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 turn into a liability when cost curves collapse faster than capital can amortize.
Technical improvements stop producing advantage once users can no longer perceive the difference.
Skill-forming and fact-forming data produce different kinds of model progress, but release cycles often blur them together.
Local models become competitive when the remaining gap falls below what users can notice.
Large language models are splitting into two economic roles: attention capture and intent execution.
As large language models become strategic infrastructure, sovereignty turns dependency, jurisdiction, and control into forces that shape competition.