Product design question
Anthropic wants to unlock more powerful capabilities only for higher-trust organizations across cloud partners. How would you design the trust tiers: eligibility criteria, verification workflow, attached controls, and escalation paths, while balancing enterprise adoption against abuse, compliance, and operational risk?
- Anthropic
- Product design
- Hard
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What this question tests
Tests designing a graduated access and verification system that unlocks value for trusted enterprises while managing abuse, compliance, and operational risk.
How to approach it
- Define what higher trust unlocks, such as higher rate limits or access to preview capabilities.
- Set eligibility criteria combining objective signals, like verified business identity and spend history, with behavioral signals like a clean usage history.
- Automate verification for well-documented enterprises, reserving manual review for edge cases.
- Attach controls proportional to tier, so higher tiers get expanded capability alongside stricter monitoring.
- Build an escalation and appeals path so a misclassified organization can contest a tier decision quickly.
What a strong answer includes
- Ties tier criteria to hard-to-fake signals, for example a verified domain plus 90 days of low-violation usage, rather than self-attestation.
- Designs de-escalation as a first-class mechanism, not just promotion, since a trusted org can still go bad.
- Balances partner constraints, since each cloud partner exposes different identity verification data.
- Names the abuse risk explicitly, such as a shell company reaching a higher tier to unlock capability.
Common mistakes
- Making verification so manual it bottlenecks legitimate enterprise adoption.
- Treating trust as a permanent status instead of one continuously re-evaluated.
Likely follow-up questions
- What would trigger an automatic tier downgrade?
- How would you verify identity consistently when partners expose different data?
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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 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop