two under-specified asks, and communicating the same decision to different audiences.
How to approach it
- Clarify both asks first, since both are partially specified: exact constrained-environment auth requirements, and what runtime primitives FD teams actually need.
- Score both on shared criteria: account risk if missed, reusability across other customers, and effort to reach a real estimate.
- Look for a sequencing option instead of a binary choice, like shipping minimal secure-by-default first while prototyping runtime primitives in parallel.
- Make the call explicit with a named owner, since capacity is fixed and both asks are urgent.
- Tailor communication per audience without changing the decision: sequencing detail for engineers, account tradeoff for FD PMs, risk-adjusted value for executives.
- Set a checkpoint to revisit once either scope is firmer.
What a strong answer includes
- Proposes a real sequencing or partial-parallelization option instead of framing it as a coin flip.
- Applies one consistent scoring framework to both asks so the decision is defensible.
- Adapts framing per audience without changing the underlying decision.
Common mistakes
- Treating this as a pure binary choice when phased delivery is possible.
- Giving every audience the identical message instead of adapting the framing.
Likely follow-up questions
- What would you do if the constrained-environment customer walked away during the delay?
- What's your fallback if both scopes turn out larger than expected?
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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: 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