Three barriers kept the specified economy from launching: the technical, the funding, and the organizational. All three fell to the same event, the arrival of LLM-driven agentic software. That is why now.
The technical barrier. The project models the economy as a distributed network protocol, and executing it as a protocol, not merely modeling it, was frontier research: formal verification at a scale that would have demanded dozens of expensive specialists. LLMs drove that cost toward zero, and the formal design of the protocol became tractable.
The funding barrier. The project needs capital to operate, yet profit-seeking cannot be its defining driver, since the entire purpose is to create forms of surplus beyond profit. LLMs made the bridge designable: a sophisticated interface that reconciles capital flows with the network's own economic logic, so the project can be funded without its semantics being subverted.
The organizational barrier. A decentralized, non-hierarchical network is informationally expensive; centralization and hierarchy exist precisely as complexity-optimization functions, and our own organizational experiments taught us this the hard way. LLMs absorb that complexity and present a simple interface: participants express preferences and goals in familiar language, and an economic agent translates intent into network action.
Three constraints, one resolution. This is the time of the protocol, and of the network — and the reason a decade of specification raises now rather than earlier is not that the work waited, but that the barriers stood until they did not.
Distinct from its neighbors: a decade of specification names the record; what AI is really exposing names the diagnosis; this item names why the launch is now.
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