Modern AI Engineering

Lesson 11.1 · 25 min · video lesson

AI Agents: Autonomous Decision-Making Systems

A chatbot can tell you how to book a flight; what does it take for software to actually go and book it?

In short: An AI agent is a program where a language model decides, step by step, which actions to take toward a goal, runs those actions through tools, looks at the results, and repeats until the goal is met. It is built from five parts: a model, instructions, tools, memory, and a loop that ties them together. Agents shine on open-ended, multi-step tasks, but every extra step is another chance to fail, so we add limits, checks and humans where it matters.

What you will learn

  • The Big Picture
  • What is an AI Agent
  • AI Agent vs Plain LLM vs Chatbot
  • The Five Core Parts
  • How an AI Agent Works End to End
  • A Concrete Example: Research Agent
  • Types of AI Agents
  • What AI Agents Can Do Today
  • When to Use an AI Agent
  • Common Failure Modes
  • Quick Summary

In this lesson

  1. The big picture
  2. What is an AI agent?
  3. AI agent vs plain LLM vs chatbot
  4. The five core parts
  5. How an AI agent works end to end
  6. A concrete example: a tiny research agent
  7. Types of AI agents
  8. What AI agents can do today
  9. When to use an AI agent (and when not to)
  10. Common failure modes
  11. Worked example, step by step
  12. Practice: try it yourself

Key terms in this lesson

AI agent
A system where an LLM repeatedly chooses and takes actions through tools, observing results, until a goal is reached.
Tool
A function the agent's program can run on the model's behalf, such as search, a database query or code execution.
Observation
The result of a tool call, fed back to the model as input for its next decision.
Orchestrator
The plain code that runs the loop: calls the model, executes tools, updates memory and enforces limits.
Workflow
A fixed sequence of steps defined by the programmer, where an LLM may do individual steps but does not choose the path.
Autonomy
How much the model, rather than the programmer or user, decides what happens next.

This lesson is part of the Generative AI Engineering and Complete AI Engineer tracks. See plans and pricing to open the full lesson, its video, labs and quiz, or try the free lesson first (free account needed).

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