Agentic AI Needs Its TCP/IP Moment

Summary

Internet of Agents Stack Reference ArchitectureIt’s probably unsurprising to regular readers of this Substack that Agentic AI is evolving fast, but without shared protocols for communication, tool use, memory, and trust, these systems will remain siloed. To unlock their full potential, we must build an open, interoperable stack — an Internet of Agents.Today’s agents can reason, plan, and act autonomously within bounded environments. But real-world tasks cut across platforms and domains. That demands agents who can collaborate, delegate, and share knowledge across organisational and technical boundaries. Like the early internet, we’re missing the protocols, and without them, scale and composability will stall.AI agents operate efficiently within their native ecosystems, like Microsoft, NVIDIA, OpenAI, Meta, Google, ServiceNow, Salesforce, or frameworks such as LangChain, PydanticAI, or LlamaIndex, but their integrations across ecosystems and platforms remain costly, brittle, and non-scalable. Their toolchains, memory models, comms protocols, and access layers are tightly coupled to their execution environments. There's no shared grammar for agents to delegate tasks, invoke tools, or share memory across boundaries.We're in the pre-TCP/IP era of agents: powerful local nodes, no scalable network.Interoperability isn’t a single spec – it’s a stack. Here are the key architectural dimensions where we need standards or shared patterns:Tool Use & InvocationStandardised, agent-aware tool interfaces built upon existing protocols like OpenAPI, JSON-RPC, or GraphQL. This could involve agent-centric enhancements to enable reasoning about tool semantics, capability descriptions, and dynamic binding at runtime.Example: Model Context Protocol (Anthropic), Agent Communication Protocol (IBM/BeeAI)Agent Communication & MessagingA protocol layer for agent-to-agent messaging, task delegation, and negotiation. Needs standard message schemas, status codes, and handshake patterns.Example: A...