Evidence
Two kinds of evidence. One shows I can see past an industry’s assumptions. The other shows I can build the AI systems that act on it.
I helped scale Gazelle past $100M by building a business around an assumption the industry had missed. Outerwall acquired it in 2015. The lesson I carry into every engagement: the hardest thing to see in a business is the constraint everyone designed around.
Add the Gazelle insight in one line, the source for the $100M figure, and the exact title held at Gazelle.
Before Gazelle, I built systems where failure was not an option: defense lab work at Teradyne on the B-2 bomber, then enterprise systems at State Street, Cambridge Information Systems and Signiant. After Gazelle, healthcare operations at LogixHealth.
Confirm whether to mention the B-2 work publicly.
This is company-building and systems experience. It is not presented as AI implementation.
Each story has the same four parts, so you can compare them.
The situation, what I did, what I built and whether it is in production, and what changed. Only documented results appear under what changed.
Launch gate: three stories must be finished and verified before launch. Each needs the problem in one line, the direct contribution, what went into production, and at least one verifiable result. Full stories follow in Phase 2.
Healthcare operations: add a fourth story only with a verifiable healthcare AI engagement. Otherwise launch with these three. Logistics and jewelry clients stay described, not named, until they give written permission.
One essay a month on how AI changes the way companies are built.