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. It runs a local process as if it were a real pod inside your cluster: real env vars, real DNS, real network, optionally real inbound traffic. A real example: Daylight Security pairs Cursor with mirrord for daily development. Their team cut their typical edit-test cycle from 5–8 minutes to about 5 seconds. The reason isn't faster CPUs; it's that the agent now operates against the real cluster the way a senior engineer would, instead of guessing from logs.…