Enterprise AI coding bills are hitting absurd numbers. One source told Axios that a client spent $500 million in a month on Claude Code. Gartner's latest data says 23% of tech leaders are spending $200-500 per developer per month on tokens alone. Uber reportedly burned through its entire 2026 Claude Code budget by April and had to cap spending at $1,500/month per employee.
These aren't edge cases anymore. This is the new normal. And the uncomfortable truth is that most of this spend is waste.
The One-Model Trap
Here's what typically happens: A team adopts Claude Code or Copilot. They default to the most powerful model available because that's the safest bet. Every task — from scaffolding a React component to planning a complex distributed system migration — runs through the same frontier model at the same price.
The problem? Roughly 70-80% of coding tasks don't require frontier-level reasoning. Writing boilerplate, generating tests from existing code, formatting, simple refactors, documentation — these tasks get identical results from models that cost 5-10x less.
