Product design question
How would you make Google faster?
- Product design
- Medium
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What this question tests
Tests product thinking about performance as a feature: identifying where speed actually matters most to users and proposing measurable, prioritized improvements.
How to approach it
- Clarify what 'faster' means: query response time, page load time, or time to find the right answer, since these require different interventions.
- Segment by query type: simple factual queries versus complex or ambiguous ones likely have very different current latency and different improvement levers.
- Propose technical-adjacent levers: caching common queries, optimizing the ranking pipeline for the most common query patterns, and reducing page weight (ads, scripts) on the results page.
- Propose a product-level lever: showing an instant, high-confidence answer directly (a featured snippet or knowledge panel) for queries where the user does not need to click through at all.
- Prioritize by frequency and impact: optimizing for the most common query patterns and page-weight reduction likely gives the biggest aggregate speed win.
- Define success: median and 95th-percentile time to result, plus time to the user's actual answer (including featured snippets), since latency at the tail matters as much as the average.
What a strong answer includes
- Distinguishes true latency (server response time) from perceived speed (getting an answer without a click), since both count as 'faster' but need different fixes.
- Prioritizes the most common query patterns and page-weight reduction for aggregate impact, rather than optimizing rare edge cases first.
- Proposes featured snippets and instant answers as a genuine speed lever, since the fastest search result is one the user never has to click through for.
- Uses both median and 95th-percentile latency as metrics, recognizing that tail latency affects perceived reliability even if the average looks fine.
Common mistakes
- Treating 'faster' as only server response time and ignoring perceived speed improvements like instant answers.
- Proposing only average latency as a metric, missing that slow tail cases disproportionately hurt user trust.
Likely follow-up questions
- How would you balance speed improvements against showing more complete or higher-quality results?
- How would you measure the user-perceived improvement, not just server-side latency?
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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 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop