Proof of work, not a résumé

I'm most interested in AI when it leaves the demo and has to work inside a real system — with imperfect data, specific users, real constraints, and actual decisions attached to the output. A demo can be wrong and still be impressive. A system someone uses to decide what to plant, when to sell grain, or which vehicles to replace does not get that luxury. Most of the work is not in the model. It is in defining what a good answer actually is, and then building something that will not produce a bad one.

Large organizations do not change because someone writes a strategy. They change when governance, procurement, policy, budget, field operations, and reporting all move in the same direction at once. Both programs below are about that: designing the system that makes a decision stick across thousands of assets and hundreds of people who did not attend the meeting. Employer-specific detail is kept intentionally high level.

Before I was designing enterprise systems and AI tools, I was designing places. Landscape architecture taught me to think in systems — people, materials, movement, ecology, constraints, time, and implementation. A planting plan is a system with a twenty-year time axis. A park is a system with a budget, a maintenance crew, and several thousand people who will use it in ways no one predicted. I have been designing around people, constraints, systems and place for a long time. The medium has changed. That part really hasn't.

Completed as part of MESA Design Group with multidisciplinary project teams. Roles noted per project.