About
I ship the operating change, not just the deck.
Enterprise strategy, AI systems, cost discipline, and the operating change that has to happen for any of it to matter.
I've spent 25 years inside big companies — first on enterprise transformation and technology cost, then cloud and FinOps, and for the last decade, AI. One thing kept showing up in every era: the technology never sets the value. The operating model around it does.
AI made that lesson louder. Companies were buying models and counting tokens. The people who signed the checks were asking about outcomes. Those are two different conversations, and the gap between them isn't a talking problem — it's a wiring problem. That's the gap this site is about.
CloudMetrics is where I do the enterprise work. AI Value Engineering is what I call the method. This site is the writing, the playbooks, and the readiness check — so the method travels beyond the room I'm in.
AI value is a work problem, not a model problem.
Three sides of the work
Most people bring one of these. The interesting problems need all three.
Builder
I build the systems, not just talk about them. Agents, governance, orchestration, and the workers underneath — end to end.
Investor's eye
I treat AI like any other investment. What does it cost, what does it return, and can you defend it in front of a board that isn't in love with the technology.
Governance
The policy, the accountability, and the checks that decide whether AI is allowed to touch a real system of record.
Background
- Founder, CloudMetrics
- EY, Accenture — executive roles
- 25+ years inside enterprise transformation
- Technology cost, cloud, AI, data, operating models
- Startup Predicament; new books on vertical AI and AI cost in progress
- AI Value Engineering, Cost of Work, governed AI systems
JULY 2026 / thesis / operating model over model