Strategy question
A highly requested Claude-powered workflow could save employees meaningful time, but it may expose sensitive information across teams unless permissions, data handling, and auditability are designed carefully. How would you decide whether to ship it, ship a constrained version, or say no, and what conditions or safeguards would have to be in place?
- Anthropic
- Strategy
- Hard
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What this question tests
Tests risk based decision making for shipping a high value internal AI workflow that carries real cross team data exposure risk.
How to approach it
- Map exactly what sensitive information the workflow could expose, for example one team's compensation data becoming visible through a cross team Claude powered summary.
- Assess the time saved against the specific exposure risk, since a highly requested workflow with low actual sensitivity should ship faster than one touching regulated or confidential data.
- Design permission and data handling safeguards first, such as scoping the workflow to only summarize data the requesting user already has access to.
- Decide among ship as is, ship constrained, or say no based on whether safeguards can realistically be verified before launch, not just designed on paper.
- Require auditability as a condition of shipping any constrained version, for example logging every cross team data access the workflow makes.
What a strong answer includes
- Names the specific sensitive data at risk instead of treating information exposure as an abstract concern.
- Proposes a constrained version, for example limiting the workflow to data the user already has access to, as the default answer rather than a binary ship or don't ship.
- Requires verifiable, not just designed, safeguards before launch, such as an access log that can be audited after the fact.
- Frames the decision as reversible, proposing a narrow pilot with logging before considering a broader rollout.
Common mistakes
- Shipping a time saving workflow without first mapping the specific data it could expose across team boundaries.
- Treating permissions as a policy statement rather than a technically enforced and auditable constraint.
Likely follow-up questions
- How would you audit that the safeguards actually held after launch?
- What would change your answer if the workflow saved dramatically more time than expected?
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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