The next decade of AI will not be decided by which model is largest. It will be decided by which protocol lets capability live inside hardware. Today, AI capability lives where it was trained — inside large data centers, behind opaque APIs, in models whose weights cannot be inspected and whose runtime is divorced from any substrate that has to honor what they claim. The result is a structural mismatch. AI capability grows in the cloud. The trillion devices that already populate the physical world — phones, vehicles, embedded controllers, industrial sensors, smart appliances, edge gateways — are slowly drifting from "possible to upgrade" into "expensive to discard." This essay argues that the missing layer is not a new model. It is a meta-protocol — a coordination layer at which capability declarations remain accountable to the substrates that honor them, while still allowing capabilities to evolve, accumulate, and move across heterogeneous hardware.…