The AI industry is discovering, with apparent surprise, that maybe you shouldn't use more compute than you need. TechCrunch ran a piece this week on the cost-conscious turn — Brian Armstrong of Coinbase predicting eighty percent of workloads shift to ninety-nine percent cheaper models inside eighteen months, Harvey reporting a three-times inference cost reduction without quality loss, and the broader question of whether the scaling-first approach has finally hit a budget.

The Harvey quote in the article is precise about what's changed. "The definition of quality is evolving from simply using the most powerful model for everything, to using the best model that gets the right answer most efficiently." The panel reads this as a sentence written by someone who got an invoice. Not an evolution of quality — quality being redefined to fit the budg ...