Presented by OpenTeams
A Field Guide to the Distributed AI Economy
How AI capability becomes owned infrastructure, and what becomes tradeable when it does.
Three ways in
One guide, three doors. Start where your question starts.
Field map
Start here
Part I — THE PROBLEM
Part II — THE EXECUTION LAYER
- 3 Frames: Context as a Versioned Artifactthe artifact that turns organizational context into something owned, versioned, and shareable
- 4 Cogs: Accountable AI Workersthe unit at which AI work becomes assignable, governable, and auditable
- 5 Ops: Jobs You Can Installthe unit of AI work that maps to business outcomes, and the properties that make it distributable
- 6 Guards, Gates, Tracks: Show Your Workthe cross-cutting plane that verifies AI work, decides what happens next, and preserves the evidence
Part III — THE GROUND IT STANDS ON
- 7 The Intelligence Hub: A Perimeter of One's Ownthe deployment where Frames, Cogs, Ops, and Tracks actually live, and the memory it accumulates
- 8 Assembled From the Commonswhat Hubs are actually built from, and the two open-source projects (Nebari and Nebi) that make assembly and distribution tractable
- 9 The Doorwaythe products that stand between an Intelligence Hub and the people who use it, and the desktop application the paper works through as its example
Part IV — THE ECONOMY
- 10 The Four-Class Marketwhat becomes tradeable once AI work is packaged, contextualized, and verifiable, and the different economics of each artifact class
- 11 Why Open Compoundsthe economic argument that an open standard, which its steward cannot fully monetize, beats a closed platform in this particular layer
- 12 The Decade Aheadthe forces that set the timetable, who captures value if the architecture wins, and what would tell you it is failing