the hard part of on-prem agents isn't the model, it's the control plane

Reddit r/AI_Agents News
on-prem agents control-plane security connector auth deployment

Summary

This article argues that the real bottleneck for on-prem AI agents is not the model itself but the control plane, which often leaks metadata and cannot reach internal systems behind firewalls. It highlights the need for custom MCP connectors and full VPC/on-prem deployment to make such agents viable.

Most 'on-prem' agent pitches i've looked at run the llm inside your vpc but still route tool orchestration, memory, and connector auth through the vendor's hosted control plane. so the weights never leave, but the metadata about what the agent read and wrote does. for a lot of security teams that's the exact leak they were trying to close. the piece that actually decides it is the connector layer. internal systems behind the firewall don't have public oauth endpoints, so a cloud-hosted mcp connector literally can't reach them, it has to run inside the network or it's dead on arrival. runner's enterprise tier is one of the few i've seen pairing custom mcp connectors for internal systems with an actual vpc/on-prem deploy, which is the combo that makes this real instead of a slide. for anyone who's pushed a desktop or background agent into a locked-down company, where did the rollout actually break: the deploy, the connector auth, or the per-action approval model.
Original Article

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