A question, an idea to challenge, a proposal: it all lands in the same place.
Twelve Consulting, on assignment at Rothschild & Co
This site is a notebook, not a shop window. I publish what I understand about work in the age of language models: what holds up in production, what breaks, and what it changes for teams. I write to think clearly. If it helps you too, all the better.
Almost everyone can point to an AI tool that saves them time. Far fewer can say whether they've become more capable because of it, or just more dependent on it. A case for AI that builds skill instead of quietly eroding it.
Learn to evaluate products that embed AI, from your first failing run to a complete evaluation package you could hand to a decision owner.
Testing an AI product has little to do with testing classic software: several answers can be acceptable, and exact comparison no longer holds. This course does not benchmark models; it teaches you to define what "trustworthy" means for a given product, then to prove it. Seven modules, eight solved exercises and a capstone, built for non-engineers who have to sign off an AI system before it ships.
A startup I co-founded: turning export compliance auditing, manual and opaque, into an AI-driven document analysis engine.
International trade remains one of the last strongholds of administrative opacity. We started with a management interface, then flow analysis showed the bottleneck was elsewhere: in the semantic comparison done by hand, file after file. The product pivoted to an AI orchestration engine. I led it from the first line of specification through to product-market fit, with 50 paying customers and a 200k€ R&D budget.
Three formats, one rule: never write anything I do not actually believe.
What I am working on today, updated when it changes.
Use-case scoping, roadmap, answer-quality evaluation (LLM-as-a-judge), guardrails, and GDPR / AI Act compliance. The interesting part is never the model: it is everything you must build around it before anyone can trust it.
The goal is explicit: not just to lead agentic projects, but to build them myself, locally. A product owner who can read and write code makes sharper calls, and gets told fewer stories.
A public repository helping non-engineers test AI products properly. Because "it seems to work" is not a test protocol.
View the repositorySixteen kilometres and a hill everyone dreads. I am training, taking notes on what works, and it will probably end up in the Personal category.
From frontline sales to AI product leadership, by way of a startup built from nothing.
A well-argued disagreement beats a polite agreement. If a post makes you react, or you want to stress-test an idea, write to me.
