Own the enterprise brain your AI runs on.

Here's what that means, concretely. Picture three layers: the infrastructure you already run, meaning Snowflake, Databricks, whatever's already in place with no need to rip it out; the enterprise brain sitting on top of it, translating your definitions, judgment calls, and institutional memory into something a model can use; and the agents and people acting on what that brain tells them. Most AI budgets right now chase the third layer, meaning better agents and flashier copilots, while quietly renting the second, the brain itself, from whoever's platform they bought.

One belief. Two applications, twenty years apart.

Everything I've built comes back to one belief: build around the customer, not the technology. Do right by them, and the rest follows. That's not a slogan. It's an operating principle I've tested twice now.

The first time was DataOS. Enterprise data was powerful and mostly unusable, locked in formats and pipelines only engineers could navigate. Customer-centricity, applied to that problem, meant data-as-product: give data a named owner, quality standards, and semantics, so a business user never has to understand the plumbing underneath. That instinct, building for the person actually trying to get work done rather than what's technically convenient, is what earned Fortune 500 adoption and a Gartner Magic Quadrant nod, not the technology itself.

The second time is now, one layer up. Every AI initiative depends on context: a model's understanding of your business, your definitions, your judgment calls. Take customer-centricity seriously here and it leads somewhere specific: a vendor whose business model depends on you staying dependent isn't actually built around you. It's built around itself, wearing your problem as a wrapper. Most enterprises are responding by layering more point-solution AI tools over the same fragmented data. That's vendor sprawl, not a fix. If you actually center the customer's long-term interest, not just what's convenient to sell them today, the context has to be something they own and keep compounding, not something they rent forever from someone whose incentive runs the other way.

Here's what renting actually looks like: your business rules live inside someone else's schema. Your AI's judgment resets every time you switch models, switch platforms, or the vendor changes its roadmap. You keep paying for something that should get smarter and more valuable the longer you use it. Instead, it stays worth exactly your last invoice.

Owning looks different. The context compounds: every decision your AI makes teaches your system something it keeps, not something the vendor keeps. You can swap the model underneath without losing what you built. It sits on your side of the ledger, not a subscription line.

Same belief, both times, just a different layer of the plumbing.