Separating signal from noise and focusing on what actually works.
I advise on AI integration, enterprise architecture, and transformation, with a focus on systems that can be deployed, maintained, and trusted.
Moving beyond pilots to production. Defining where AI creates value versus risk.
Platform strategy, modernization, and technical due diligence that lasts.
When technology initiatives require organizational change to succeed.
Recent essays on enterprise AI strategy, governance, architecture, and the operational realities of getting systems into production.
AI has collapsed the cost of producing content while the cost of verifying it has not moved. The next enterprise data moat is adjudicated data: authority, provenance, correction history, and outcome evidence. A 90 day trust audit checklist is provided.
ReadFoundation models are commoditized; the model is no longer the hard part. Enterprise AI stalls on integration — wiring models into systems of record efficiently, without a runaway token bill. Most pilot failures trace back to architecture, not model capability.
ReadGetting enterprise AI into production is the start of the real product work, not the finish. Once it's live, people ask it to do things nobody planned for, expectations outrun what the system can do reliably, and quality drops on the complex cases. Someone has to own the whole loop.
Read on LinkedInI work with executive teams on AI strategy, enterprise architecture, and transformation. Whether you're scoping a new initiative or stuck on one in flight, a short conversation is often the fastest way to figure out the right next step.