Almost all the major AI labs bet heavily on the same direction: agents. OpenAI launched Tasks and autonomous operators. Anthropic built Claude Projects with action capabilities. Google integrated agents into Workspace. AI agents stopped being a promise to become real tools that marketing, sales, support, and programming teams already use every day. The problem is that most people in LATAM still don't quite know what an "AI agent" is or how to distinguish it from a simple chatbot. This article explains it clearly, with concrete examples and steps to get started.

What an AI agent is (and what it isn't)

An AI agent is a system that can execute tasks autonomously, using external tools, making intermediate decisions, and chaining actions to achieve an objective without the human intervening at each step.

The difference from a conventional chatbot is fundamental:

• A chatbot answers questions. You ask, it responds. The initiative is always the human's.

• An agent receives an objective, plans the necessary steps, and executes them. It can search for information on the internet, read files, send emails, call APIs, and adjust its plan based on the results it obtains.

Concrete example: if you ask ChatGPT "write an email for my client", that is a chatbot responding to your prompt. If you ask "research my client's last 3 projects, identify their recurring problems, and send them a personalized email with a solution proposal", that is an agent executing a workflow with multiple steps and decisions.

OpenAI published the complete vision of agents and their use cases on its blog. Anthropic also documented how to build with Claude Agents in production.

Real examples of agents in different industries

AI agents are already being used in real environments in 2026. These are some of the most common cases:

• Marketing: agents that monitor brand mentions in real time, generate weekly competitor reports, and suggest responses to negative comments on social media.

• Sales: agents that automatically qualify incoming leads, look up prospect information on LinkedIn and the CRM, and draft the first personalized contact email for the salesperson to review and send.

• Customer support: agents that read a user's ticket history, suggest responses based on internal documentation, and escalate the cases that require human decision.

• Programming: agents like Devin or Cursor in agent mode that receive a development task, read the existing code, write the necessary changes, run the tests, and report the result.

• Research and content: agents that generate trend reports, look for sources, synthesize information, and produce drafts of articles or presentations.

How to use agents without knowing how to program

The good news is that you don't need to know how to program to start using AI agents. These are the most accessible platforms to activate them today:

• ChatGPT Tasks (OpenAI): allows you to schedule recurring tasks that ChatGPT executes automatically at the time you define. Example: "Every Monday at 9am, find the 3 most relevant news items in my industry and send them to me by email."

• Claude Projects (Anthropic): allows you to create projects with persistent context, reference documents, and permanent instructions. Claude remembers all the project context and can make decisions based on that information every time you use it.

• Gemini in Google Workspace: integrated directly with Gmail, Docs, and Calendar. It can read your agenda, draft email responses, organize information from your documents, and execute tasks within the Google ecosystem.

For more advanced users who want to connect multiple apps, tools like Make (formerly Integromat), Zapier AI, or n8n allow you to build visual agentic flows that connect hundreds of applications without needing to write code.

Step-by-step use case: a research agent for content teams

Objective: generate a weekly trend report in your industry without having to search for it manually.

1. Create a Project in Claude with the company's context: what it does, who the competitors are, what topics interest it, and in what format you want the report.

2. Ask it: "Every week, find the 5 most relevant news items about [topic], identify what the competition is doing, and put together a one-page report with the most important points for our team."

3. Review the first output, adjust the instructions based on what is missing or excessive, and automate the delivery via Slack or email.

Estimated initial setup time: 30-45 minutes. Time saved per week: between 2 and 3 hours of manual research. Over time, the agent learns the team's preferences and improves the quality of the reports.

If you're interested in exploring this topic further, you can also read how to learn artificial intelligence from scratch.

Recommended Coderhouse courses

To learn to build and use AI agents professionally, the Coderhouse AI Agents Course is the most direct one on the topic: you'll learn to design, configure, and deploy real agents for different enterprise use cases.

If you're just getting started with AI and want a solid conceptual base before diving into agents, the Introduction to Artificial Intelligence Course gives you the framework needed to understand how these systems work. And if your focus is workflow automation with tools like Make or n8n, the AI Automation Course perfectly complements working with agents.

Frequently asked questions

What is the difference between an AI agent and a chatbot?

A chatbot answers questions reactively: you start, it responds. An agent can take actions, use external tools, chain multiple steps, and operate autonomously to achieve an objective without you having to guide it at every moment.

Are AI agents safe to use in companies?

It depends on how they are configured. It is essential to clearly define what permissions the agent has (what it can read, modify, or send), review its actions before giving it full autonomy, and use platforms that offer auditable logs of what the agent does.

Can I build an agent without knowing how to program?

Yes. Tools like ChatGPT Tasks, Claude Projects, and Make allow you to configure agents with visual interfaces or natural language instructions. For more complex cases or custom integrations, basic technical knowledge may be required.

How much does it cost to use AI agents?

It depends on the platform. ChatGPT Plus ($20/month) and Claude Pro ($20/month) include basic agentic capabilities. For more complex automations with Make or n8n, paid plans start from $9 USD/month. API costs for more advanced agents vary depending on the volume of use.

What is the difference between an AI agent and a traditional automation workflow?

A traditional workflow (like basic Zapier) follows predefined steps and cannot adapt if something changes. An agent uses reasoning to decide what to do based on the context, can handle unforeseen situations, and adjust its plan when it encounters an obstacle. It is the difference between a fixed recipe and a cook who improvises.