AI-First MVP Validation with

You have an AI product idea (or three). We run it through the exact validation workflow we use at Build Up Labs to decide which startups we build. We'll pressure-test the problem, identify the riskiest assumption, and design the cheapest experiment to invalidate it before you write a line of code. Particular focus on AI-specific traps: fake moats, wrapper economics, "GPT for X" positioning, and demo-to-production gaps. You leave with a kill-or-continue decision and a concrete next step for the week.

Over the past decade, I've been in the trenches with founders, turning napkin sketches into live products, first users into scaling businesses, and uncertainty into validation. As CTO and Entrepreneur in Residence at Build Up Labs in Lisbon, I spend my days doing what I love most: building products and helping entrepreneurs launch MVPs that actually ship, test assumptions with real users, and pivot or scale based on data, not hope.

I've seen firsthand what separates ideas that fade from products that fly, and it usually comes down to how quickly you can prototype, learn, and iterate. Whether through code, no-code tools, or AI, my mission is to help you find the fastest path from concept to customer feedback.

I mentor founders navigating their first launch, guide teams through the messy middle of product-market fit, and teach the frameworks that turn vision into traction. If you're building something new and want practical insights on prototyping and MVPs, I'm here to share what works and what doesn't.