AI Agent Governance: 7 Best Practices for Production
Seven battle-tested practices for governing AI agents in production — from audit trails to kill-switches.
What you will learn
- Apply 7 governance best practices to your AI agent fleet
- Understand the governance pyramid: visibility, control, compliance
- Design policy hierarchies that scale across teams and tenants
The Governance Pyramid
Agent governance is not a single checkbox — it is a pyramid. The foundation is visibility (can you see what agents are doing?), the middle layer is control (can you stop them?), and the top is compliance (can you prove it to auditors?).
Most teams skip straight to compliance and wonder why audits fail. You cannot prove control you do not have, and you cannot control what you cannot see.
1. Maintain an Immutable Audit Trail
Every agent action should be logged to an append-only store. Not just what happened, but who triggered it, which model was used, how many tokens were consumed, and what the output was. This is your foundation for everything else.
Dobby logs every agent action to an immutable audit trail with 365-day retention. Every LLM call, every tool use, every approval decision — all queryable, all exportable for auditors.
2. Require Human Approval for High-Risk Actions
Not every action needs approval. Reading a file is low risk. Deploying to production is high risk. Configure approval gates based on the impact of the action, not just the agent performing it.
3. Set Token Budgets Per Agent
A single misconfigured agent can burn through thousands of dollars in hours. Set daily and monthly token budgets per agent, per tenant, and per organization. Alert at 80%, warn at 90%, block at 100%.
4. Restrict Models by Policy
Not every agent needs GPT-4. A summarization agent works fine with a smaller model. Restrict which models each agent can use — this reduces cost and limits the blast radius of a compromised agent.
5. Enforce Data Residency
If your organization operates under GDPR, SOC 2, or similar frameworks, agent data must stay within designated regions. Choose your region at workspace creation and ensure no agent call crosses boundaries.
6. Implement Role-Based Access Control
Not everyone should be able to configure agents, approve actions, or view costs. Use a 3-level RBAC hierarchy: Platform admins set global policies, Organization owners manage their org, Tenant members work within their workspace.
7. Have a Kill-Switch Ready
When something goes wrong — and it will — you need to stop everything instantly. A kill-switch should propagate within seconds, be scoped (all traffic, LLM only, or new keys only), and leave an audit record of who activated it and why.
Governance is ad-hoc. Policies live in Confluence docs nobody reads. When an agent misbehaves, the team scrambles to find the off switch. Audit prep takes weeks.
Governance is enforced by the platform. Policies are code. Every action is logged automatically. Kill-switch stops everything in 5 seconds. Audit prep is a query.
All 7 practices are built into Dobby as platform features — not add-ons. Audit trails, approval gates, budgets, model restrictions, data residency, RBAC, and kill-switch are available on every plan.