1. The AI Race Is a Category Error
AI competition is not one race but many layered domains with different constraints and timelines.
An introduction to the forces that drive competition, cost, and control in the large language model industry.
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.
As large language models become strategic infrastructure, sovereignty turns dependency, jurisdiction, and control into forces that shape competition.