I spent the first minute just trying to figure out what angle to take.
Start by clarifying the scope and constraints of the self-driving car feature, then propose a user-centric feature that addresses a real pain point, and finally outline how you would validate and iterate on it. Focus on demonstrating structured thinking, technical feasibility, and alignment with Google's mission.
Pro tip: Anchor your feature in a specific user scenario and quantify its potential impact (e.g., safety, efficiency, or accessibility) to show you think like a product engineer, not just a coder.
Ask questions to understand the target user, use case, and constraints (e.g., level of autonomy, regulatory environment, existing features). This shows you avoid assumptions and scope the problem effectively.
Choose a specific pain point or opportunity (e.g., reducing motion sickness, improving accessibility for disabled riders, optimizing energy efficiency) and justify why it matters.
Describe the feature clearly, including how it works from a user and technical perspective. Explain how it leverages sensors, AI, or data to deliver value.
Discuss technical challenges, required data, potential risks, and how you would measure success (e.g., safety metrics, user satisfaction, adoption rate).
Explain how you would test the feature (simulations, pilot programs) and iterate based on feedback, emphasizing safety and continuous improvement.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.