We are currently in the "Wild West" phase of Agentic AI. The prevailing wisdom on X (formerly Twitter) is that the future belongs to "Swarms"—decentralized groups of autonomous agents (Coder, Reviewer, Planner) chatting peer-to-peer to solve complex problems.
It sounds beautiful. It feels organic.
It is also an architectural nightmare that we already solved in 2004.
If you are building an Agentic architecture today without a central governor, you are falling into the Choreography Trap. And if you don’t fix it, your system won't just fail; it will hallucinate itself into a security breach.
📉 The Math of the Mess (The N2 Problem)
In the current "Swarm" model, we let Agent A talk to Agent B, who asks Agent C for data, who pings Agent A for clarification.
In Integration Architecture, we call this Point-to-Point (P2P) Spaghetti. The math is unforgiving. As you add Agents (N) to your swarm, the number of potential communication pathways grows by N(N-1)/2.
Agent Count | Potential Connections | Complexity Level |
3 Agents | 3 connections | ✅ Manageable |
10 Agents | 45 connections | ⚠️ High Risk |
50 Agents | 1,225 connections | 🚨 Impossible |
We call the cost of managing these connections the Coordination Tax.
In traditional software, the tax is paid in latency. In Agentic AI, the tax is paid in Context Window and Hallucination Risk.
Every time Agent A has to explain the "Goal" to Agent B, you burn tokens. By the time the message reaches Agent Z, the original intent is gone. The swarm isn't "thinking"; it's just gossiping.
👻 The Silent Killer: Permission Drift
This is the failure mode nobody talks about.
In a swarm, Agent A passes a task to Agent B. Agent B creates a sub-task for Agent C. By the time Agent C executes the command, the original security context (the User's Intent) has been summarized, re-tokenized, and diluted three times.
The "Telephone Game" Vulnerability:
Agent C doesn't know who authorized the request; it only knows that Agent B asked for it.
This is Permission Drift. The swarm isn't just "thinking"; it is slowly forgetting the rules. Without a central authority to re-validate the credentials at every hop, you are building a system designed to be socially engineered by itself.
🏰 The Return of the King: The "Cognitive Broker"
To scale Agentic AI, we must kill the "Swarm" and build the Hub.
We need a Cognitive Broker—a central Governance Layer that sits between your Agents.
This isn't the heavy XML-based ESB of the past. It is a lightweight, deterministic router that enforces the Physics of the System.
The Hub-and-Spoke Pattern
🚫 Agents Don't Talk to Agents: The "Coder Agent" submits code to the Broker, not the "Reviewer Agent."
🧠 The Broker Maintains State: The Broker holds the "Global Truth" (The Goal). It doesn't rely on the Agents to remember the plan.
⚖️ Deterministic Routing: If the code fails the test, the Broker routes it back to the Coder. The Coder cannot "convince" the Reviewer to let it slide because they never speak.
🛡️ Why This Matters for the CIO
If you are a CTO or Chief Architect, you aren't looking for "cool demos." You are looking for Auditability.
In a Swarm, if the system hallucinates and deletes a production database, who do you blame? The Coder? The Planner? The Reviewer? There is no single log of truth because the state was distributed in chat logs.
In a Hub, the Broker is the immutable log. You can replay the decision tree. You can see exactly where the intent drifted.
Stop Building Spaghetti
Agents are effectively "Microservices with an Attitude Problem." They are non-deterministic, probabilistic, and chatty. Treating them like magical employees that can "figure it out" is a mistake.
The future of Agentic AI isn't a flat mesh. It’s a hierarchy.
It’s time to stop paying the Coordination Tax.
Bring back the Hub.
📚 References & Further Reading
For those building the "Spine" of the Agentic Mesh, these papers define the new standard:
The Mathematical Limit: Chan, et al. (2023). "ChatEval: Towards Better LLM-Based Evaluators through Multi-Agent Debate." (Demonstrates that without a judge, agents spiral into agreement loops).
The Architecture: Cherri, R. (2026). "The Sovereign Trust Layer: Moving from Policy to Physics." ImmoQuick Whitepaper. (A breakdown of using TEEs to enforce liability at the hardware level).
The Security Standard: OWASP Top 10 for LLM Applications (2025). "LLM01: Prompt Injection & LLM04: Model Denial of Service."
The Governance Mandate: ISO/IEC 42001 Annex B.9. (Mandates audit trails for autonomous decision-making).