How To Learn AI Agents: 8 Steps In The Right Order

Q: What is the best way to learn AI agents?

The best way is to learn in order: understand what an agent is, use one ready-made agent for a real task, then add tools, memory, a schedule, skills, more agents and finally your own agent OS. Each step builds on the one before it.

Q: Can I learn AI agents for free?

Yes. Hermes Agent is free and open source, free models exist, and my YouTube courses and the AI Money Lab are free. The Hugging Face AI Agents Course and Microsoft's AI Agents for Beginners are free as well.

How to learn AI agents comes down to eight steps done in order, and the result is one agent that does a real job for you every day without being asked.

Here is the whole path before you scroll.

You understand what an agent is.
You use one ready-made agent for one real task.
You give that agent tools.
You add memory.
You put it on a schedule.
You teach it skills.
You run several agents.
You build your own agent OS.

I'm Julian Goldie, and I run my business on a crew of AI agents inside my own Agent Operating System.

This page is the operator version of the path, so every step has the exact command, a check that tells you when you are done and a free resource.

How To Learn AI Agents: The Path At A Glance

This table is the whole method, and the rest of the page explains each row.

Step	What you do	How you know you are done
1	You learn what an agent is.	You can explain the difference between a chatbot and an agent in one sentence.
2	You install one ready-made agent and give it one task.	The agent finished a real task while you watched.
3	You switch on the tools it needs.	The agent used the web or your files to answer.
4	You give it memory.	A new session already knows who you are.
5	You schedule one job.	A result arrived without you opening the app.
6	You teach it one skill.	You stopped repeating the same instructions.
7	You add a second agent.	Two profiles hold different jobs and different memory.
8	You put everything behind one dashboard.	You start your day from one screen.

Most people fail because they start at step seven.

They watch a video about ten agents working as a team, try to copy it and quit on day three.

The order is the lesson, so please do not skip ahead.

Step 1: Understand What An AI Agent Is

A chatbot answers you, and an agent does the work.

Anthropic's engineering guide gives the cleanest definition I have found.

It says agents are systems where the model dynamically directs its own process and tool usage.

It contrasts that with workflows, where the model and the tools follow predefined code paths.

In plain words, an agent has a brain, which is the model, and hands, which are the tools.

It also runs in a loop, so it looks at the result of each action and decides what to do next.

That same guide recommends finding the simplest solution possible and only adding complexity when you need it.

I agree with that, and it is the reason this path starts with one agent and one job.

Your free resource for this step is Anthropic's Building Effective AI Agents article.

You are done when you can explain the idea to a friend without using the word "autonomous".

Step 2: Use One Ready-Made Agent For A Real Task

You learn agents by running one, so this is the most important step on the page.

I start people on Hermes Agent, which is a free, open-source agent from Nous Research.

You can download Hermes Desktop from the Hermes website and install it like any other app.

You can also install it from a terminal with the command in the official docs.

curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash

Then you run hermes setup --portal, which logs you in to Nous Portal and lets you pick a model.

Some models there are marked free, so check the label before you confirm.

Free models get rate limited at busy times, so I add a second one with hermes fallback add.

If anything looks broken, hermes doctor is a built-in health check that explains the problem in plain words.

Now give the agent one real task from your own week.

A good first task is to ask it to read a folder of your notes and write a one-page summary.

Do not configure everything on day one.

Get one task finished, watch how the agent plans and acts, and then close the laptop.

My best Hermes Agent setup guide has the full install walkthrough with every option.

Step 3: Give Your Agent Tools

An agent without tools can only talk, so the third step is to check which tools are switched on.

You run hermes tools, and it lists every toolset as enabled or disabled.

When I ran it on my own install, version 0.21.4 listed 26 built-in toolsets with 20 switched on.

Terminal, files, web and scheduling are already on in a default install.

You switch one on with a command such as hermes tools enable browser.

You switch one off the same way, and I'd turn off anything you do not use.

The first mistake in my Hermes crash course is adding too many tools too soon.

Add one tool, test it on a real task and only then add the next.

Outside apps connect through MCP, which stands for Model Context Protocol.

The official MCP site describes it as an open-source standard for connecting AI applications to external systems.

In Hermes you run hermes mcp catalog to see what is available and hermes mcp install to add one.

Your free resources are my best Hermes Agent tools list and the official MCP introduction.

You are done when the agent has answered a question using fresh information from the web or from your own files.

