I help executive teams find out where they actually stand — what's working, what's provable, and what the right next move is from here.
Asked of each thing you've built or bought — separately, not as an average.
The answers rarely match across deployments — and that mismatch is the finding. Most companies are advanced in one place and at zero in four others, which no single maturity score can tell them.
AI is deployed in several places. Spend keeps rising. Nobody can say what it returned, and the board has started asking. You need to know whether the problem is the technology, the people, or where you pointed it — because the fix is different in each case.
You're being told to do something about AI. Every vendor has an answer. You'd rather skip the expensive mistakes the companies ahead of you already made — and know what to build first, and what not to buy yet.
I'm a practitioner, not a consultant. Eight years building AI and machine-learning systems — previously head of AI engineering at a major games publisher, currently CTO and cofounder of an agentic AI platform company in Austin.
That means I've paid the bills for a bad model-routing decision, set up the evaluation that told me it was bad, and had the argument about whether it was worth fixing. It also means I can tell when a vendor's claim is true, true-but-irrelevant, or quietly wrong — which is most of what this job turns out to be.
If you can't answer three of the six, it's worth forty minutes.
sid@sidadvisory.com