Strategy question
You are a PM for Autonomous Rides at Lyft. Lyft is launching self-driving cars in Palo Alto. Due to mapping constraints, you can only enable a limited number of pickup and drop-off locations initially. How would you prioritize them?
- Lyft
- Strategy
- Hard
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What this question tests
Tests prioritization under a hard operational constraint in a new, safety-critical product: can you name a clear framework for choosing initial autonomous-vehicle pickup zones.
How to approach it
- Clarify the constraint: a limited number of locations must be chosen due to HD-mapping and validation requirements, so criteria must balance demand with what is safely mappable.
- Define the primary criteria: highest predicted ride demand from existing Lyft data combined with the lowest routing complexity, simple curbs and minimal double-parking.
- Add a safety criterion explicitly: prioritize locations where the self-driving system is most thoroughly validated, since safety must override pure demand in an autonomous product.
- Consider strategic value: include a few high-visibility locations near tech campuses or downtown that support the broader launch narrative.
- Sequence the rollout: start with the smallest, most validated set, then expand based on real-world performance data like disengagement rate.
- Define success as completed rides per location and, critically, a disengagement rate that gates any expansion.
What a strong answer includes
- Explicitly places safety validation above pure demand as the primary gating criterion, fundamentally different from a human-driven rollout.
- Uses existing Lyft ride-demand data as a concrete input for prioritization rather than guessing at popular locations.
- Adds high-visibility locations as a secondary, explicitly lower-priority factor, balanced strategic thinking that doesn't override safety.
- Proposes a staged expansion tied to a real safety metric, showing prioritization continues after initial launch.
Common mistakes
- Prioritizing purely by ride demand without treating safety validation as a gating factor specific to autonomous vehicles.
- Treating this like a standard rideshare hotspot analysis, ignoring the unique HD-mapping and validation constraints of self-driving operation.
- No plan for how the location list would expand or be evaluated after initial launch.
Likely follow-up questions
- How would you handle a high-demand location that cannot yet be safely validated?
- What would you do if early disengagement data showed a location was riskier than expected after launch?
- How would you communicate limited initial coverage to riders in a way that manages expectations?
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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