Agentsecurity

A diagram showing Claude Code delivery controls and enterprise AI security controls sharing one agent budget

Treat the agent budget as a security budget

Claude Code teams already budget scope, tools, review time, and rollback effort. Security teams should treat that same budget as delegated authority, evidence, and risk ownership.

A production AI agent operating model connecting engineering delivery controls with security evidence controls

The agent rollout needs one operating model

Teams buying Claude Code or enterprise AI agent guidance do not need two disconnected playbooks. They need one operating model that connects delivery speed, delegated authority, evidence, rollback, and security review.

A production agent control loop connecting Claude Code delivery practices with enterprise AI agent security controls

Agentic coding is also a security decision

Claude Code can ship useful patches quickly, but production agents also create authority, evidence, rollback, and audit questions. Teams need the delivery loop and the security loop together.

A control map showing security questions for a Claude Code rollout: authority, boundaries, evidence, and risk ownership

What security should ask before a Claude Code rollout

Before Claude Code becomes a team habit, security should ask about authority, boundaries, evidence, rollback, and ownership. These questions turn agentic coding from a demo into a reviewable operating model.

Cover of Securing Enterprise AI Agents by Thomas De Vos

Securing Enterprise AI Agents is live

I published Securing Enterprise AI Agents, a practical book on bounded AI autonomy, AgentSecOps, MCP security, RAG governance, identity, evals, policy, and evidence.

What is an AI agent? A practical definition for production teams

AI agents are not just chatbots with a loop. For production teams, the useful definition is about delegated authority: what the system can see, decide, call, change, and prove afterward.