Your Copilot and Cursor seats are approved. Adoption is climbing, engineers are shipping, the dashboards look healthy. Then the invoice changes shape. What used to be a flat seat fee is now metered by the token, and it moves with every prompt your team sends. Your first instinct is to cap usage and switch on spend alerts. That instinct may be a mistake.
This is not hypothetical. Uber's CTO told The Information his organization burned through its entire planned 2026 AI coding budget in four months, with individual engineers spending 500 to 2,000 dollars a month on tokens. Microsoft answered the same math by pulling most Claude Code licenses from its Experiences and Devices division. Two of the most sophisticated engineering organizations on the planet, and their first public responses to metered AI were a blown budget and a retreat.
So the decision in front of you is not "how do we cut the AI bill." It is "are we treating tokens as a cost to suppress, or as capital to compound?" Get it wrong and you either starve your best people or fund theater. Get it right and every token buys both an outcome today and an asset tomorrow.
Building the AI-DLC harness at Betsson, I saw the same type of tasks task run in two different ways: one setup burned ten times the tokens of the other and produced similar to worse results, purely because of how context was fed, which model was chosen, and constraints provided.
