Letting AI Debug Production

It’s 2 in the morning, and you’re reading an incident channel: checkout is failing, orders are stuck, and support is starting to field angry messages from customers who can’t get past payment. After quite a bit of digging through the logs, you find the cause. It was a rejected payment call buried deep in thousands of entries. And you’re left thinking: this is exactly the kind of grunt work an AI agent should be able to take off your hands. For AI coding assistants, writing new code is the easy part. The hard part has always been maintenance. But you can’t just set an agent loose in production. It can easily corrupt the database, and all it can do afterwards is apologize and promise not to do it again. An agent debugging a codebase can read the code and guess, or execute the code and risk side effects. Test suites by themselves are not enough because a production incident is, by definition, a case the tests didn’t cover. What AI, or humans, for that matter, actually need is a way to…