You control what your AI agent can do by deciding which tools it has access to, setting rules about when it can use them, and requiring human approval before high-stakes actions are taken. This combination keeps you in charge without slowing the agent down on routine tasks.
The Three Levers of Agent Control
Controlling an AI agent is not complicated once you understand the three levers available to you. First, you control the toolset — what tools the agent has access to at all. If the agent cannot see a tool, it cannot use it. Second, you write instructions that tell the agent when and how to use each tool. Third, you decide which actions require your sign-off before the agent proceeds.
Think of it like managing a new employee. They can handle routine tasks on their own, but for anything involving money, sensitive information, or public communication, they check with you first. Same principle applies to your AI agent.
Human-in-the-Loop for High-Stakes Actions
One of the most practical control mechanisms is the human-in-the-loop step. For certain tools — like sending emails, posting to your community, or making changes to student records — you configure the agent to draft the action and wait for your approval before executing. The agent does the thinking and prep work, but you press “go.”
For lower-risk actions — like looking up information, summarizing content, or generating draft responses — you can let the agent run autonomously. This distinction between autonomous and approval-required actions is worth mapping out before you deploy any agent in your business.
What This Means for Educators
As a coach or trainer, your most sensitive actions are probably communication-related: sending messages to students, posting announcements, updating enrollment status. These are exactly the tools you want to keep under human approval. Meanwhile, tasks like drafting a follow-up email, generating a lesson recap, or looking up a student’s progress can run automatically without much risk.
Start by listing the tools your agent will have and marking each one as either autonomous or approval-required. That list becomes your agent’s operating policy — and it gives you a clear picture of where the agent is fully trusted and where you stay in the loop.
The Simple Rule
Any action that cannot be easily undone should require human approval before your agent executes it. Read-only actions — looking things up, generating drafts, summarizing — are safe to automate. Write actions — sending, publishing, updating, deleting — deserve a second set of eyes, at least until you have tested the agent enough to trust its judgment on those tasks.