Every product leader is under pressure to "do AI," but few can separate what agentic AI reliably delivers from what still breaks in production. Drawing on the front lines of building Productboard Spark, Hubert Palan offers an honest field guide to the architecture underneath a working agentic PM system and what it demands of your organization. He'll walk through where AI genuinely improves product decisions, where it manufactures risk at speed, and why the hardest part is never the model but the persistent context, coordination, governance, and institutional memory around it. The through-line: adopting agentic AI is a strategic build-vs-buy decision, not a prompting exercise and understanding what the full system actually requires is how you tell a weekend experiment from a capability you can bet the roadmap on. You'll learn: - How to tell real decision-quality gains from superficial AI productivity - The components a dependable agentic PM system needs — 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 - What must be true in your organization before you safely increase product velocity