Strategy question
You are the PM at an online shopping website. One of your engineers wants to launch a "Related products" feature. What do you do?
- Asana
- Strategy
- Medium
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What this question tests
How a PM handles a bottom-up engineering feature request and validates it before committing roadmap capacity.
How to approach it
- Acknowledge the engineer's initiative but don't greenlight immediately; ask what problem they think it solves.
- Check if 'related products' already has signal, for example frequently-bought-together patterns or search abandonment data.
- Check against current priorities: does this compete with a roadmap item already committed for the quarter?
- If the data is promising, scope a lightweight rules-based version to test before a full recommendation engine.
- Define a success metric upfront: incremental attach rate or click-through on the module.
- Decide and communicate clearly: fold it in with a priority, or explain why not now and log it in the backlog.
What a strong answer includes
- Doesn't just say yes or no; investigates existing data, cart abandonment, cross-sell affinity, before deciding.
- Respects engineer motivation while protecting roadmap discipline, a realistic PM balancing act.
- Proposes testing cheaply first, rules-based, before committing to a bigger ML investment.
Common mistakes
- Either blindly approving because an engineer is enthusiastic, or shutting it down without evaluating the idea.
- No success metric defined to judge the feature later.
Likely follow-up questions
- What if the data is inconclusive?
- How would you handle it if the engineer builds it anyway without approval?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop