The Future Isn't One Cloud

Predictable AI infrastructure economics depend on not being trapped by them.

Lock-in rarely arrives as a single decision. Nobody sits down and signs a contract that says "we will be dependent on this vendor for the next decade, on their pricing terms, with no realistic way out." It arrives gradually, through dozens of individually reasonable choices: a proprietary API here, a convenient managed service there, a training pipeline built around one platform's specific tooling because it shipped fastest. Each choice saves time in the moment. Together, they add up to a company that can't leave even when leaving would be the right call.

AI infrastructure is accelerating that pattern, not slowing it down. The stack has more layers than traditional cloud infrastructure did — chips, orchestration, model hosting, fine-tuning tools, inference serving — and every layer is a fresh opportunity to get locked into a single vendor's version of how things should work. The more of that stack one company controls, the more your economics depend entirely on their decisions, not yours.

Scale is not the same as leverage

There's a natural assumption that going all-in with one large provider buys you negotiating leverage — better pricing, better support, better priority access to capacity. Sometimes that's true. But leverage only holds as long as switching is realistically possible. The moment your training data, your fine-tuned models, your deployment tooling, and your monitoring are all native to one platform, the leverage quietly flips. You're not the customer with options anymore. You're the customer who can't leave.

That's the uncomfortable part of consolidation: it feels like simplicity right up until it becomes dependency. And dependency is expensive in a way that doesn't show up on an invoice — it shows up the next time that vendor changes pricing, deprioritizes a feature you rely on, or has a capacity shortage during exactly the week you need it most.

What we mean by "not one cloud"

We're not arguing that every company needs to run active workloads across five providers simultaneously — that's its own kind of complexity tax. We're arguing for something narrower and, we think, more durable: infrastructure that's designed so you could move if you needed to, even if you never do. Control over your own models, your own data, and your own deployment path, instead of control that only exists on paper because switching costs make it theoretical.

That's the economic case for portability, and it's the one we find most convincing: predictable costs come from having somewhere else to go, not from hoping your current vendor stays reasonable. Infrastructure built around that principle costs more to build correctly. It's also the only kind that keeps your organization's leverage where it belongs, with you.