Product design question
How would you improve Sierra's AI agents to resolve more customer issues without escalation?
- Sierra
- Product design
- Medium
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Product improvement for a conversational AI agent product, focused on the core outcome metric of resolution without human handoff.
How to approach it
- Define the current gap: identify the top reasons agents escalate today, such as ambiguous customer intent, missing account context, or policy edge cases the agent is not confident handling.
- Improve intent understanding: add clarifying-question flows so the agent asks for missing detail instead of escalating on ambiguity.
- Expand safe autonomy: give the agent access to more account and order context (with proper permissions) so it can resolve issues that today require a human to look something up.
- Add confidence-based fallback: when the agent is uncertain, have it attempt a best resolution with a clear confirmation step rather than immediately escalating.
- Build a continuous improvement loop, reviewing a sample of escalated conversations weekly to identify new automatable patterns.
- Define success as resolution rate without escalation, paired with a customer satisfaction guardrail, since faster resolution without satisfaction is a false win.
What a strong answer includes
- Grounds the improvement plan in specific, named escalation reasons rather than a generic 'make the AI smarter' answer.
- Proposes concrete mechanisms (clarifying questions, expanded context access, confidence-based fallback) tied to those reasons.
- Builds a feedback loop from real escalated conversations, a practical and scalable improvement mechanism.
- Pairs the resolution-rate goal with a satisfaction guardrail, avoiding a metric that rewards resolving issues poorly just to avoid escalation.
- Shows awareness that expanding autonomy must be paired with proper permissioning and safety.
Common mistakes
- Proposing to just 'add more training data' without identifying specific escalation causes.
- Ignoring the satisfaction guardrail, risking a metric that rewards false resolutions.
Likely follow-up questions
- How would you identify new automatable patterns from escalated conversations?
- What would you do if resolution rate rose but satisfaction dropped?
- How would you balance autonomy against the risk of a wrong resolution?
More product design questions
- Design an agent that works seamlessly across chat, voice, email, and SMS.Sierra · Product design · Hard
- If you joined Sierra today, what developer-facing platform capabilities would you put in v1 to help engineers deploy, observe, and iterate on AI agents reliably? Be specific about the first APIs, SDKs, workflows, or internal tools you would build, who they serve, and what criteria would determine whether something belongs in the initial platform versus a later release.Sierra · Product design · Medium
- A large healthcare payer wants Sierra to launch a customer-support agent in 8 weeks. How would you discover requirements, choose the first workflows to automate, and define an MVP that is safe enough for launch but still delivers measurable value?Sierra · Product design · Hard
- Sierra is launching the first version of its Agent SDK for enterprise developers. What would you include in the v1 launch scope, and how would you prioritize among core integration primitives, customization hooks, observability, safety controls, and brand configuration? Be explicit about the tradeoffs you would make to balance fast time-to-value with enterprise requirements.Sierra · Product design · Hard
- Sierra is considering a new SDK capability to help companies create more brand-aligned, human-sounding agents. How would you identify the right opportunity, validate that customers will use it, and decide whether it is worth investing in as a 0→1 product bet?Sierra · Product design · Hard
- You’re onboarding a large Arabic-speaking enterprise customer to Sierra. How would you discover their support workflows, identify the highest-value use cases, and define the v1 AI agent scope, including which intents to automate, which cases to escalate to humans, and what tradeoffs you would make across customer experience, implementation speed, and safety?Sierra · Product design · Hard
More questions from Sierra
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