Build Your First AI Tool: Simple Automation Projects You Can Create on Your Computer For Free

By Jason Criddle

Build Your First AI Tool

Introduction: Learn How AI and Automation Actually Work

One of the most powerful things about technology is how accessible it has become to everyone. Build Your First AI Tool You no longer need a massive development team, a giant data center, or a venture capital round to create something meaningful. All you need is a computer, an idea, and a willingness to experiment.

At DOMINAIT.ai, our goal is to empower people… not just to use tools, Build Your First AI Tool but to understand them. When you know how things work behind the scenes, you stop feeling limited by what’s been built and you actually start thinking about what you can build.

Today, we’re going to take a hands-on approach. I’m going to show you how to install Python on your Windows computer, open Visual Studio Code (VS Code), Build Your First AI Tool, and build your first little automation script. How about a simple bot that checks your primary email inbox and gives you an overview of what’s inside.

You’ll see firsthand how automation connects the dots between you and AI systems like Ryker. Build Your First AI Tool And by the end of this guide, you’ll have built your first working AI-powered automation on your own computer.

Step 1: Install Python on Windows

Why Python?: Build Your First AI Tool

Python is the most widely used programming language in AI, Build Your First AI Tool automation, and machine learning. It’s simple, readable, and powerful enough to run billion-dollar systems, but easy enough to learn in a weekend of reading.

Here’s How to Get It:

1. Go to the official Python website: python.org/downloads
   
2. Click “Download Python 3.x.x” (choose the latest version).
   
3. Once downloaded, run the installer.
   
4. Important: During installation, check the box that says “Add Python to PATH.”
   
5. Finish installation and open your Command Prompt (CMD).
   

Type the following into the command prompt to confirm it worked:

python –version

6.  If you see a version number (for example, Python 3.12.0), you’re good to go.
   

Step 2: Set Up Visual Studio Code

Now that Python is ready, Build Your First AI Tool let’s set up the workspace where you’ll actually write and run your automation scripts.

Download VS Code: Build Your First AI Tool

1. Visit code.visualstudio.com.
2. Download and install the version for Windows.
3. When it’s installed, open VS Code.

Install the Python Extension:

1. Inside VS Code, click on the Extensions icon on the left sidebar (looks like four squares).
2. Search for “Python.”
3. Click Install on the official Microsoft Python extension.

Now VS Code will automatically detect Python scripts and make your life much easier with autocomplete, Build Your First AI Tool syntax highlighting, and direct run support. Remember folks, this is all free.

Step 3: Create a Folder for Your Project

Let’s organize your work like a real developer.

Create a new folder on your desktop called:
MyFirstAutomation

Open VS Code and click File → Open Folder, Build Your First AI Tool then select MyFirstAutomation.

Inside VS Code, click New File and name it:
email_summary_bot.py

This will be your Python script… Your first real automation file.

Step 4: Install the Required Libraries

Python uses packages to handle different types of work. For this simple bot, we’ll use:

• IMAPClient to connect to your email inbox.
• pyzmail36 to read and parse the emails.

Open a terminal window inside VS Code (Ctrl + ~) and run the following commands:

pip install imapclient

pip install pyzmail36

These commands download and install the tools your bot will need to talk to your email account.

Step 5: Build the Email Summary Bot

Now it’s time to code. Build Your First AI Tool

Below is a universal example that anyone can use. It connects securely to Gmail, checks for unread messages, and prints a quick summary of the newest ones.

⚠️ Note: For Gmail, you’ll need to enable App Passwords (Google > Manage Account > Security > App Passwords). Use the app password instead of your real password for safety.

Here’s the complete code to copy and paste into a terminal on VS Code:

from imapclient import IMAPClient

import pyzmail

# Email account credentials

EMAIL = “your_email@gmail.com”

PASSWORD = “your_app_password”

IMAP_SERVER = “imap.gmail.com”

# Connect to the mail server

with IMAPClient(IMAP_SERVER) as server:

    server.login(EMAIL, PASSWORD)

    server.select_folder(“INBOX”, readonly=True)

    print(“Connected to your email inbox!”)