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Step 4: Add Memory So It Stops Forgetting You

A normal chatbot resets to zero every day, and memory is what fixes that.

Hermes ships with a small built-in memory that persists between sessions.

The official docs describe two files, which are MEMORY.md for the agent's own notes and USER.md for your profile.

They are limited to 2,200 and 1,375 characters, so they hold only the facts that matter in every prompt.

Every past session is also stored in a local database that the agent can search.

On top of that, I add a notes vault, and I use the free Obsidian app for mine.

Three notes get you started, which are an about-me note, a decisions log and a daily log.

Then you add one rule, which is that the agent reads before it works and writes before it leaves.

Give the agent the real folder path and not the words "this folder".

I made that exact mistake while filming, and the agent built the folders in its own workspace instead.

The full method is in my best Hermes Agent memory guide.

You are done when you open a brand new session and the agent already knows what you sell and how you write.

Step 5: Schedule It So It Works Without You

A scheduled job is a prompt that runs on a timetable and delivers the result to you.

This is the step where an agent starts to feel like an employee and stops feeling like a chat window.

Here is a real example from my use cases guide.

hermes cron create "0 6 * * *" "Read my task list and send me a short to-do recap" --name "Daily 6AM To-Do Recap" --deliver telegram

The schedule also accepts plain forms such as every 2h, so you do not have to learn cron syntax.

You see your jobs with hermes cron list.

The hermes pause command is an emergency stop, and hermes resume lifts it.

A scheduled job that calls a model uses tokens on every run, so start with one or two.

Another mistake from my crash course is turning every idea into a scheduled job.

You are done when a useful result reaches you tomorrow morning and you did nothing to trigger it.

Step 6: Teach It Skills

A skill is a reusable instruction pack that the agent loads only when a job needs it.

In Hermes, each skill is a folder with a file called SKILL.md that holds the steps, the commands and the pitfalls for one kind of job.

You see what is installed with hermes skills list.

You find more with hermes skills search, and you read one before installing it with hermes skills inspect.

Every installed skill becomes a slash command in chat.

The part I like most is that you can correct the agent once and have that correction saved as a recipe.

Hermes also has a /learn command that turns a guide or a book into a skill, and I show a real one in my Book Brain Engine guide.

My best Hermes Agent skills list ranks the ones I use daily.

If you want a structured course on this idea, DeepLearning.AI lists a short course called Agent Skills with Anthropic.

You are done when a job you used to explain every time now runs from one short command.

Step 7: Run Several Agents

Only now do you add a second agent, and you add it because one agent has too many jobs.

In Hermes, you create separate agents with profiles.

You run hermes profile create research and hermes profile create builder.

Each profile has its own memory, its own skills and its own model.

That is the rule I teach, which is one profile for one job and one model.

Subagents are the second way to spread work, because one agent can split a job across several child agents.

The third way is a ticket board, which you create with hermes kanban boards create my-builds.

Bigger jobs become tickets, and a worker picks each one up.

In my Hermes Command Desk guide, three tickets were finished without me, which were a landing page, a content kanban app and an analytics dashboard.

Two warnings from my crash course belong here.

The first is having five profiles and zero workflows.

The second is trusting subagents without checking their work.

You are done when two profiles do two different jobs and neither one confuses the other's notes.

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Step 8: Build Your Own Agent OS

An agent OS is one dashboard where all your agents live, share one memory and pick up work from one board.

It has three pieces, which are a dashboard, a shared memory and a task board.

You have already built two of them by this point, because the vault from step four is the memory and the board from step seven is the task list.

The easy version of the dashboard is hermes dashboard, which opens a web dashboard on your own machine.

The full version is one you build yourself by describing it to a coding agent, reviewing what it made and saying what to change.

My AI Agent OS guide gives the exact prompts in the exact order.

My free video course on it is below.

You are done when you begin your working day from one screen instead of a pile of tabs.

Your 4-Week Plan To Learn AI Agents

This is a plan and not a promise, so stretch any week that needs more time.

Week	Steps	What you do	What you finish with
1	1 and 2	You read the Anthropic guide, install Hermes and run one real task a day.	One agent you trust with a small job.
2	3 and 4	You check your tools, add one new one and set up the notes vault.	An agent that can fetch facts and remembers you.
3	5 and 6	You schedule one morning job and save one correction as a skill.	One job that runs daily without you.
4	7 and 8	You create a second profile, open a ticket board and open the dashboard.	A small agent OS you can grow.

