U2xAI
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Model Fluency & the AI PM Role

What changes when the product is probabilistic Interview Questions

21 questions. All 21 carry a written answer.

  1. #1Name three product decisions that change when a feature's output is probabilistic rather than deterministic.ConceptFoundational
  2. #2A traditional feature either works or has a bug. Explain why that framing breaks for an LLM feature.ConceptFoundational
  3. #3What does 'correct' mean for a summarization feature? Give a definition your engineering team could test against.CaseIntermediate
  4. #4QA files a bug that reads: the model gave a wrong answer once. How do you triage it?CaseIntermediate
  5. #5Explain the difference between a defect and an acceptable error rate to a non-technical executive.InterviewFoundational
  6. #6Why can you not write an acceptance criterion like 'the output must be accurate' for a generative feature?ConceptFoundational
  7. #7Describe how you would set a quality bar for a feature whose output is free text.CaseIntermediate
  8. #8What is the product cost of a false positive versus a false negative in a resume-screening feature?CaseIntermediate
  9. #9Give an example of a product where a 95 percent success rate is excellent and one where it is unshippable.ConceptFoundational
  10. #10How does non-determinism change your regression testing strategy?ConceptAdvanced
  11. #11Two users send the same prompt and get different answers. Is that a bug? Defend your answer.InterviewIntermediate
  12. #12What changes about your rollback plan when the thing you might roll back is a model, not code?CaseAdvanced
  13. #13Explain why 'it worked in the demo' is a systematically misleading signal for AI features.ConceptFoundational
  14. #14Describe the relationship between sampling temperature and product predictability.ConceptIntermediate
  15. #15How do you communicate a confidence level to a user without teaching them statistics?CaseIntermediate
  16. #16What is the difference between model quality and product quality? Give an example where they diverge.ConceptIntermediate
  17. #17Your model improves on benchmark accuracy but users complain more. List four possible explanations.CaseAdvanced
  18. #18Why does a probabilistic product need a feedback mechanism that a deterministic one does not?ConceptIntermediate
  19. #19How does probabilistic output change the shape of your support and escalation process?CaseIntermediate
  20. #20Describe a product decision you would make differently if the model's error rate doubled overnight.CaseAdvanced
  21. #21Walk me through how you would convince a skeptical enterprise buyer that your AI feature is reliable enough to trust.InterviewAdvanced