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18/08/2026 2:43 pm
TL;DR: A proxy can route, rate-limit, and log AI agent traffic, but it cannot govern agent decisions, tool outputs, or multi-step behaviour, according to Fiddler. The governance gap is now at the system level, where observability, policy enforcement, and auditable oversight determine whether agents can be trusted in production.
NHIMG editorial — based on content published by Fiddler: AI Agent Control Plane, Why a Proxy Alone Cannot Govern Autonomous Agents
By the numbers:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems, sharing sensitive data, and revealing access credentials.
Questions worth separating out
Q: How should security teams govern shared AI agents that can inherit hidden proxy settings?
A: Treat shared agents as imported software with identity, network, and tooling metadata.
Q: Why do shadow AI agents create a governance gap for IAM and NHI teams?
A: Shadow AI agents create a governance gap because they can hold persistent permissions, act on behalf of users, and connect to corporate data while staying outside normal inventory processes.
Q: What do security teams get wrong about AI control planes?
A: They often treat the control plane as a product choice rather than a trust-boundary decision.
Practitioner guidance
- Separate routing from governance Keep gateways for transport, rate limiting, and API key handling, but move decision policy, evaluation, and redaction into a distinct control layer that can act before execution completes.
- Instrument MCP tool flows end to end Trace what enters the agent context, what tools return, and what the agent does next so that prompt injection and sensitive-data propagation can be detected across the full path.
- Create an AI agent registry Maintain a single inventory of live, testing, and retired agents with ownership, permissions, connected tools, and policy version so governance decisions are auditable.
What's in the full article
Fiddler's full blog post covers the operational detail this post intentionally leaves for the source:
- How the control-plane model maps to request, response, and decision paths in agentic systems
- The five capability areas that Fiddler uses to distinguish governance from routing, including telemetry and auditable oversight
- Examples of production failure modes such as policy drift, down-sampled evaluation, and incomplete audit trails
- How the article frames coding agents, MCP flows, and agent posture management across development and production
👉 Read Fiddler's analysis of AI agent control planes and proxy-only governance →
AI agent control planes: what proxy-only governance misses?
Explore further
18/08/2026 3:27 pm
Proxy-only governance is a category error for agentic systems. A gateway secures access, but it does not govern the decisions that follow access. Once agents can call tools, consume returned data, and trigger new actions, the relevant control is behavioural oversight across the full execution chain. Practitioners should stop treating routing as governance and start separating transport security from decision control.
A question worth separating out:
Q: Who should be accountable when an AI agent causes a security incident?
A: Accountability should sit with the human owner, platform team, or business function that granted and operated the agent. The identity may act independently, but governance cannot detach responsibility from the delegation chain. Programs should define ownership, escalation, and remediation paths before deployment so responsibility is clear when the agent's behaviour changes.
👉 Read our full editorial: AI agent control planes expose the limits of proxy-only governance
