A few months ago I opened our cloud bill and had that small stomach drop moment every engineer knows. Our AI coding spend had roughly tripled. Not because anything was broken, but because everything was working. The team had gone all in on Claude Code and Codex, they were shipping faster than ever, and nobody, including me, could say where the money was actually going.
I run engineering at a small software company. We're not Uber. But it turns out the shape of this problem is the same whether you have 15 engineers or 5,000, and the big players hit it first and hardest. Uber reportedly burned through its entire annual AI coding budget in four months. Meta's engineers pushed tens of trillions of tokens in a single month, partly chasing an internal usage leaderboard, and their own CTO had to point out that token usage isn't a measure of impact.
If it can happen to them, it can absolutely happen to you. Here's what actually went wrong for us, and the concrete things that brought it back under control.
The problem isn't the tools. It's the blindness.
The productivity gains from agentic coding are real. I'm not here to be a skeptic. The speedup was immediate and nobody wanted to go back. The problem is a specific and dangerous gap: you can't see the spend until the invoice arrives, and by then it's already spent.
