From napkin sketch to architectural pattern

In my last post, I shared a drawing—a quick architectural sketch that looked more like a late-night whiteboard session than a polished presentation. It had messy lines, a circle around "PII?", and a visible correction where I originally wrote "ERR" before darkening it into "ERP."

That "ERR" was a Freudian slip of the best kind. It served as a reminder that without a governed foundation, an Agent Mesh will inevitably turn your ERP into an ERR system.

But we are moving past the "napkin" phase. With the recent ISO 42001 certifications from CrowdStrike and IBM, we now have the industry anchors needed to realize the pattern I sketched: the Top Layer (Brain), the Middle (Spine/Filter), and the Bottom (Body).

Mapping the pattern to the stack

This isn't about a single product; it’s about a governance pattern. To turn that drawing into a deployable reality, we have to treat AI governance as an engineering requirement. Here is how the conceptual boxes in the sketch translate into a modern enterprise reference stack:

  • The Brain (Top Layer): Represented by IBM Granite 4.0. It provides an ISO-certified "Audit Trail" for LLM intent generation.

  • The Filter (Spine): This is where IBM Granite Guardian 3.0 lives—a specialized "Risk Brain" designed to answer that "PII?" question from the sketch.

  • The Shield (Spine): This is the role of CrowdStrike Falcon AIDR, providing the runtime enforcement needed to prevent "hallucinated" or unauthorized commands.

  • The Body (Bottom): This is where webMethods acts as the mTLS anchor, bridging the certified "Brain" to the legacy systems.

Envisioning the Shield: The Falcon MCP Pattern

In the sketch, the "Shield" is the barrier between agent intent and legacy execution. In a production environment, this could be realized using the Falcon MCP (Model Context Protocol) Server.

The pattern involves routing agent requests through an MCP server rather than granting direct API access. This allows the "Shield" to evaluate an agent’s intent against real-time security telemetry before it ever touches the "Body."

Reference Logic: Validating intent at the Gateway

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Note: This logic illustrates how a "Shield" policy might evaluate agentic risk at the gateway.

# Reference logic for validating Agent intent via Falcon MCP
import requests

def shield_preflight_check(agent_intent):
    # The 'Shield' pattern evaluates if the action matches security baselines
    # before the request is routed to the legacy ERP.
    response = requests.post("https://api.falcon.crowdstrike.com/mcp/v1/validate", 
                             json={"intent": agent_intent},
                             headers={"Authorization": "Bearer ${FALCON_TOKEN}"})
    
    validation = response.json()
    return validation.get("is_safe", False)

Addressing the PII question with Granite Guardian

That circle in the drawing—"PII?"—is the primary hurdle for integration architects. You can’t just "hope" an agent doesn't leak customer data. You need a dedicated "Filter."

IBM Granite Guardian offers a blueprint for this. It is a specialized model designed for risk detection. By placing a "Guardian" node in the "Spine," architects can run a check on every agent response. If the model identifies a Social Security Number or a Credit Card in the payload, the "Filter" triggers and blocks the write.

Reference Logic: The PII Gatekeeper

# Reference logic for scrubbing responses before they hit the 'Body'
def filter_risk_pattern(payload):
    # Guardian-style models identify PII, bias, or unethical behavior
    check = requests.post("http://guardian-node:11434/api/generate", 
                          json={"model": "granite3-guardian:8b", "prompt": payload})
    
    # If the filter identifies a risk, the legacy write is aborted
    if "risk_detected" in check.text:
        raise SecurityException("PII Leak Blocked by Filter")
    return payload

The Spine: webMethods as the mTLS Anchor

None of this architecture holds up if the connections aren't cryptographically secure. In the drawing, the "Spine" handles the mTLS handshake—this is the webMethods core competency.

In this pattern, the API Gateway acts as the orchestrator. It holds the client certificates for the agents, calls the Shield to check intent, runs the Filter to check for PII, and only then opens the door to the Legacy ERP.

Architecting the transition

We are moving away from "swivel-chair security" and toward a Certified Foundation where the infrastructure itself enforces the governance.

The "ERR" in that sketch serves as a permanent reminder: without these layers, the Agent Mesh is just a cascading failure waiting to happen. With this architectural pattern, it becomes a robust, governed reality.

Viva, The Agent Mesh!

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