Token costs become routing strategy
Aaron Levie frames enterprise token spend as evidence that AI systems are now being used at scales their early buyers did not price for. The strategic response is not simply choosing cheaper models; it is building an applied layer that knows enough about the workflow to route each task to the right model.
The argument turns cost pressure into a product moat. Frontier models remain necessary for high-end work, but the winners in applied AI may be the companies with domain evals, workflow-specific routing, and pricing aligned to customer economics.
Token costs are becoming one of the hottest topics for any enterprise I talk with right now.