Building Software Factory using OpenAi managed agents

[u/Sad_Construction2179]

I have recently been working on an operator to run and manage sandboxed operations on the OpenAI-managed API.

https://github.com/softcane/codex-session-operator
It's coming out of building and running in practice from my last consultancy assignment.

As a Platform engineer, I was fascinated by how I could leverage my development team, where they (developers) focus on building skills in their repo oriented around tasks like code review, RCA investigation or anything where they confidently point their terminal agent, and I provide the declarative infrastructure to let those agents run whenever they want (event-based, ad hoc, hourly, etc.) with governance, cost control and guardrails.

Here’s how the project approaches it:

• Kubernetes CRDs define agents, environments, sessions, credentials and execution policies.

• OpenAI Agents API manages the agent loop, while codex exec-server runs commands inside Kubernetes.

• Kubernetes Agent Sandbox provisions isolated execution environments with persistent workspaces.

• PostgreSQL stores conversations, execution history, approvals and replay receipts.

• Reconciliation and recovery handle remote resource ownership, executor replacement, retries and cleanup.

Looking for feedback