    # Search for unread messages

    messages = server.search([‘UNSEEN’])

    print(f”You have {len(messages)} unread emails.\n”)

    for msgid, data in server.fetch(messages, [‘ENVELOPE’]).items():

        envelope = data[b’ENVELOPE’]

        subject = envelope.subject.decode()

        sender = envelope.from_[0]

        print(f”From: {sender.mailbox.decode()}@{sender.host.decode()}”)

        print(f”Subject: {subject}”)

        print(“—-“)

What This Does:

• Logs securely into your Gmail inbox.
• Finds any unread messages.
• Prints the sender and subject for each one.

How to Run It:

Inside VS Code’s terminal, type:

python email_summary_bot.py

If everything’s set up correctly, you’ll see output like:

Connected to your email inbox!

You have 3 unread emails.

From: jessica@company.com

Subject: Meeting follow-up

—-

From: support@github.com

Subject: Security alert

—-

From: team@newsletter.ai

Subject: Welcome to our AI weekly digest

—-

Congratulations! You’ve just built your first bot! For free! 

Step 6: Experiment and Customize

Now that your email summary bot is working, try experimenting.

Here are a few ideas:

• Filter by keyword: Add a filter to only show emails with “invoice” or “meeting” in the subject.
• Save summaries to a text file: Instead of printing, write results to a .txt file for later.
• Schedule your bot: Use Windows Task Scheduler to run the script every morning automatically. Look into further instructions online if needed, but I promise you, this stuff is simple.

Every modification teaches you something new about how AI systems like Ryker perform tasks, break goals into processes, manage connections, and interpret data intelligently when you have a basic understanding of it yourself.

Step 7: Understand What’s Happening Behind the Scenes

This exercise might look small, but it mirrors how most modern automation works.

When you run your script, you’ve effectively built a micro AI agent:

1. It connects to a source (your inbox).
2. It analyzes the data (emails).
3. It extracts meaning (subjects and senders).
4. It reports findings in human-readable form.

This is the foundation of AI. It’s simply structured reasoning applied to repetitive, real-world problems.

Now imagine scaling this up across thousands of users, millions of data points, and multiple agents that are each doing specialized tasks, communicating with each other, and optimizing over time. That’s what Ryker does inside DOMINAIT.ai.

Step 8: Keep Learning by Building Small

The secret to understanding automation and AI isn’t learning everything at once. Build Your First AI Tool It’s building one small project after another until you realize how the pieces fit together.

Here are a few more easy ideas you can try next:

1. Folder Organizer: Write a bot that automatically moves files into folders based on their file type.
2. Task Reminder: Create a Python script that sends yourself a text message every morning using Twilio’s free API.
3. Weather Reporter: Pull daily forecasts using a public weather API and email yourself a summary.
4. AI Notes Assistant: Use an open-source large language model locally to summarize your meeting notes.

Each project gives you one more piece of the bigger picture: data → process → automation → intelligence. And then you won’t feel lost when an AI tool is acting wonky. You can troubleshoot it and maybe even fix it yourself.

Step 9: Why This Matters to Us at DOMINAIT.ai

At DOMINAIT, we believe that knowledge is ownership.

When users understand what’s happening behind the curtain, they gain control. That’s the foundation of our philosophy: AI should empower you, not replace you. We aren’t trying to keep everything hidden from you and act like AI gatekeepers like most companies. We want you to build your own AI tools and companies.

That’s why systems like Ryker are built to be explainable, adaptable, and self-learning.. but also teachable. The same way you just taught your computer how to check your emails, Ryker learns new tasks, self-corrects errors, and grows stronger from experience.

The difference is that Ryker operates at a post-AGI level. Reasoning like a human, scaling like an ecosystem, and never relying on third-party models to think for him.

But the core principle is the same: it all starts with understanding how automation works.

Step 10: Final Thoughts: From Small Scripts to Big Systems

You just created a working automation that pulls real data, processes it, and reports results. That’s exactly what happens inside major AI systems, only at a larger scale.

Every AI journey starts here. Not with huge budgets or massive datasets, but with curiosity. Build Your First AI Tool And you did it!

When you build even one tiny bot, you start to see what makes systems like Ryker possible: logic, patience, process, and human vision.

So open VS Code. Try something new. Build Your First AI Tool Experiment with automation. Learn by doing. Get on Reddit and Medium. Find forums where builders are building and start learning everything you can.

Once you understand how the pieces connect, you’ll see the same magic that drives everything we build at DOMINAIT.ai. From the smallest Python script to the most advanced AI brain on Earth.

Jason Criddle
Founder, Jason Criddle & Associates
Architect of DOMINAIT.ai and Ryker