How 4Geeks Academy Embeds AI Throughout Its Coding Bootcamp Curriculum

Alejandro Sanchez is the co-founder of 4Geeks Academy, who has been revolutionizing coding education since he was a teenager, building interactive websites at 13. From co-founding startups by 16 to scaling 4Geeks Academy into a global coding school with over 2,500 graduates across the US, Latin America, and Europe, Alejandro is now pioneering the next evolution in coding education by embedding AI throughout 4Geeks' full-stack curriculum and adopting an AI-first approach across their entire technology stack. We'll hear about how AI is transforming coding education, why he's rebuilding 4Geeks' technology using AI-generated code, and the academy's strategic plans for incorporating AI into 2026.

Tell us your role and how you support students at 4Geeks Academy. 

I’m the Co-Founder and Managing Director of 4Geeks Academy. My role is to make sure our students don’t just learn to code, but actually build the skills and confidence to land jobs in tech. I’m constantly improving our platform and incorporating new innovations, most recently AI. That includes developing features like our AI mentor, Rigobot, and LearnPack, our interactive learning environment, which make the learning process smoother and more effective. Beyond the tech side, I also stay close to the student experience by joining mentorships and helping to create a strong community where support goes beyond the classroom.

Give our readers a high-level overview of how AI is incorporated into the curriculum and teaching approach at 4Geeks Academy. 

AI is part of how we teach and how students learn. Rigobot, our 24/7 AI mentor, provides personalized, real-time guidance across our platform and LearnPack, tracking progress and offering hints without spoiling answers (Socratic method). He can understand what you’re working on, read the articles or lessons you’re looking at, and even remember past interactions to give you more personalized guidance. Beyond that, we’re incorporating AI directly into our bootcamps. The most recent example is our Full-Stack Development with AI program, and more AI-powered programs are on the way. The focus isn’t just to teach students to ‘use’ AI, but to prepare them to be professionals who work with AI, not professionals who risk being replaced by it. That’s a critical difference. We want our grads to walk into the job market ready for how tech teams are actually building today and in the future.

Why is now the right time for beginners and career changers to learn AI?

Now is the ideal time for beginners and career changers to learn AI because we’re at a turning point. The world is shifting from before AI to a future where it’s part of everything. It’s still fresh, but moving fast, so starting now lets you grow with this change and stay ahead in a job market that’s rapidly embracing AI. It’s about learning skills that match where the world’s going.

There’s been a lot of noise in the media about AI replacing junior developers. What are you seeing on the ground? And how can learning AI tools help early-career technologists stand out and stay relevant?

The fear of AI replacing junior developers is overstated. AI is automating some tasks, but it’s not about replacing developers; it’s about working smarter. By mastering AI tools, early-career technologists can stand out, solving problems faster and more creatively. The focus should be on collaborating with AI, not fearing it, to stay relevant in a job market that values adaptability and innovation. Training to integrate AI into workflows prepares developers for how tech teams build now and in the future.

If I’m in the Fullstack Development with AI bootcamp, how might I encounter AI in the curriculum or use AI tools during my studies?

From day one, everything in the program is built around generative AI. Other bootcamps or institutions will tell you that you first have to learn programming without AI and only later, once you understand the fundamentals, start using it. We believe it should be the opposite: you should learn the fundamentals while using AI, because that’s how the world works now and that’s exactly what our method allows.

For example, in the old curriculum, your first assignment was to build a simple “postcard” layout with HTML and CSS to learn the basics of flexbox. In the new AI-powered curriculum, you’ll ask the AI to generate that same layout for you.

The goal isn’t just to see if you can type out syntax anymore; instead, we’re training you to read, interpret, and understand AI-generated code. That means recognizing patterns, understanding how layouts are structured, and solidifying the architectural concepts behind HTML and CSS.

Since reading doesn’t lock in knowledge as deeply as writing, each single writing exercise from the old curriculum has now become multiple reading and analysis exercises in the new one. This shift builds a skill that’s now essential for any junior developer: quickly understanding other people’s (or AI’s) code.

And here’s the biggest change: our way of evaluating your knowledge no longer depends on whether you wrote the code line by line. We don’t test syntax. Instead, we’ve built interactive evaluation mechanisms, such as role-playing, guided conversations, Q&A, etc. that let us measure how deeply you understand the fundamentals.

In short, you’ll still master the same fundamental concepts, but instead of memorizing syntax, you’ll learn to collaborate with AI, detect patterns, and think like a professional developer from day one.

How many weeks of your bootcamp programs are specifically dedicated to AI?

All of it. From day one, our entire program is built around AI. Every lesson, project, and evaluation integrates generative AI tools so you learn the fundamentals while collaborating with AI, just like you’ll do in the real world.

Tell us about Rigobot - how does it work in practice when a student is struggling or needs help? How is it better than ChatGPT for 4Geeks students? 

Rigobot isn’t just another AI like ChatGPT; it’s an AI mentor built specifically for 4Geeks students. While ChatGPT can answer almost anything, it doesn’t know what you’re studying, where you’re stuck, or how you’ve progressed. Rigobot does, because it’s embedded in the 4Geeks curriculum. Rigobot sees the exact lesson, project, or exercise you’re working on. It uses evaluation algorithms to guide you with context-aware hints, never giving away the solution, but nudging you in the right direction. It remembers your history, adapts to your pace, and measures your growth.

