Interview Questions

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Asked at Google DeepMind • 5 months ago
How do you collect insights and apply them to products?
Product Manager
Product Design
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Product Manager
Product Design
Asked at Google DeepMind, Uber • a month ago
Tell me about your process for working with design teams.
Product Manager
Behavioral
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Product Manager
Behavioral
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Asked at Google DeepMind • 5 months ago
How would you launch a product for the proactivity space in Gemini?
Product Manager
Artificial Intelligence
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Product Manager
Artificial Intelligence
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Asked at xAI • a month ago
Implement an iterator class that supports next, hasNext, getState, and setState, then extend it to treat a list of iterators as one continuous iterator with a global index.
Software Engineer
Coding
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Software Engineer
Coding
Asked at LangChain • 5 months ago
Build a customer service agent using LangGraph.
Solutions Architect
Customer Interaction
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Solutions Architect
Customer Interaction

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Asked at LangChain • 5 months ago
Demo LangSmith product capabilities.
Solutions Architect
Customer Interaction
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Solutions Architect
Customer Interaction
Asked at LangChain • 5 months ago
What's the difference between LangGraph and LangSmith?
Software Engineer
Technical
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Software Engineer
Technical
Asked at LangChain • a month ago
Design an alarm system for streaming metrics.
Software Engineer
System Design
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Software Engineer
System Design
Asked at LangChain • a month ago
Implement a SQL parser that converts raw SQL strings into programming objects or ORM primitives.
Software Engineer
Coding
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Software Engineer
Coding
Asked at Perplexity AI • 5 months ago
What product do you think has good UX design and why?
Product Manager
Product Design
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Product Manager
Product Design
Asked at Perplexity AI • 5 months ago
How have you worked on quick iterations with UX designers in the past?
Product Manager
Behavioral
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Product Manager
Behavioral
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Asked at Perplexity AI • a month ago
How have you worked with designers to A/B test different iterations?
Product Manager
Behavioral
+1 more
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Product Manager
Behavioral
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Asked at Perplexity AI • 5 months ago
How would you handle a disagreement with an engineer over a product decision, balancing data insights with their technical perspective while preserving collaboration?
Product Manager
Behavioral
1 answer
"Clarification - I will first clarify what is the data insights we are talking about? Is it a feature in the platform or are we talking about data insights that we use in our work? First listen and not judge - I will first try to understand what the engineer is talking about, what is the disagreement that he is raising. Context - Then I will try to ask the engineer if he has the overall context about the feature/solution/functionality he is talking about. If he has all the cont"
Rohith K. - "Clarification - I will first clarify what is the data insights we are talking about? Is it a feature in the platform or are we talking about data insights that we use in our work? First listen and not judge - I will first try to understand what the engineer is talking about, what is the disagreement that he is raising. Context - Then I will try to ask the engineer if he has the overall context about the feature/solution/functionality he is talking about. If he has all the cont"See full answer
Product Manager
Behavioral
Asked at Perplexity AI • 5 months ago
As a PM, how do you work with users?
Product Manager
Behavioral
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Product Manager
Behavioral
Asked at Perplexity AI • 5 months ago
How would you define success metrics for an AI-oriented feature or product?
Product Manager
Analytical
+1 more
9 answers
+6
"As per my understanding, Success of the AI product/feature has to be measured in 2 aspects: success of the problem it solves success of the model used Success of the problem- start with the overall business goal of the problem(acquisition, retention etc) & the high level metric(essentially north star) then comes the product/feature level goals & metrics(conversion, engagement, clicks etc) Success of the model used- general: precision, recall, latency ethical: bias, safety busine"
Debajyoti B. - "As per my understanding, Success of the AI product/feature has to be measured in 2 aspects: success of the problem it solves success of the model used Success of the problem- start with the overall business goal of the problem(acquisition, retention etc) & the high level metric(essentially north star) then comes the product/feature level goals & metrics(conversion, engagement, clicks etc) Success of the model used- general: precision, recall, latency ethical: bias, safety busine"See full answer
Product Manager
Analytical
+1 more
Asked at Perplexity AI • a month ago
You are launching an autonomous vehicle service in Austin. Estimate market size, demand, and optimal fleet size, plan for peak and off-peak periods, and explore business strategy options such as op...
Product Manager
Estimation
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Product Manager
Estimation
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Asked at Perplexity AI • 5 months ago
How would you rollout a new feature for Perplexity?
Product Manager
Artificial Intelligence
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Product Manager
Artificial Intelligence
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Asked at Perplexity AI • a month ago
Propose a new feature for Perplexity.
Product Manager
Product Design
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Product Manager
Product Design
Asked at Perplexity AI, xAI • a month ago
Why do you want to join an AI-first company?
Product Manager
Artificial Intelligence
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Product Manager
Artificial Intelligence
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Asked at Perplexity AI • 5 months ago
What experience do you have with AI projects/automations?
Product Manager
Artificial Intelligence
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Product Manager
Artificial Intelligence