Top 5 AI tutorials 2025: From AI basics to building agents

From understanding ML to crafting prompts to building with the Model Context Protocol and Goose.

AI moved from abstract concept to practical tool in 2025, but cutting through the noise to actually understand the capabilities and limitations, took some work. These five tutorials form a complete learning path, starting with how AI observes patterns and makes predictions, progressing through the art of prompt engineering, diving into the protocols that let AI talk to your tools, and finishing with open source agents that run in your dev environment. Read them in order or pick up where you need to learn more.

Top 5 AI tutorials of 2025

What is Artificial Intelligence (AI) and the three things it does well

By Ebony Louis

Ever wonder why auto-correct knows what you meant or Face ID recognizes you instantly? AI does three things really well: It observes patterns, predicts outcomes, and adapts from what it learns. This article breaks down how those simple actions power everything from Spotify playlists to fraud detection.

AI vs ML vs DL: A practical guide with real-world engineering examples

By Dhanush Nehru

Confused about AI, machine learning, and deep learning? This guide uses real examples such as spam filters, self-driving cars, and instant credit approvals, to show how these technologies actually work and build on each other. No abstract theory, just practical applications that make the distinctions crystal clear.

What is prompt engineering?

By Mark Hinkle

Treating AI like a search engine leaves results on the table. This article teaches three prompt styles that turn vague outputs into precise content: Zero-shot, few-shot, and many-shot. Learn when to use each, see real examples, and build a prompt library that makes AI actually useful.

Deep dive into the Model Context Protocol

By David Parry

How do AI assistants actually communicate with external tools? This technical deep dive builds the Model Context Protocol from scratch using Java and STDIO. Watch JSON-RPC messages flow through stdin and stdout to see the mechanics that let AI discover tools and execute commands.

Meet Goose: The open source AI agent built for developers

By ATO Team

While chat assistants suggest code fixes, Goose actually implements them by connecting to your IDE and running commands. This open source agent taps into 1,700+ extensions through the Model Context Protocol, turning code generation into genuine automation. It runs locally with your LLM of choice.

---

That’s the path from AI fundamentals to running your own agents. These tutorials build on each other by design, each one adds a layer of understanding that makes the next one make sense. Save this list and work through it step by step as you need to, and you’ll have the foundation to actually build with AI instead of just talking about it, or talking to it.

More from We Love Open Source

• What is Artificial Intelligence (AI) and the three things it does well
• AI vs ML vs DL: A practical guide with real-world engineering examples
• What is prompt engineering?
• Deep dive into the Model Context Protocol
• Meet Goose: The open source AI agent built for developers