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AI in production. How to give coding agents production context, connect them over MCP, and let AI change live systems with the right guardrails.

AI in production covers two things: using AI agents to run and debug production systems, and running AI workloads safely once they are live. Both raise the same questions about access, review and what happens when the agent is wrong.

These guides are for engineers who already use coding agents such as Claude Code or Cursor and want to point them at production. They cover how to give an agent logs, traces and infrastructure context, how much access to grant and how to scope it, how to stop an agent's change from breaking production, and how the managed agent platforms from the large clouds work and where they fall short. Each guide is specific about permissions and review, because that is where most of the risk sits.

How Polylane works on these platforms: AWS and Kubernetes.

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