AI agents can talk to each other now — they just can’t understand what the other one is trying to do. That’s the problem Cisco’s Outshift is trying to solve with a new architectural approach it calls the Internet of Cognition.
The gap is practical: protocols like MCP and A2A let agents exchange messages and identify tools, but they don’t share intent or context. Without that, multi-agent systems burn cycles on coordination and can’t compound what they learn.
“The bottom line is, we can send messages, but agents do not understand each other, so there is no grounding, negotiation or coordination or common intent,” Vijoy Pandey, general manager and senior vice president of Outshift, told VentureBeat.
The practical impact:
Consider a patient scheduling a specialist appointment. With MCP alone, a symptom assessment agent passes a diagnosis code to a scheduling agent, which finds available appointments. An insurance agent verifies coverage. A pharmacy agent checks drug availability.
Each agent completes its task, but none of them reasons together about the patient’s needs. The pharmacy agent might recommend a drug that conflicts with the patient’s history — information the symptom agent has but didn’t pass along because “potential drug interactions” wasn’t in its scope. The scheduling agent books the nearest available appointment without knowing the insurance agent found better coverage at a different facility.
They’re connected, but they’re not aligned on the goal: Find the right care for this patient’s specific situation.
Current protocols handle the mechanics of agent communication — MCP, A2A, and Outshift’s AGNTCY, which it donated to the Linux Foundation, let agents discover tools and exchange messages. But these operate at what Pandey calls the “connectivity and identification layer.” They handle syntax, not semantics.
The missing piece is shared context and intent. An agent completing a task knows what it’s doing and why, but that reasoning isn’t transmitted when it hands off to another agent. Each agent interprets goals independently, which means coordination requires constant clarification and learned insights stay siloed.
For agents to move from communication to collaboration, they need to share three things, according to Outshift: pattern recognition across datasets, causal relationships between actions, and explicit goal states.
“Without shared intent and shared context, AI agents remain semantically isolated. They are capable individually, but goals get interpreted differently; coordination burns cycles, and nothing compounds. One agent learns something valuable, but the rest of the multi-agent-human organization still starts from scratch,” Outshift said in a paper.
Outshift said the industry needs “open, interoperable, enterprise-grade agentic systems that semantically collaborate” and proposes a new architecture it calls the “Internet of Cognition,” where multi-agent environments work within a shared system.
The proposed architecture introduces three layers:
Cognition State Protocols: A semantic layer that sits above message-passing protocols. Agents share not just data but intent — what they’re trying to accomplish and why. This lets agents align on goals before acting, rather than clarifying after the fact.
Cognition Fabric: Infrastructure for building and maintaining shared context. Think of it as distributed working memory: context graphs that persist across agent interactions, with policy controls for what gets shared and who can access it. System designers can define what “common understanding” looks like for their use case.
Cognition Engines: Two types of capability. Accelerators let agents pool insights and compound learning — one agent’s discovery becomes available to others solving related problems. Guardrails enforce compliance boundaries so shared reasoning doesn’t violate regulatory or policy constraints.
Outshift positioned the framework as a call to action rather than a finished product. The company is working on implementation but emphasized that semantic agent collaboration will require industry-wide coordination — much like early internet protocols needed buy-in to become standards. Outshift is in the process of writing the code, publishing the specs and releasing research around the Internet of Cognition. It hopes to have a demo of the protocols soon.
Noah Goodman, co-founder of frontier AI company Humans& and a professor of computer science at Stanford, said during VentureBeat’s AI Impact event held in San Francisco that innovation happens when “other humans figure out which humans to pay attention to.” The same dynamic applies to agent systems: as individual agents learn, the value multiplies when other agents can identify and leverage that knowledge.
The practical question for teams deploying multi-agent systems now: Are your agents just connected, or are they actually working toward the same goal?
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