AI agents, explained
A normal AI response gives you text. An agent can continue from that response by choosing another step, asking a tool for information, and adjusting its plan.
An AI agent is a system that plans a sequence of steps toward a goal and uses available tools to gather information or perform actions.
An agent works toward an outcome
You give an agent a goal rather than every individual instruction. The agent can divide that goal into smaller tasks and decide which available tool fits each task.
For example, an agent handling a request could look up a record, check a rule, and prepare an action. Its permissions determine whether it may only suggest that action or carry it out.
Tools give the agent reach
An AI model cannot open a business system by itself. The surrounding agent can offer tools for approved data sources and actions. Each tool has a defined purpose and input.
That reach needs boundaries. People still set the goal, decide which tools are available, and define where review is required.
AI agent terms
- Goal
- The outcome the agent is asked to work toward.
- Tool
- A connected function or service the agent can ask to read information or perform an action.
- Guardrail
- A rule that limits what the agent may access, decide, or change.
What to define before using an agent
The outcome
State what should be true when the work is complete.
The permissions
Give the agent only the data and actions required for the task.
The approval points
Decide which choices or actions still need a person.
Questions about AI agents
No. A chatbot may only return a response. An agent can plan further steps and use tools to work toward a result.
It can choose among actions allowed by its design. People should define the rules, permissions, and approval points around those choices.
No. Agents can have different levels of independence. Some suggest each action, while others carry out bounded steps before asking for review.
Related glossary terms
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