Before speed,the right direction.
AI Lead Product Manager, ten years building products, the last four focused on artificial intelligence. I build the product vision, even when everything is still blurry, then test it quickly against reality with prototypes I build myself, and I only keep the use cases that truly serve your business goals. From startups to large groups, that's what takes AI from demo to production.
You don’t need AI. Yet.
They trusted me.
Three moves, one standard. Aim true.
Build the vision
When things are still blurry, I start from what teams and users are really trying to accomplish. It's rarely what the tool can do. That's where a product vision everyone can understand and defend comes from.
Prototype to decide
I build my own prototypes, in Figma or with Claude Code. A use case gets tested with users in a few days, before a whole team is committed. The ones that hold up go on the roadmap, the others stop early and cost little.
Align product and business
An AI feature only has value if it serves a measurable goal and people actually use it. At ArcelorMittal, our telemetry tool detected anomalies up to 21 days before an incident, on breakdowns that cost millions. That link between product and outcome is what I look for every time.
A PM who gets hands-on with the product
Ten years in product development, from startups to large groups, in Montreal, Dublin and Munich, then France. I've worked with ArcelorMittal, Auchan, BSH, Elle and Lenovo, and on SquadBox, an AI agent management product born at HalfSerious.
Technology is rarely the bottleneck. The McKinsey State of AI shows adoption moving much faster than real impact on results. What's missing is redesigning the work around the tool. It's the subject of my article on efficiency and relevance, and the common thread of my product practice.
Hiring an AI Lead Product Manager?
Let's talk about your product, your team and what AI can bring to it. Write to me, I'll answer.