You know that feeling when you deploy an AI agent on Monday morning, check the logs Wednesday, and suddenly discover you've burned through three months' worth of API budget in 72 hours? Yeah. That happened to me too. The problem isn't that AI agents are expensive—it's that they're invisibly expensive. Unlike traditional applications where you can see requests flowing through your infrastructure, agents operate in feedback loops, making retries, spinning up parallel tasks, and calling external APIs in ways that are genuinely hard to predict. By the time you notice the damage, you're already deep in the red. Let me walk you through the playbook I've built to keep costs under control. The Three Leaks First, identify where your money's actually going. AI agents typically hemorrhage budget in three places: Token overflow : Your agent hits a rate limit, retries with exponential backoff, and suddenly one simple task has consumed 10x its intended token count. This escalates fast.…