Skip to content
PMInterviewKit
In this module9 lessons
  1. What AI product rounds testFree
  2. How large language models work, for PMs
  3. Designing an AI feature
  4. Evals and quality
  5. Metrics for AI products
  6. Risk, safety and trust
  7. Cost and latency trade-offs
  8. Worked answers
  9. Common traps and how to recover

Metrics for AI products

Pick a metric set for any AI feature across outcome, interaction, cost, speed and safety, and spot the AI metrics that mislead.

6 min readFull kit

Once an AI feature has real users, the Proof gate shifts from evals to metrics. The usual rules from Choosing a north-star metric still apply: tie the metric to user value, pair it with guardrails, break it into parts. But AI products add new metrics, and several of them mislead in ways that trip up even experienced PMs.

This lesson gives you a five-layer metric set you can build for any AI feature in about two minutes, then the traps that separate a strong answer from a checklist.

Checking your access…

Practice this lesson

← PreviousEvals and qualityNext →Risk, safety and trust