It made me think about something I don’t see discussed as much:
Most agent frameworks optimize for capability and iteration speed. That makes sense for personal assistants.
But enterprise environments operate under very different constraints:
- No inbound tunnels – Strict egress control – Identity enforcement – Tenant isolation – Audit logging – Deployment portability (local/cloud/air-gapped)
When agents move from “assistant” to “worker,” the runtime layer becomes critical.
Curious how others here are thinking about:
What does a production-grade AI agent runtime need to look like for regulated environments?
Would love to hear real-world deployment experiences.