The simple explanation
An agent is not a digital person. It is an arrangement of a model, instructions, information, tools and controls. Its useful question is not ‘Is it autonomous?’ but ‘What may it do, how do we observe it, and when must a person decide?’
Picture it this way
Imagine a new assistant with a clear brief, a limited set of approved tools and a supervisor. The assistant can inspect a situation and choose a next step—but important actions still require permission.
An agent’s decision loop
The meaning remains clear even when motion is turned off.
- 01Receive a goal
- 02Understand available context
- 03Choose an approved tool
- 04Take one action
- 05Observe the result
- 06Continue, ask or stop
What it can do
- Choose among approved tools
- Adapt a sequence to the situation
- Summarize and transform information
- Ask for missing context
- Escalate to a person
What it cannot do
- Guarantee truth
- Know hidden business context
- Accept responsibility
- Safely use unlimited access
- Decide that oversight is unnecessary
Agent, chatbot or traditional automation?
A chatbot mainly responds in conversation. An agent may also use tools and change external state. Traditional automation follows a predefined path; an agent can choose among allowed paths using a model.
An agent is not automatically better than a workflow. If the steps and rules are stable, traditional automation is often cheaper, clearer and safer.
Control is a design choice.
People define permissions, review risky actions, resolve uncertainty, monitor outcomes and remain accountable for the system’s use.
From understanding to a useful system
Automation software helps turn clear work into dependable digital flows. The RPAi Framework adds a structured way to assess value, risk and responsible scale.
See tools and resources →Now you understand the basic idea behind AI agents.
Continue when you are curious—or return to a completely different part of Aurora.
Sources and further reading
Updated 15 July 2026