Katamari strategy: applied AI firms training their own models
The observation flips the usual assumption that startups should stay thin wrappers over frontier APIs. Founders deciding between fine-tuning in-house and riding foundation model progress can use the three-part test: domain clarity, training budget, and demand density. It also hints at where vertical AI moats may erode as base models improve.
