Agent Governance

Agent Governance Patterns

Patterns for adding safety, trust, and policy enforcement to AI agent systems.

Overview

Governance patterns ensure AI agents operate within defined boundaries — controlling which tools they can call, what content they can process, how much they can do, and maintaining accountability through audit trails.

User Request → Intent Classification → Policy Check → Tool Execution → Audit Log
                     ↓                      ↓               ↓
              Threat Detection         Allow/Deny      Trust Update

When to Use

• Agents with tool access: Any agent that calls external tools (APIs, databases, shell commands)
• Multi-agent systems: Agents delegating to other agents need trust boundaries
• Production deployments: Compliance, audit, and safety requirements
• Sensitive operations: Financial transactions, data access, infrastructure management

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Pattern 1: Governance Policy

Define what an agent is allowed to do as a composable, serializable policy object.

from dataclasses import dataclass, field
from enum import Enum
from typing import Optional
import re