The bottleneck for long running agents is no longer the model, It's the environment.

I built a helm chart to get stateful sandboxed agents out of the box in a kubenetes cluster using aws's cloud primitives

An agent that runs in a throwaway container with no persistent storage and shared network access is fundamentally limited.

It cannot accumulate context across sessions.

It cannot install tools and keep them around. It's a cool demo but can't do much.

Give it an isolated persistent sandbox and suddenly the ceiling goes way up.

The agent can build up its workspace over time, maintain state across sessions, and operate without stepping on other agents. With everything tracked in Git.

The models will keep getting better.

The base harness will keep evolving.

But the environment is what lets agents go from "run a task" to "live in a workspace"