What happens when AI agent governance is missing at scale
meshIQ engineering head Gourab Basu argues AI agent governance must inspect proposed tool calls in-flow, since prompts alone cannot control nondeterministic agents.
In a Help Net Security interview, Gourab Basu, Global Head of Engineering at meshIQ, argues that prompt instructions are an insufficient control boundary for nondeterministic AI agents. He advocates a framework-independent governance engine that inspects proposed tool calls and parameters before execution, citing an example of pausing refunds above $100 for human approval. He warns that scaling from ten to a thousand agents makes manual oversight and destination-side controls unworkable, so governance must sit inside the agent execution flow across frameworks such as FastMCP.
- Prompts alone cannot serve as the control boundary for nondeterministic agent behavior.
- Governance layer should inspect tool call parameters before actions reach production systems.
- Framework-independent policy engine separates decision semantics from per-framework interception adapters.
- Scaling to a thousand agents makes manual review and destination-side controls insufficient.
From the original article
4 min read at helpnetsecurity.com
In this interview with Help Net Security, Gourab Basu, Global Head of Engineering at meshIQ, discusses governance in AI agent systems. He argues that instructions written into a prompt are not enough to control what an agent does, since agents can change their own path as they work. Real control means checking proposed actions before they reach production systems, such as pausing a large refund for human approval.
By Mirko Zorz · helpnetsecurity.com
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