Product design question
Ghostwriter can propose changes to prompts, journeys, routing logic, and integrations. How would you define a decision framework for which changes the system can apply automatically versus which must require human approval, change review, or a separate workspace before going live?
- Sierra
- Product design
- Hard
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What this question tests
Tests designing a risk-based decision framework for which AI-proposed changes to a live production system can auto-apply versus require human review.
How to approach it
- Categorize the change types Ghostwriter can propose: prompt tweaks, journey changes, routing logic, and integration changes, since blast radius differs.
- Assess reversibility and blast radius per category, since a routing logic change can affect many live conversations at once.
- Set auto-apply eligibility for low-risk, easily reversible changes that pass the simulation suite with a wide margin.
- Require human approval for changes touching integrations, routing, or anything affecting customer-facing commitments like refunds.
- Provide a separate workspace for CX teams to preview higher-risk changes before they go live, regardless of tier.
What a strong answer includes
- Tiers changes by blast radius and reversibility, not just type, since some prompt changes can also be high-risk depending on the journey.
- Requires simulation results to clear a defined margin before any auto-apply, not just a pass or fail.
- Keeps integration and routing changes behind mandatory human review given their broader operational impact.
- Gives CX teams a preview path for any change they want to inspect, even auto-apply-eligible ones.
Common mistakes
- Drawing the auto-apply line purely by change type instead of actual risk and reversibility.
- Making everything require human approval, defeating the purpose of an AI copilot for a non-technical CX team.
Likely follow-up questions
- What would happen if a supposedly low-risk auto-applied change caused unexpected customer harm?
- How would you build trust with a CX team nervous about auto-applied changes?
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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