About.

I build platform products — the kind that sit underneath other teams' work and have to be right in order for anything downstream to be trusted. Data infrastructure, fit-for-purpose data products, governance designed in rather than bolted on. The job is getting the foundation solid enough that the applications on top can move fast, without knocking the building down in the process.

At Oracle

I did that twice, in different industries, at scale. First for a $200M+ AdTech and MarTech business — multi-source marketing signals that had to be harmonized, resolved, and made trustworthy enough to build decisioning products on. Then for a $200M+ health data platform following Oracle's acquisition of Cerner. Health data is a harder version of the same problem: clinical records, lab results, claims, pharmacy data, each arriving from a different system, in a different format, with a different definition of the same field. Before any of it is worth building on, it has to be made coherent.

The architecture challenge is familiar. The reason it matters is not — a bad marketing audience wastes money; unreliable clinical data affects care decisions. Same lens, different domain, meaningfully higher stakes.

Building Organizations

Leading PM organizations of upwards of forty people taught me that the technical work is a small fraction of the real work. The real work is alignment — and I mean actual alignment, not consensus, which is slower and usually wrong. Alignment to the customers' real, hard problems, and alignment with Dev, Sales, and Compliance on what we're doing and why. It's helping people grow into harder problems, act with more autonomy, and step into leadership they didn't know they had. And increasingly, it's change management: how you bring an organization through a meaningful shift without losing the people who are most skeptical and most valuable.

The Gap That Matters

Enterprise software is littered with technically sound products that didn't take because the organization couldn't absorb them. Whether a SaaS platform actually succeeds is at least as much a function of change management as the technology — sometimes more.

That dynamic is only getting sharper. The gap between what AI can do and what most organizations can actually put to work isn't capability. It's trust, literacy, and the willingness to redesign workflows that used to work well enough. That's a product and organizational problem more than a technical one, and it's where platform thinking and change management experience start to converge in ways I find worth paying attention to.