Architecture trained me to listen before I design. That habit doesn't change.
I spent fifteen years in architecture, the last five as a partner, closing enterprise deals in hospitality and commercial development. The last couple of months I've been building AI systems from scratch: a 13-container autonomous trading platform, an AI-powered business intelligence suite, tools running on self-hosted infrastructure. The craft is the point.
AI tools, live and in use.
Not prototypes. Working systems, built with the same patience and intention you'd bring to anything meant to last.
Architecture work.
Fifteen years in the field, five as a partner at Clayton Korte. Clients in hospitality and commercial development. Austin, TX.
Full portfolio at claytonkorte.com
Fifteen years learning what clients need before they know they need it. Good craft works that way.
Architecture teaches you that. So does running a trading system through four production bugs at 2am. The work here covers both worlds.
Fifteen years in architecture, five of them as a partner at Clayton Korte. Clients in hospitality and commercial development, mostly. Long deals, multiple stakeholders, the kind of work where trust is the actual product.
The last couple of months have been about building the translation layer between what AI can actually do and what enterprise teams believe about it. That gap is the opportunity. Closing it is a relationship problem, and that is precisely what fifteen years in architecture trains you for.
Every system here was built to last and built to work. The name is a reminder of that.
The right problem.
Most AI companies have the technology figured out. The harder problem is the gap between what the system can actually do and what an enterprise buyer believes about it. Closing that gap is a relationship problem. It requires someone who can sit across from a skeptical VP and make the abstract concrete, and then go back to the team and translate what the buyer actually needs into something buildable.
That is what fifteen years in architecture trained me to do. And it is what I have been doing on my own: building production systems from scratch, running them, debugging them at 2am, and learning what it actually takes to ship AI that works in the real world.
I am looking for a GTM Strategy, AI Strategy, or Founding PM role at a sub-100-person AI company where the gap between capability and adoption is the opportunity. If you are building something real and need someone who can own both sides of that equation, I would like to talk.








