AI agents write code that compiles, runs locally, and breaks the first time it touches your Kubernetes cluster. The cluster is full of state the model never sees: the env vars on the running pod, the schema in your real Postgres, the headers your upstream auth-service sends, the topics your consumer subscribes to. Without that context, the code an agent writes for your live infrastructure is informed guessing, whether you're shipping a new feature or fixing a regression. mirrord closes that gap...