Preface
Most platform teams are no longer being asked whether AI belongs in the engineering workflow. They are being asked when it will arrive, where it will run, what it will be allowed to touch, and who will answer when it makes a poor decision. Those are not model questions. They are platform-engineering questions: identity, policy, delivery, observability, ownership, and recovery. A useful agent must fit inside those controls. Otherwise, it is just a fast new way to create an incident.
This book grew out of a live build in which Claude Code helped assemble a 33-component AI-native internal developer platform on a real Kubernetes cluster. The agent scaffolded configuration, wired GitOps applications, created Backstage templates, declared agents, ...
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