Strategy question
A new enterprise customer wants Sierra to launch an AI agent for a high-volume support workflow. How would you uncover their requirements, decide what should be handled through configuration or implementation-specific work versus added to Sierra’s core product, and make the tradeoff clear to both the customer and engineering?
- Sierra
- Strategy
- Hard
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What this question tests
Whether you can run structured requirements discovery for an enterprise deployment and draw a clear, defensible line between core product and implementation-specific work.
How to approach it
- Run structured discovery with the customer covering the workflow end to end: volume, common request types, escalation paths, and any unique business rules specific to their process.
- Separate requirements into two buckets as you go: capabilities that look like general patterns other high-volume support customers would also need, and capabilities specific to this customer's unique systems or policies.
- Validate the general-pattern bucket against Sierra's existing roadmap and other customer feedback before committing it to core product, to avoid overfitting to one customer's phrasing of a common need.
- Scope the customer-specific bucket as configuration or an implementation-specific solution, being transparent with the customer about why it will not become a platform feature.
- Make the tradeoff explicit and visible to engineering early, sharing the two buckets and the reasoning, not presenting a finished requirements doc after the fact.
- Set expectations with the customer upfront that some requests will be handled through configuration rather than new product capability, so the distinction does not feel like a rejection later.
What a strong answer includes
- Uses a two-bucket sorting method during discovery itself, rather than treating prioritization as a separate step after requirements are collected.
- Validates the general-pattern bucket against other customer feedback before committing to core product, avoiding overfitting to one customer.
- Sets the configuration-versus-product expectation with the customer early, which prevents a difficult conversation later.
- Shares the reasoning with engineering during discovery, not after, so the roadmap tradeoff is a shared decision.
Common mistakes
- Treating every customer request as either fully core product or fully rejected, without a configuration middle path.
- Committing to core product based on one customer's ask without validating the pattern elsewhere.
- Setting expectations with the customer only after the sorting decision is made, creating avoidable friction.
Likely follow-up questions
- How would you validate a requirement is general without waiting for several more customers to ask for it?
- What would you do if the customer disputes your classification of their request as customer-specific?
- How would you handle a requirement that starts as customer-specific but later shows up elsewhere?
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- You have separate 30-minute meetings with a CIO and an engineering lead at the same prospect. How would you change the demo, proof points, and objections you address for each audience while keeping the core product story consistent?Sierra · Strategy · Medium
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More questions from Sierra
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovering and Sizing AI Opportunities
- Chapter 9: Measuring AI Product Economics
- Chapter 14: Interviewing for AI PM Roles