I'd spend most of each session doing and very little of it watching.

One finished job every week beats ten tutorials.

A Free Resource For Every Step

I checked every outside resource below on its own page on 13 October 2026.

I have not taken the outside courses myself, so I am describing them from what their pages say.

Step	My resource	Free outside resource
1	Hermes crash course	Anthropic: Building Effective AI Agents
2	The two-hour Hermes video at the top of this page	Hermes Agent official docs
3	Best Hermes Agent tools	Hugging Face MCP Course, which the page calls free and built in partnership with Anthropic
4	Hermes second brain guide	Hermes memory docs
5	Best Hermes Agent use cases	Hermes scheduled tasks docs
6	Best Hermes Agent skills	Hermes skills docs
7	Hermes Command Desk guide	Microsoft AI Agents for Beginners, which includes a lesson on the multi-agent design pattern
8	AI Agent OS guide	LangChain Academy, which says its course content is always free

Two broader courses cover the theory behind the whole path.

The Hugging Face AI Agents Course describes itself as a free course that takes you from beginner to expert, with a free certification process.

The Agentic AI course from DeepLearning.AI is taught by Andrew Ng and covers reflection, tool use, planning and multi-agent workflows.

Its page says you can audit it for free, and it asks for intermediate Python skills.

My free community is the AI Money Lab, which includes a free AI course and 1,000 AI agents.

How Long Does It Realistically Take To Learn AI Agents?

The honest answer is that it depends, and I will not invent a number for you.

Here is what I can point to.

The Hermes install is one copy-paste command, so a first working agent can exist the same day.
My memory guide says the notes vault takes about an afternoon to set up properly.
Hugging Face says each chapter of its agents course is designed to be completed in one week, with roughly three to four hours of work a week.
Anthropic's Claude Academy lists its courses with lengths from 45 minutes to 4 hours.

Those are the only timings I can source.

How long it takes to become good depends on how many hours you give it and whether you have a real job for the agent to do.

People with a real job to automate learn faster, because every session has a point.

Seven Mistakes That Slow You Down

These come straight from my Hermes crash course, and I have made most of them.

You add too many tools too soon.
You save everything to memory, so the important facts get buried.
You put a weak model on hard work and then blame the agent.
You turn every idea into a scheduled job.
You trust subagents without checking what they produced.
You create five profiles and have zero finished workflows.
You treat the agent like magic, when it only compounds if you feed it well.

The fix for all seven is the same, which is to finish one job before you start the next.

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Also On Our Network

FAQ: How To Learn AI Agents

What is the best way to learn AI agents?

The best way is to learn in order.

You understand what an agent is, use one ready-made agent for a real task, and then add tools, memory, a schedule, skills, more agents and finally your own agent OS.

Do I need to know how to code to learn AI agents?

You do not need to code to use and run agents.

The steps on this page use copy-paste commands and plain English prompts.

You do need Python if you want to build agents from scratch with frameworks.

How long does it take to learn AI agents?

It depends on your hours and on whether you have a real job for the agent.

Hugging Face says each chapter of its agents course is designed for one week at about three to four hours a week.

Nobody can honestly promise you a date for mastery.

Can I learn AI agents for free?

Yes, you can.

Hermes Agent is free and open source, free models exist, and my YouTube courses and the AI Money Lab are free.

The Hugging Face AI Agents Course and Microsoft's AI Agents for Beginners are free as well.

Which AI agent should a beginner start with?

I start people on Hermes Agent, because it is free, open source and installs with one command.

The steps work with other agents too, so use one you already have if you prefer.

What should I build first when learning AI agents?

Build one small job you already do every week, such as a morning to-do recap or a summary of a folder of notes.

One agent doing one job teaches you more than ten half-built projects.

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About Julian

I'm Julian Goldie, an SEO entrepreneur, author and founder of the AI Profit Boardroom, which has 3,400+ members.

I help business owners scale with AI agents, automation and SEO.

I started Goldie Agency on my own, and it is now a 7-figure SEO and link-building agency with 70+ people.
I've grown my YouTube channel to 400,000+ subscribers.
I wrote "Link Building Mastery".
My Udemy courses have taught 29,000+ students.

→ Get my best AI training inside the AI Profit Boardroom

Start step two today with one agent and one job, and you will already be further along than most people who ask how to learn AI agents.