Twenty Years of Getting the Model Right.
I've been building the kinds of models that defense organizations stake real decisions on for over twenty years. Missile defense, multi-domain operations, architecture-level trade studies. Every one built from physics, validated against data, tuned to what the decision actually required.
At MITRE, I led analysis teams working problems that cut across the entire Department of Defense. Before that, I ran my own defense consulting firm for seven years. Before any of that, I was a math teacher. That lesson from the classroom stuck: it doesn't matter how right your model is if the person across the table can't act on it.
The fidelity of the model determines the quality of the decision. I spent twenty years learning that in defense. Now I'm applying it to the problems that matter most to me.
Most modelers I know resist AI. I've leaned into it — not as a replacement for judgment, but as a way to do more analysis than one person should be able to. The methodology keeps it honest. The agents make it fast. I haven't met many people doing both.
Long-term, I want to point these methods at the biggest problems I can find — energy systems, environmental contamination, human health, education. Frame the problem, build the right model, show what's possible. Read the full vision →