Course

Agents & Tools

A chatbot writes; an agent acts. This course walks you from one to the other: how a tool gives the model real hands, how MCP is the one shared port that connects any tool to any app, how an agent loops think-act-observe toward a goal, the five workflow patterns you can actually trust, the LLM-as-operating-system picture that ties it together, and the permissions and human checkpoints that keep a capable agent safe. Beginner-friendly, drawn scenes, no code required.

7 lessonsBeginner42 min

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Course lessons

Tools turn talkers into doers

On its own the model just talks. Give it a tool and it can actually do things — send mail, read a file, add an event.

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One port for every tool

Before, every app needed a custom hookup to every tool — a tangle. MCP gives all of them one shared port.

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The agent loop

An agent doesn't answer once. Give it a goal and it loops — think, act, observe — adjusting until it's done.

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Workflows you can trust

A free-roaming agent is powerful but unpredictable. Five fixed patterns give you reliable, repeatable results.

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The LLM as an operating system

Picture the model as the CPU of a new kind of computer — with the context window as its RAM and tools as peripherals.

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Keeping agents on a leash

An agent that acts on its own can be wrong on its own. Permissions and a human checkpoint keep risky actions safe.

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Putting it together

A quick recap of how AI stops being a talker and becomes a doer — and a check to lock it in.

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