As AI agents become increasingly integrated into development workflows, the shift from demo to production environments reveals critical challenges. AI agents, while powerful, can cause memory leaks, zombie processes, and security breaches when scaled to serve multiple concurrent users. The 'Happy Path' of development, where an agent is tested on a single user, often overlooks these issues.

When agents access sensitive files or consume excessive resources, it can lead to shared secrets, resource exhaustion, and unmanaged processes. To address these, developers need to implement isolation techniques similar to Kubernetes. Ephemeral sandboxes, hard resource limits, and egress filtering are essential to ensure each agent runs in a safe, isolated environment.

By adopting these practices, developers can focus on agent logic while the infrastructure handles isolation, scheduling, and cleanup, ensuring a smooth transition from development to production.