This is the central concept of creating a new infrastructure for AI agents to communicate, collaborate, and share context, much like the internet did for computers. It proposes new protocols and a 'cognition fabric' to move beyond the current paradigm of isolated, non-cooperative agents.
The discussion contrasts the dominant industry approach of building ever-larger, monolithic models (vertical scaling) with a new paradigm of connecting many specialized, distributed agents (horizontal scaling). This distributed approach is presented as more resilient, innovative, and less prone to dangerous concentrations of power.
A significant portion of the discussion focuses on the need for new standards for agents to discover, identify, communicate with, and observe each other, analogous to TCP/IP and HTTP for the internet. Cisco is leading the open-source Agency.org project to build this 'plumbing' and proposes extending the OSI model with new layers for syntactic and semantic communication.
The conversation grounds the futuristic vision in the practical realities of enterprise needs. It emphasizes that widespread adoption hinges on effective guardrails, robust security models (like T-back), comprehensive observability, and the ability to manage a heterogeneous, multi-vendor agent environment.
The discussion is supported by concrete examples of implementation. Cisco's internal Community AI Platform Engineer (CAPE) system, a multi-agent solution that automated 40% of SRE tasks, serves as a powerful proof-of-concept for the productivity gains and operational efficiencies possible with this approach.
Keep pulling the thread on Vijoy Pandey.