Your AI problem is not a tooling problem.

Work with me

Most companies buy the models, hire the talent, and still see nothing change. The bottleneck is the operating model: how decisions get made, how teams are structured, and how work actually moves. That is the layer I rebuild. I am a fractional AI leader who has run transformation inside Amazon and Intel and built it from zero in the field.

Schedule a Consultation

Transformation in Practice

Five examples from inside Amazon and Intel. The same lesson in five different shapes: the constraint was never the tooling; it was the operating model.

View Case Studies

A Trusted AI Operator

I have led AI transformation in the places where adoption, scale, and operating change are hardest. See how that experience shapes the way I help leaders move from AI ambition to real execution.

Learn More

THE WEDGE

Why AI initiatives stall

The pattern is consistent. A company stands up a pilot, sees a promising demo, and then watches the momentum disappear into the org chart. The tools work. The people are capable. But the operating model underneath was built for a pre-AI way of working, and it quietly rejects the new one.

Decision rights are unclear. Teams are structured around old workflows. Governance is either absent or so heavy it strangles iteration. Nobody owns the outcome. The result is a portfolio of stranded pilots and a leadership team that has lost confidence.

AI does not transform a business by being adopted. It transforms a business when the operating model is redesigned to run on it. That is a leadership problem before it is a technology problem, and it is the problem I am built to solve.

WHAT I DO

Fractional AI leadership

Embedded, operator-level ownership of your AI transformation. I take a CTO-level mandate, set the strategy, and stay accountable for it landing. Not a slide deck and a handoff. Real execution alongside your team.

AI incubator and operating model design

I stand up the structure that lets AI work actually ship: the team topology, the decision rights, the governance that protects speed instead of killing it, and the pipeline that moves an idea from hypothesis to deployed system. This is the engine, not a one-off project.

Spec-driven AI development

A disciplined pipeline that takes a hypothesis from a non-technical stakeholder through research, specification, and autonomous implementation to a deployable output. It makes AI delivery repeatable instead of heroic.

See how this plays out in practice.

Read the Case Studies

WHY ME

An operator,
not an observer

I have led AI transformation at the scale where it is hardest. At Amazon I worked across Fire TV and Alexa, and scaled an internal AI engineering practice to 2,000 engineers across a division. At Intel I built perceptual measurement science as an engineering practice and led software teams as a manager and human factors engineer. Today I run an AI innovation incubator with a CTO-level mandate, building the exact operating models I advise on.

I do not consult on AI in theory. I am doing the work right now, and I bring that directly to you.

SELECTED WORK

Outcomes that speak

Nine months, zero lines of code, four features shipped

AI moves the unit of value from code produced to problems framed. An operating model that still measures the old unit never sees the gain.

Decades of benchmark data harnessed for forecasting

AI’s biggest gain isn’t faster answers. It is making a new class of question askable, and the advantage goes to whoever sees it first.

A weekend of test-writing, done in ninety minutes

When systems become probabilistic, the engineer’s job shifts from production to judgment. The model has to make room for it.

View all Case Studies

LET'S TALK ABOUT YOUR OPERATING MODEL

Schedule a Free Consultation

If your AI initiatives are stalling, the problem is probably not the one you are funding. A short conversation will tell us whether it is. No pitch, no obligation.