1. The AI Race Is a Category Error
AI competition is not one race but many layered domains with different constraints and timelines.
A dossier on the structural and economic forces shaping competition in large language models.
AI competition is not one race but many layered domains with different constraints and timelines.
Early infrastructure advantage can flip into a liability when cost curves collapse faster than capital amortization.
Technical improvements stop producing advantage once users can no longer perceive the difference.
Skill-forming and fact-forming data drive different kinds of model progress and are often mistaken for one another.
Local models become competitively viable when remaining performance gaps fall below practical perception.
Large language models are evolving along two economic trajectories: attention capture and intent execution.
Sovereignty as a Structural ForceWhen Diffusion Becomes Strategically Incentivized