Another big difference is prompting. To get the best out of ChatGPT, you need to know how to craft a strong prompt, and most students don’t start with that skill. Rigobot removes that barrier. You can literally type “help me” and it immediately understands your context, what you’re working on, and how to guide you.

Where ChatGPT might give you a confident but misleading response, Rigobot is bounded by the 4Geeks learning framework, ensuring accuracy and alignment with what you need to learn. That’s the difference: ChatGPT is a generalist, Rigobot is a specialized teaching system designed to help you think and grow like a developer.

What's been the most surprising way students have used Rigobot that you didn't initially anticipate?

Honestly, the biggest surprise has been seeing students use Rigobot as emotional support. We expected them to ask for coding help or solutions, things like “how do I fix this bug?” or “show me the right approach.” But some students actually open up to Rigobot about their frustrations: “I feel stuck,” “I don’t know if I can keep going,” “Can you help me figure out how to keep learning?”

That emotional dimension was unexpected, but it shows how much students value having a 24/7 presence they can turn to, not just for technical answers, but also for encouragement when they feel blocked.

We’ve also seen curiosity from more advanced students who ask Rigobot about how it was built, how it exchanges messages, how it’s configured, and how the AI itself works, almost using it as a window into AI engineering while learning to code.

How are instructors and mentors supporting students in understanding how to implement AI in their workflow?

In many ways, the support looks the same as it always has. A mentor’s job is to understand the student’s project and guide them in applying the right tools to bring it to life. Conceptually, nothing has changed; it’s the same process as when we used to help students integrate APIs, work with sockets, or adopt a new technology.

The only difference is that now the “new technology” happens to be AI. Instructors still walk students through the same steps: understanding the project, clarifying the problem, and showing how to implement the right tools. The framework of mentorship hasn’t changed — the tools have.

How do you balance AI in teaching with ensuring students learn to problem-solve independently? 

We don’t see AI as replacing problem-solving, we see it as reshaping what problem-solving means. In the past, students spent most of their time memorizing syntax or getting stuck on small errors. Today, AI can generate working code instantly, but the real challenge is understanding, analyzing, and adapting that code. So instead of measuring how fast a student can type out a function, we focus on whether they can read AI-generated solutions, detect patterns, and decide how to apply or improve them. That’s the new independence: knowing when to trust the AI, when to question it, and how to adjust it to fit the project.

Mentors still play the same role they always have, guiding students through the process, asking the right questions, and pushing them to think critically. AI doesn’t remove the need to problem-solve; it raises the bar. Our students learn to solve problems not by fighting with syntax, but by orchestrating tools, making decisions, and owning the outcome.

How are you helping students not just use AI tools but also understand the logic and ethics behind them?

We’ve never believed that “using AI” is enough. What matters is that our students understand the logic driving those tools and the responsibility that comes with them. That’s why our programs don’t stop at showing you how to prompt an AI or generate code, we push you to read, analyze, and critique what the AI produces. You learn to detect patterns, evaluate accuracy, and make decisions based on real fundamentals.

On the ethics side, we treat it the same way we’ve always treated technology: as something that can empower or harm, depending on how you use it. Students explore issues like bias in data, ownership of AI-generated work, and the impact automation has on careers. The point is to graduate people who don’t just know how to orchestrate AI, but who also know why and when to apply it responsibly. 

Are 4Geeks grads now working with AI on the job? Could you brag about some alumni working in AI/ML today?  

Yes, several of our graduates are now working directly with AI and Machine Learning. For example, one of our alumni is an Automation Engineer at Cognizant, where leveraging AI tools has become central to his daily work. Beyond those in AI/ML-specific roles, many of our graduates are applying AI in their jobs as part of business-as-usual tasks, which has quickly become the new standard across industries. Even when they’re not building AI systems themselves, our graduates benefit from being AI-literate, which gives them a strong competitive edge in the workplace.

Where do you see coding education heading in the next 3-5 years, and how is 4Geeks preparing for that future?

At 4Geeks, we’re not aiming to graduate “programmers” anymore, we’re preparing the people who will replace programmers. The profession itself is shifting: in the near future, the real role won’t be writing every line of code, but orchestrating AI systems. That requires something deeper than just syntax, it means mastering the fundamental and architectural concepts of technology so you can guide AI effectively.

Paradoxically, to replace a programmer you have to be even more of a programmer. An AI orchestrator needs to understand the underlying logic, patterns, and structures at a very high level, because if the AI fails or generates something flawed, only someone with strong fundamentals can recognize and fix it. That’s why we’re evolving our curriculum and transforming Rigobot into a true AI teaching agent. Today, Rigobot supports the professor. In the future, the model flips: the AI will deliver the core instruction, and mentors will step in to support the AI, keeping the human side alive while scaling teaching through automation.

This is the challenge and the opportunity of the next 3–5 years: building an education system where students learn to orchestrate AI, not just use it, while ensuring the human connection in learning never disappears.

Find out more and read 4Geeks Academy on Course Report. This article was produced by the Course Report team in partnership with 4Geeks Academy.