AI agents stopped being a promise: today you can delegate real tasks to them like following up on leads, writing emails, searching for information, or managing your calendar. The key is not the chat, but configuring flows where AI acts for you. This guide shows you how to start with concrete examples.

The difference between using a chatbot and delegating to an agent is enormous: the first responds, the second executes. According to McKinsey's State of AI, the organizations that integrate AI into their processes (and not just as a query assistant) are the ones that capture real value. The same applies to your individual work.

What an AI agent is and how it differs from a chat

An agent combines a language model with tools and permissions to act: read your email, write in a spreadsheet, schedule a meeting. Instead of asking you to copy and paste, it does the task end to end. If you want the complete overview, this article explains what AI agents are and how to use them.

Tasks you can already delegate today

• Lead follow-up: an agent can detect new contacts, classify them, and send a first personalized message.

• Email writing: responding to frequent queries with drafts ready to review and send.

• Information search: researching a topic, summarizing sources, and returning a report to you.

• Calendar management: proposing times, coordinating meetings, and sending reminders.

How to build your first flow with Make

Make (formerly Integromat) connects apps without code through "scenarios". A typical flow: when a new form arrives, the scenario sends it to ChatGPT to classify the query, generates a response, and sends it by email. You start by choosing a trigger, add an AI step, and define the final action. For a step-by-step, look at how to automate your tasks with Make.

Best practices when delegating to an agent

Start with repetitive and low-risk tasks. Define clear permissions: what the agent can and can't do. And keep a human in the loop to review results at the beginning. Trust is built with gradual supervision, not all at once. The Verge's AI coverage shows how companies adopt agents gradually.

Recommended Coderhouse course

To go from theory to flows that work, these training programs give you the foundations and the practice:

• Introduction to Artificial Intelligence: the starting point to understand what these models can and can't do.

• AI Automation Course: to build real automations with tools like Make and n8n.

• AI Agents Course: the advanced level to design autonomous agents that execute complex tasks.

Frequently asked questions

Do I need to know how to program to use AI agents?

Not to start. Tools like Make or n8n let you build flows without code. Knowing how to program gives you more control, but it's not an initial requirement.

How reliable are agents for important tasks?

For low-risk tasks they are very useful. In critical tasks it's a good idea to keep human supervision and review the results before they are sent or executed.

How much does it cost to automate my tasks?

Many tools have free plans for low volumes. The cost scales according to the number of operations and the AI model you use.

Where is it a good idea to start?

With a single repetitive task that consumes your time, like classifying queries or scheduling meetings. When that flow works, you scale to more complex processes.