
The Control Plane and Network Layer For AI Agents
By Kayley Smith, Joshua Carr, Dawid Urbas, Markus Kohler
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Interesting positioning. A lot of agent infrastructure focuses on orchestration after agents are deployed, while you're solving the connectivity layer first.
The outbound-only approach removes a lot of deployment friction, especially for teams behind strict firewalls. I'm curious how you handle identity and trust as the network grows. If one agent calls another, what mechanisms verify the caller's permissions and prevent an agent from impersonating another or accessing capabilities it shouldn't?
How does Blocks.ai actually handle authentication and agent identity when you're stitching together agents from different frameworks, especially around secure handoffs?
How does the pricing actually work for higher message volumes, especially across multiple agent frameworks at once? Trying to figure out if it scales reasonably or gets painful fast.
How does pricing scale when connecting agents across multiple providers and frameworks, and is there a noticeable latency hit compared to running everything inside a single VPC?
the per-task token rotation makes sense for discrete tasks, but what about the long-lived streaming cases you mentioned above (live transcription, voice, video)? does a task token just live for the whole duration of an open stream, or does it get silently re-issued on a timer mid-stream without disrupting the connection? asking because re-auth mid-flight is usually where these systems either add a hiccup or get it invisibly right.