Prompt. Build. Ship.:: AI for Web Devs Build x3 Times Faster

Hey there, and welcome to Module One!

In this module, we’re going to go over a few key things.

First, you’ll get a quick overview of what you’re going to learn in this course—the full program.

Then, we’ll talk about how this course can support you on your journey to becoming a web developer.

After that, we’ll go over who this course is designed for.

We’ll also take a moment to introduce your instructor—just so you know who’s guiding you.

And finally, we’ll cover the tools and tech stack you’ll need to successfully complete the course.

Lesson 1.

What you’ll learn

Hey my friend, and welcome to Lesson One!

In this lesson, we’ll talk about what you’re going to learn throughout this course.

We’ll kick things off with Module Two, where we’ll cover the foundations. That includes what general AI is, how it works, and how to structure your prompts effectively. We’ll take a closer look at popular general-purpose AI tools like ChatGPT and Claude, and we’ll go over the four main ways you can interact with AI.

In Module Three, we’ll dive deeper into the web development process—specifically, how general AI fits into coding. We’ll review code generation tools, explore the strengths and limitations of using AI for coding, and talk about different tools used in modern web development.

Then, in Module Four, we’ll go over five ways AI can support you in your coding journey, and we’ll break each one down in detail.

In Module Five, we’ll talk about the two speeds of code generation and how to choose the one that works best for you.

Next, Module Six will be all about hands-on practice. We’ll build a real project using AI and follow a typical web development workflow.

Finally, in Module Seven, you and I will tackle two coding challenges together. You’ll build real projects, and of course, I’ll walk you through the solutions.

Lesson 2.

How this course will help youHow will this course actually help you?

In short, you’ll learn how to build and launch your websites and web apps faster.

I’ll show you real examples of how to boost your productivity with AI—whether it's generating code, debugging, fixing errors, refactoring, or following best practices.

You’ll also learn how to cut down on repetitive tasks, which can save you a lot of time.

And in the last two modules, we’ll walk through the full app-building process, where you’ll see exactly how to create web apps with the help of AI.

Lesson 3.

Who this course is for

So, who is this course for?

We’ll keep it simple—there are two main groups of professionals this course is designed for.

First, web developers of all skill levels. Why web developers? Because the examples we’ll use throughout the course are based on HTML, CSS, and JavaScript. That makes the content more visual and familiar if you’re already working in web development.

The second group is developers from other backgrounds—like mobile developers, software engineers, or anyone coding in different languages. It doesn’t really matter what language you use, because the core principles of working with AI are language-agnostic.

That means everything you learn here can still be applied, no matter what your tech stack looks like.

Lesson 4.

Who is your teacher

Let me quickly introduce myself.

My name is Ilyas Seisov. I’m a web developer, and these days I help businesses and entrepreneurs bring their ideas to life through design and code.

My main tech stack is React and Next.js. I earned my Bachelor’s degree in Computer Science in 2014 and completed my Master’s in 2016. I’ve been working in the web development industry since then.

In my free time, I enjoy mentoring and teaching—especially around AI for coding, web development, and web design.

If you’d like to check out my latest work, head over to my website at ilyasseisov.com. You can also connect with me on LinkedIn.

Lesson 5.

What tools you need for this course and tech stack

Let’s quickly go over the tools and tech stack you’ll need for this course.

First, you’ll need a code editor. You can use anyone you like, but I personally recommend VS Code—it’s the most popular choice among developers and works great for what we’ll be doing.

Second, let’s talk about the tech stack. You should have a basic understanding of HTML, CSS, and JavaScript. That said, it’s not strictly required to know these specific technologies. Since we’ll mostly be focusing on the fundamentals of using AI in coding, you’ll still be able to follow along even if your background is in another language.

Hello, and welcome to Module Two!

In this module, we’ll explore the following topics:

We’ll start with the basics of general AI and how it actually works.

Then, we’ll dive into some of the most popular general-purpose AI tools, and we’ll break each one down in detail.

Next, we’ll look at the four main ways to interact with AI.

And finally, we’ll wrap up with an introduction to prompt architecture—how to structure your prompts effectively.

Alright, let’s jump in and get started!

Lesson 1.

What is Generative AI and how it works

Hello and welcome to Lesson One!

In this lesson, we’re going to talk about how generative AI actually works—specifically, text-based generative AI. Why text-based? Because code is essentially just text.

Let me show you a couple of slides from Google’s official explanation. According to Google, generative language models learn patterns in language by being trained on huge amounts of text data—think terabytes of it. Engineers feed this massive data into the system, and the AI learns from it.

Here’s the key point: the responses you get from a generative AI model aren’t calculated using fixed formulas—they’re predicted based on patterns the model has seen during training.

Let me say that again: it’s prediction, not exact calculation.

For example, take this sentence:

“I’m making a sandwich with peanut butter and…”

The AI might continue it with words like jelly, jam, banana, and so on. Each time you run that prompt, you might get a slightly different answer. That’s prediction in action.

Here’s another example. I asked ChatGPT to list different ways someone could respond to “Hello.” It gave me a variety of options—casual, friendly, formal, funny, energetic, sarcastic, short, and more.

So, when you prompt a language model with “Hello,” you could get any one of these variations, depending on the context and randomness involved.

Again, this shows that it's not about calculating the "right" answer, but about predicting a plausible one.

So why is this important to understand?

Because later on, as you gain more experience, you might want to build your own generative AI model trained on a custom dataset.

Why would you do that? Maybe you’re building a chatbot for a company or creating a code generation tool for specific technologies—like Nuxt.js, Next.js, or even C++—where you need precise, domain-specific responses.

To make that happen, you’d train your AI model on relevant material—documentation, books, and example code related to your specific domain.

So yeah, understanding this foundation is key if you want to go deeper in the future.

Lesson 2.

Popular general-purpose AIs

Hello, and welcome to Lesson Two!

In this lesson, we’re going to explore some popular general-purpose AIs. By "general-purpose," I mean AIs that can handle a wide variety of tasks, not just coding.

The first and most famous one is ChatGPT. It was probably the first AI model of its kind to hit the market, which is why it's so well-known. So, here we are inside ChatGPT.

In the center, we usually have the input field where we enter our prompts, along with some additional features like uploading files, searching the web, and using reasoning models for more advanced tasks. You can even use voice mode for voice recognition.

Let’s try something with ChatGPT. We’ll ask it to generate a basic HTML boilerplate.

As you can see, it successfully completes the task, and now we have a basic HTML structure that we can copy if needed. It also often includes helpful comments for better understanding.

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