About
Thirty years in IT has a way of teaching you that the most consequential work happens at the edge of what's ready — not what's proven. I've spent my career arriving early: to enterprise integration before it had a playbook, to cloud architecture before it had guardrails, and now to AI before most organizations know what questions to ask.
Today, I serve as an AI Architect and Trainer at a major financial institution, where I lead adoption strategy, design training programs, and help teams move from curiosity to capability. That means writing the frameworks that didn't exist yet, running proofs of concept that test what vendors won't tell you, and translating complex AI behavior into decisions real teams can act on. My technical foundation spans Microsoft 365, Azure, and the Power Platform — but the work I find most meaningful sits at the intersection of architecture and organizational change.
What three decades have given me isn't just depth — it's pattern recognition. I've watched organizations fail at transformation not because the technology wasn't ready, but because the people strategy wasn't. That's shaped how I approach every engagement: with equal weight on the technical architecture and the human one. I don't believe in adoption for its own sake. I believe in building organizations that know how to learn — because in a field moving this fast, that capacity is the only durable advantage.