AI Agents Tutorial

An AI agent is an AI system that does not just answer: it takes steps to complete a goal. It can decide to search, read a file, run code, call an app's API or send a message, look at the result, and decide what to do next.

Chatbots answer questions. Agents get tasks done: "Find three cheap flights to Islamabad for next Friday and put them in a table", or "Read these 20 invoices and list the unpaid ones." Models like ChatGPT, Gemini and Claude now power agents that work in browsers, code editors and business tools.

This tutorial explains how agents work, how to build a simple one in Python, and how to keep them safe.

What You Will Learn

• What agents are, and how they differ from chatbots
• Tools and function calling
• The agent loop: plan, act, observe, repeat
• Short-term and long-term memory
• Multi-agent systems
• Building a simple agent in Python
• Risks, limits and human approval

The Idea in a Few Lines

goal = "Find the total of today's orders"
steps = ["read orders file", "add the amounts", "report the total"]
for number, step in enumerate(steps, start=1):
    print(f"Step {number}: {step}")
print("Goal done:", goal)

Step 1: read orders file
Step 2: add the amounts
Step 3: report the total
Goal done: Find the total of today's orders

A real agent decides these steps itself, using an AI model.

Exercises and Quiz

Every lesson ends with an exercise, and the last lesson is a quiz.

Before and After This Tutorial

You should know basic Python (start with Intro to Programming if you are new) and have read the Chatbots Tutorial, which explains calling an AI API. Good Prompt Engineering makes agents much more reliable.