A simple AI governance checklist for your first production agent
A lot of agent projects spend months improving prompts, models, and workflows, then ship to production without asking a few fairly basic questions. Before trusting an AI agent with real work, I'd want clear answers to these:
1. What actions is the agent allowed to take?
Define the boundaries before deployment, not after.
2. Which tools and systems can it access?
Give access based on necessity, not convenience.
3. Are sensitive actions gated by approval?
Not every step needs review, but some decisions probably should.
4. Is there a record of what the agent did?
If something goes wrong, you should be able to reconstruct the sequence of events.
5. What happens when the agent is uncertain?
Low-confidence outputs need a clear path instead of silently moving forward.
6. Can you roll back mistakes?
Every production workflow should have a recovery plan.
7. Who owns the outcome?
At some point, a person needs responsibility for the workflow, even if an agent is doing most of the work.
None of these questions are particularly complicated. What's surprising is how often they only come up after an agent is already running in production.
What would you add to the list before trusting an agent in production?
Replies
Great checklist. I’d add “What data is the agent allowed to remember?” Access permissions are important, but memory and data retention can quietly become a bigger risk.
One thing I’d add is monitoring for behavior drift. An agent may behave correctly during testing but start taking unexpected paths as tools, prompts, data, or surrounding systems change.
I think production automation needs more than just prompt rules. Adding more rules can make an agent less flexible, but it still does not fully prevent hallucinations or unsafe actions.
A better approach might be to use specialized agents. Each one handles a specific task with full control, but only inside a limited context. That way, the system stays capable without giving one agent access to everything.
How do you enforce those limits during execution?
solid list. I'd add one that's easy to skip if all your agent examples are text/API-based: does the action happen in the real world where it can't be undone. rollback plans work great for a database write or a sent email you can follow up on, but a phone call the agent already made and the person already heard has no rollback, whatever it said is now common knowledge between two humans. worth explicitly separating reversible actions from ones where the best you get is a fast correction afterward, not an undo