AI agent
An AI agent is a program that takes a goal, plans the steps to reach it, calls tools or APIs to carry them out, and checks its own progress before reporting back. Unlike a chatbot, an agent acts on systems rather than only producing text about them.
What are the parts of an AI agent?
- A model that decides what to do next, given the goal and everything observed so far.
- Tools: the functions, APIs and databases the agent is permitted to call, each with a defined signature.
- Memory: what carries between steps within a task, and what persists between tasks.
- A control loop that decides when to continue, when to ask a human, and when to stop.
- Logging of every step, without which no one can reconstruct why the agent did what it did.
The tool list is the security boundary. An agent can only affect what it has been given a tool for, so the review question in an enterprise deployment is which tools exist and what each one is allowed to touch, rather than how capable the underlying model is.
How is an agent different from a chatbot?
| Chatbot | Agent | |
|---|---|---|
| Output | Text | Actions, then text |
| Steps per request | One | Many, decided at runtime |
| Touches other systems | No | Yes, through defined tools |
| Failure mode | A wrong answer | A wrong action, possibly irreversible |
| What review needs | Answer quality | An audit trail of steps and calls |
The failure mode is why the two are governed differently. A chatbot that answers wrongly costs a reader some time; an agent that acts wrongly has changed a record, sent a message or moved money, and the control that matters is which actions require confirmation before they happen.
What does an enterprise deployment have to control?
- Scope each tool to the narrowest permission that still allows the task, using a service identity rather than a person's credentials.
- Require confirmation before any irreversible action, and define exactly which ones qualify.
- Log every step, tool call and result in a form an auditor can read months later.
- Set a budget in steps or time, so a loop terminates rather than running until someone notices.
- Decide where the model runs, since sending internal data to a hosted model is a data transfer whatever the interface looks like.
Frequently asked questions
- What is an AI agent?
- An AI agent is a program that takes a goal, plans the steps to reach it, calls tools or APIs to carry them out, and checks its progress before reporting back. The distinguishing property against a chatbot is that it acts on systems rather than only producing text about them.
- What is the difference between an AI agent and a chatbot?
- A chatbot produces text in a single step. An agent decides a sequence of steps at runtime and calls tools that change things: sending a message, updating a record, running a query. That difference in effect is why agents need action-level permissions and an audit trail, and chatbots generally do not.
- What tools can an AI agent use?
- Only the ones it is given. Tools are defined functions with a signature and a permission scope: a database query, an HTTP call, a file operation, a message send. The tool list is the security boundary of the deployment, because an agent cannot affect anything it has no tool for.
- Are AI agents safe to run in production?
- They are as safe as the permissions and confirmations around them. The controls that matter are least-privilege tool scoping, a confirmation step before irreversible actions, complete logging of steps and calls, and a step or time budget so a loop terminates on its own.
- Can an AI agent run on-premise?
- Yes, when the model, the tools and the orchestration all run on local hardware. Ayonix ATLAS agents are built for that case, including air-gapped installations. The practical constraint is model size against available hardware, not the agent architecture itself.
- Do AI agents replace staff?
- In deployments that work, they take the mechanical parts of a workflow and leave the judgement and the approval with a person. Handing an agent an unsupervised end-to-end process is what produces the failures that get written about, because there is no step at which a mistake is caught.