Strategy question
A customer's executives want an aggressive launch date for a complex agent, but Forward Deployed Engineers believe the full scope carries material integration and reliability risk. How would you re-scope the deployment, sequence milestones, and align customer and internal stakeholders so that you protect trust without slipping into an open-ended implementation?
- Decagon
- Strategy
- Hard
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What this question tests
Tests re-scoping a deployment under executive launch pressure without either slipping into scope creep or ignoring engineering risk signals.
How to approach it
- Get FDE's risk assessment in specific terms: which parts of the full scope carry the integration or reliability risk, not a general 'it's risky' statement.
- Split the scope into a reduced v1 that avoids the highest-risk integrations and a fast-follow phase for the rest.
- Set milestone-based checkpoints tied to real system behavior, like error rates in a staging environment, not just calendar dates.
- Present the re-scoped plan to the customer's executives as protecting their launch date for the core value, not as a delay.
- Get explicit agreement from FDEs on the reduced v1 scope so the team is not silently absorbing the original risk anyway.
- Define what would trigger further scope cuts or a real delay, so the plan does not quietly become open-ended.
What a strong answer includes
- Names a concrete reduced-scope v1 rather than a vague 'let's descope some things' plan.
- Uses real milestone checkpoints, like staging error rates, to decide whether to proceed, not calendar dates alone.
- Sets explicit trigger conditions for further delay, preventing the deployment from becoming open-ended.
Common mistakes
- Agreeing to the aggressive date without actually reducing the risky scope.
- Letting the re-scoped plan drift into an open-ended timeline with no checkpoints.
Likely follow-up questions
- How would you handle it if the customer rejects the reduced v1?
- What would you do if a staging checkpoint failed right before launch?
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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