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Google·Software Engineer·Onsite - Product Sense / Strategy·Staff

StaffPrefer not to say
May 2026

Summary

Got a product strategy question at Google for a lead PM role, basically a big open-ended problem about fake drugs and what you'd build to solve it. No fluff, just got dropped straight into the deep end.

Questions Asked (1)

Q1

You're a lead PM at Google and your mandate is to eliminate counterfeit drugs. What product would you build?

Product Sense & IdeationProduct StrategyAdaptability & Ambiguity
Author's notes

This one is deceptively wide.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem scope and constraints, then propose a product that leverages Google's strengths in data, AI, and scale. Focus on a specific user segment and a clear value proposition, and outline how you would measure success and mitigate risks.

Pro tip: Show awareness of the complex ecosystem (regulators, manufacturers, pharmacies, patients) and propose a solution that complements existing efforts rather than duplicating them. Emphasize privacy and security, as counterfeit drugs often involve sensitive health data.

1. Clarify the Problem

Ask questions to understand the scope: which regions, drug types, and user segments are most affected? What are the current pain points and existing solutions?

2. Define the User and Value Proposition

Identify primary users (e.g., patients, pharmacists, regulators) and articulate how your product would solve their specific problem better than current alternatives.

3. Brainstorm Solutions

Generate a few product ideas that leverage Google's capabilities (e.g., AI, search, cloud, Android) and evaluate them based on impact, feasibility, and alignment with Google's mission.

4. Select and Detail the Product

Choose the most promising idea and describe its key features, how it works, and the technology stack. Explain how it integrates with existing systems.

5. Define Success Metrics and Risks

Outline metrics to measure success (e.g., reduction in counterfeit incidents, user adoption) and discuss potential risks (e.g., privacy, false positives) and mitigation strategies.

Key Points to Mention

  • Leverage Google's AI/ML for drug authentication (e.g., image recognition of packaging, blockchain for supply chain).
  • Consider a mobile app for patients to scan and verify drugs, integrated with Google Lens or Search.
  • Partner with regulators, pharmacies, and manufacturers to ensure data accuracy and adoption.
  • Address privacy and security concerns, especially with health data.
  • Propose a phased rollout, starting with a pilot in high-risk regions.
  • Measure impact via reduction in counterfeit cases and improved patient safety.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.