I build AI products inside regulated financial services — where the hard problems are rarely the models, and almost always trust, governance, and what an organization will actually adopt. This site is where I keep what I've learned, in the open, for anyone it might help.
Over the past few years I've organized what I've learned shipping AI in production into a course — 24 units, free, no sign-up, no expectations. It exists to give back to the community that taught me. Start with Unit 01: What AI Engineering Is (and Isn't), or see the full syllabus.
I maintain two working tools for exactly this problem: AI Reg Atlas, a live, sourced tracker of AI regulation in US insurance and financial services, and the Compliance Cost Lens, which turns regulatory burden into arithmetic. Both are open datasets — read about them here.
Everything I build lives in the open. The current work — datasets, experiments, half-formed ideas — is on GitHub.
Another giving-back project: Product Careers aggregates product-management roles from across the industry into one curated board. If you're a PM looking, start there — or read how it works.