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Scaling isn’t about doing more — it’s about doing what works, better. This post breaks down how teams can move from early traction to sustainable growth without losing focus. Learn how to define what to scale, prioritize the right features, and use product analytics to turn validation into repeatable success.

This one was tough to write — I tried to untangle everything that’s changing in product management with AI. AI is reshaping product work at its core, shifting us from deterministic systems where we controlled every outcome to probabilistic ones where models learn and evolve. It cuts through the noise to show what actually changes when you build AI products: how your role shifts from defining logic to designing learning loops, why data literacy and AI evals become non-negotiable, and how to translate real business problems into AI solutions that work.

Most teams skip discovery and jump straight to building. That's a mistake. Without understanding the real problem, you're just guessing. You talk to the wrong users, build things nobody uses, and waste months fixing what could've been avoided. In this post, I break down why skipping discovery is the fastest way to waste time — and what good discovery actually looks like.

Learn how to validate your product idea before building. A step-by-step guide with real startup lessons to help teams build with clarity and confidence.

Most product teams don’t fail because of a lack of talent or effort, but because they chase speed without clarity. I’ve fallen into this trap myself. In this article, I lay out the foundations of what building products really means—and share a practical way of thinking about it: Validate → Build → Scale.