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The short answer
An AI agent is a system that can take steps toward a goal instead of only answering a question: it decides what to do next, uses tools or software, checks the result and carries on. It suits jobs with several steps, clear tools and defined guardrails, while a simple answer or a normal workflow is often cheaper.
Three things to remember
- 01A chatbot answers and stops, while an agent can plan the next step, use tools and check results.
- 02An agent works by taking a goal, deciding, using tools, checking the result and repeating.
- 03Use an agent for multi-step work with guardrails, not just because the term is popular.
Every slide, in words
- 01
What is an AI agent?
More than a chatbot: a system that can take steps toward a goal
An AI agent is a system that can do more than answer a question.
It can decide what to do next, use tools, and take steps to complete a task.
Goal
Decide
Use tools
Check result
Think: a chatbot talks. An agent can work through a task.
- 02
Agent vs. chatbot
A chatbot responds: an agent can act
Chatbot
Answers questions
Mostly focused on conversation
Usually stops after the reply
Best for simple help or content
Agent
Can plan the next step
Can use tools and workflows
Can check results and continue
Best for multi-step work
Respond
Act
Think: chatbots talk. Agents can do the work around the answer.
- 03
How does an agent work?
Goal → decide → use tools → check → repeat
Goal
Decide
Use tool
Check result
Repeat
The agent starts with a goal.
It decides what to do next.
It can call tools or systems.
It checks the result and continues if needed.
Agents are useful when the job takes more than one step.
- 04
What gives an agent power?
Knowledge + connections + decisions
RAG
Gives the agent the right knowledge and context.
MCP / APIs
Let the agent reach tools, software, and data.
Other models
Help with routing, scoring, or special decisions.
An agent is powerful because it can combine all three.
The agent is the system coordinating the work.
- 05
When should you use an agent?
Use one when the job has multiple steps
Good fit
The work has several steps
Clear tools or systems are available
Rules and guardrails are defined
Checking results adds value
Not every task needs one
A simple answer may be enough
A normal workflow may be cheaper
High-risk actions need strong controls
Some jobs are better as plain automation
Not every AI problem needs an agent.
Use agents for multi-step work, not just because the term is popular.
More in part 6
- 1What is an AI workflow?
- 2What is an AI agent?You are here
- 3Workflow vs. agent: what's the difference?
- 4Chatbot or AI agent on your website: which do you need?Written
- 5What AI is already built into the software you pay for?Written
- 6How AI works with what you already have
- 7What are automation tools like Zapier, Make and n8n, and where does AI fit?Written
- 8What is RPA, and is it still worth it?Written
- 9What is an integration, really?
- 10What is an API?
- 11What is a webhook?
- 12What is tool calling / function calling?
- 13What is structured output / JSON?
- 14What is MCP?
- 15What is an AI harness?
- 16What are AI skills?
- 17What are subagents?
- 18What is computer use?
- 19What is Jev?
Next step
Where does this fit your business?
Six quick questions about your business, then your AI plan: what to start with, what a person still checks, and the lessons that go with it. Or bring it straight to a free thirty-minute call.