Product design question
A Fortune 500 health plan wants Decagon to automate benefits and eligibility plus prior-authorization status across voice and chat, but compliance, clinical, and security leaders are worried about PHI, consent, and unsafe responses. How would you scope a first production launch: which intents, channels, and member segments would you include or exclude; what escalation and approval rules would you set; and what evidence would you bring to get executive sign-off?
- Decagon
- Product design
- Hard
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What this question tests
Whether you can scope a first regulated healthcare launch with real precision on inclusion and exclusion, and bring the specific evidence needed to get compliance, clinical, and security sign-off, not just product sign-off.
How to approach it
- Scope intents narrowly to start: include benefits and eligibility status checks, which are largely factual lookups, and prior-authorization status checks, which are also status lookups rather than clinical judgment calls.
- Exclude anything requiring clinical interpretation or advice at launch, and exclude high-ambiguity member segments, like members with complex multi-plan histories, until the narrower cases prove reliable.
- Scope channels by risk: start with chat, where responses are logged and reviewable, before voice, where real-time misunderstanding is harder to catch and correct in the moment.
- Set escalation rules explicitly: any request touching PHI beyond the scoped intents, any expression of clinical concern, or any low-confidence response escalates immediately to a human, with no AI-generated clinical guidance ever surfaced.
- Bring compliance, clinical, and security leaders evidence specifically suited to their concerns: audit logs and consent flow documentation for compliance, accuracy and escalation-rate data from a controlled pilot for clinical, and access control and data handling documentation for security, rather than one generic readiness deck.
What a strong answer includes
- Scopes intents by risk type (factual lookup versus clinical judgment) with real precision, rather than a vague safe-topics list.
- Sequences channels by reviewability, starting with chat before voice, reflecting genuine understanding of where real-time healthcare AI risk concentrates.
- Tailors evidence to each stakeholder group's actual concern, audit logs for compliance, pilot accuracy data for clinical, access controls for security, instead of one generic pitch to all three.
Common mistakes
- Scopes the launch broadly across all intents and channels at once, ignoring the stated compliance and clinical concerns.
- Brings one generic readiness presentation instead of evidence tailored to what each stakeholder group specifically needs to sign off.
Likely follow-up questions
- How would you handle a member request that sits right on the boundary of the scoped intents.
- What pilot data would you need before adding voice as a channel.
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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