Product Management in the AI Era

Every roadmap now has someone asking "where's the AI?" — and answering that well is a different skill from being swept up in it. This course is for the person who has to ship something real: a PM, founder, designer, or analyst who needs to turn a vague "let's add AI" into a product that actually solves a problem and keeps working after launch. You'll start where good products always start — finding the real user problem, before any solution — and learn to tell an AI-shaped problem from one where AI is just an expensive way to do something simpler. From there you'll define requirements for features that are right only most of the time: what "good enough" means when the output is probabilistic, how to evaluate feasibility, cost, and latency before you commit, and how to weigh the risks, from bias and privacy to prompt injection and the EU AI Act. You'll prioritize against outcomes instead of feature count, then measure what you ship with both ordinary product metrics and the AI-specific ones teams routinely get wrong — and keep a live model healthy as the world drifts underneath it. The through-line is a habit worth more than any tool: telling the durable craft of product management apart from the perishable specifics of today's AI. Model names, prices, and benchmarks will be obsolete soon; the way you discover, decide, and measure won't. No coding and no math required — just honest, practical judgment, grounded in the real frameworks practitioners use, so you can direct AI products with clear eyes instead of hype.