The thesis
The frontier is not the whole story
Most attention at the frontier goes to the models, and to the labs racing to make them more capable. That race matters, but capability on its own is unstable ground. When value pools at a single layer, the rest of the stack stays thin, dependent, and easy to displace. A frontier with no ecosystem around it does not hold for long.
Value lives across the stack
A working AI economy is not one layer winning. It is many layers fitting together: foundation models, the infrastructure that serves them, the data that grounds them, the applications that turn them into outcomes, and the channels that carry them to real users. Each layer needs the others, and none captures durable value alone. The interesting question is not which layer wins. It is how the layers get wired together, and who does the wiring.
Capability earns the headlines. Ecosystems decide who keeps the value.
Ecosystems are built, not assumed
That wiring is deliberate work, and it happens through partnerships. A model provider and a distributor. An application and a data owner. An incumbent and a startup deciding what to build and what to borrow. These choices decide where value settles and who holds a durable position. They are made under real uncertainty, and they are rarely undone cleanly.
What this covers
Frontier Ecosystem follows that building. It tracks how ecosystems are forming across the AI stack, and argues for how they should form. The teardowns take one real partnership at a time, a distribution deal, an integration, an acquisition, and work through what each side gave, what each side got, and who came out better positioned. The aim is a clear, practical, and opinionated read on how the AI ecosystem is actually being assembled.