Strategy question
Sierra wants to expand beyond benefits eligibility and case-status support. How would you identify and prioritize the next public-sector workflow for an AI agent, using a framework that weighs constituent pain, mission impact, implementation effort, policy risk, and trust requirements?
- Sierra
- Strategy
- Hard
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What this question tests
Tests strategic prioritization for expanding a public sector AI agent's scope using a framework that weighs mission impact against policy and trust risk.
How to approach it
- List candidate next workflows, for example unemployment claims status, housing assistance, or child care subsidy applications.
- Score each candidate on constituent pain, how often people struggle with this today, and mission impact, how much it affects access to a needed service.
- Score implementation effort and policy risk together, since public sector workflows often have complex eligibility rules with real consequences for getting them wrong.
- Weight trust requirements heavily, since an error in eligibility or benefits guidance can cause real harm, more so than a private sector support error.
- Prioritize the workflow with high constituent pain and lower policy risk first, deferring higher risk, higher complexity workflows until trust is established.
- Validate the framework with the agency's own program staff, since they know the real world consequences of specific policy areas better than an outside team.
What a strong answer includes
- Weights policy risk and trust more heavily than a typical enterprise prioritization framework would, reflecting the higher stakes of public sector errors.
- Sequences toward lower risk, high pain workflows first, building trust before tackling more complex eligibility heavy expansions.
- Validates the framework directly with agency program staff, not just internal assumptions about policy complexity.
Common mistakes
- Applying a generic enterprise prioritization framework without adjusting for the much higher cost of errors in public sector eligibility decisions.
- Choosing the next workflow by technical feasibility alone without weighing policy risk and mission impact.
Likely follow-up questions
- How would you handle a workflow with high constituent pain but also high policy risk?
- What evidence would convince the agency to expand scope faster than planned?
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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