Every product leader is under pressure to "do AI," but most of its benefits to date have centered around product execution, leaving the rest of the product development lifecycle a green field for the next wave of innovation, and increasingly, a strategic imperative. Drawing from the front lines of building Productboard Spark, Hubert Palan makes the case that these other phases have stayed unsolved for a specific reason. Beyond the orderly structure of a repo, agents require a shared, interconnected substrate. Hubert explores the architecture that closes that gap. The through-line: adopting agentic AI for product management is a strategic build-vs-buy decision, not a prompting exercise, and understanding what the full system requires is how you tell a weekend experiment from a capability you can bet your roadmap on. You'll learn: - How to tell real decision-quality gains from superficial AI productivity - The components of a dependable agentic product system, and why each one is easy to underestimate - Why "build it ourselves" is harder than it looks, and how to frame build-vs-buy for AI - Why loop speed, not shipping speed, is the real competitive advantage