Stop Burning AI Credits: A Framework for Right-Sizing Model Usage
Four months into 2026, Uber's AI budget for the year was already gone — thousands of engineers with un-gated access to Claude Code, bills reportedly running $500–$2,000 per person per month, and leadership asking very loud questions about what exactly all those tokens were buying. Around the same time, an unnamed "mystery company" reportedly burned $500 million on Claude credits in a single month — not from a runaway model or a billing bug, but because nobody had thought to put a usage cap on employee licences.
Neither story is about bad engineering. Both are about one broken default: when developers get unrestricted access to frontier models, they use frontier models for everything.
I've been working through a framework to fix this — not by restricting access, but by routing the right task to the right model. The goal is frictionless development that doesn't quietly drain your budget. Here's how it works.