Article
If you are putting AI agents inside your company, treat them like new interns.
They do not know your business, your products, your prices, or how your team communicates. They cannot reliably figure all of that out on their own. You have to give them focus.
I use a simple framework for this: JAR. It stands for Job, Authority, Review.
Job: give the agent something specific to do
An agent needs a clear assignment. A generic instruction leaves too much room for interpretation, and the agent will not always land where you expected.
Be specific about the work you want it to handle. What is the task? What should the finished output look like? Where does its responsibility begin and end?
Think about how you would assign work to a new intern. You would not point vaguely at the company and ask them to make things better. You would give them a defined job. An AI agent needs the same kind of focus.
Authority: define what it can know and say
Once the job is clear, decide what information the agent needs inside your systems. That could include product details, prices, or CRM information.
Access is only part of authority. You also need to define what the agent can discuss with other people.
If it will communicate with staff or customers, what is it allowed to say? What should it avoid?
This boundary matters because an agent can hallucinate products or prices that do not exist. That is a major no-no.
Give the agent enough context to do its job, then put clear limits around how it uses that context.
Review: keep checking the work
Review can seem like a small final step. It is probably the most important one.
At the start, check the agent's output closely. Make sure the information is true and the result matches what you asked for. Releasing unchecked output can cost you reputation and create trouble when the agent gives people information that is not true.
Once the work is stable and you are confident in it, the review can become lighter. Check in every so often, perhaps once a week or once every two weeks, and confirm that the agent is still producing what you expect.
I have seen agents drift. The change is not always dramatic, but it can be enough to become annoying. Regular review helps you catch that drift before it turns into a bigger problem.
Put the three pieces together
Before you put an agent to work in your business, answer three questions:
- What specific job does it have?
- What information and communication authority does it have?
- How will you review its output now and over time?
Job gives the agent focus. Authority gives it the context and boundaries to operate. Review confirms that it is still producing what you expect.
That is JAR: Job, Authority, Review. Stick to those three pieces and you will be ahead of most companies trying to put AI inside their business.