questions / ai
ai questions
01 How would you design an A/B test for an AI feature whose outputs are non-deterministic?The AI PM experiment design question. How to control model, evaluation, and population variance when your feature's output changes every run. hard → 02 Design the guardrails for an agent that can act on a user's behalf across their calendar, inbox, and task management tools.The 4-dimension rubric for agent guardrails interview questions: scope, confirmation, limits, and kill switch. What clears the bar at AI-first companies. hard → 03 Design an evaluation framework for a customer-support AI agent before it talks to real customers.How to answer the AI PM eval-design question. Offline vs online evals, real thresholds, MiHR/MaHR, shadow mode, and the flywheel that makes evals a product moat hard → 04 How would you make an LLM's output more creative?The AI PM creativity question. Three control layers, the sampling-and-ranking pattern, eval signals, and what clears the bar at Google and Apple. standard → 05 How would you define goals and measure success for a new AI product?The AI metrics interview question that separates candidates who've shipped from those who've read about it. A step-by-step framework with a worked example. hard → 06 How would you optimize an LLM for retrieval on a given dataset?The Meta AI PM retrieval question decoded. Decision hierarchy, RAG vs fine-tuning, hybrid search, eval metrics, and the 2026 reframe interviewers are testing for. hard → 07 How would you price an AI product without killing margin?The AI PM pricing question. Token economics, the autonomy-attribution matrix, and margin levers, structured as a spoken interview answer. hard → 08 When would you use prompting, RAG, or fine-tuning for an AI feature?The AI PM decision question. A decision framework, 2026 production realities, follow-up prep, and what clears the bar at OpenAI and Anthropic. standard → 09 What safeguards would you build into an agentic AI product, and how would you decide which ones to prioritize?How to answer the agentic AI safeguards question in PM interviews. The irreversibility framework, key vocabulary, and what separates a hire from a pass. hard → 10 What hallucination rate would cause you to refuse to launch?How to answer the AI PM launch-gate question with a specific threshold, measurement method, and fallback path that clears the bar. hard → 11 How would you validate an AI model before shipping it?What a strong PM answer looks like in 2026: offline gates, online monitoring, grader design, agentic evals, and the viability/lovability layer beyond hard → 12 When does a feature warrant an agent rather than a simpler LLM call?The three-gate framework for deciding when to use an AI agent, with strong/weak answer examples and the 2026 feasibility reframe. hard →