Runpod has published an analysis of the engineering realities behind production AI agents. The piece argues that moving agents out of notebooks requires attention to infrastructure, latency, observability and failure handling.
That is a practical point as more teams discover that agent demos are easier than dependable deployment. Tool calls, retries, cost controls and GPU availability all become part of the product surface.
For builders, the message is clear: agent quality depends on the surrounding system, not only the prompt or model choice.