When people first started talking about problems in coding education, the biggest issue was something called "tutorial hell."
You knew you were stuck in tutorial hell if:
- You followed many tutorials but couldn't build anything by yourself
- You spent more time watching coding videos than actually coding
- You knew a little about many technologies but didn't really understand how they worked
Students would watch long programming videos, follow along step by step, and feel like they understood everything.
But the moment they tried to write code on their own, they got stuck.
They weren't actually learning how to program. They were just copying what they saw.
This was the problem many coding platforms tried to solve.
The Shift to Hands-On Learning
At Sigmaschool, we believe learning to code requires three important things:
Deep fundamentals
Programming basics should not only be taught in universities. Anyone should be able to learn them properly.
Hands-on practice
You need to write code constantly. Not just in big projects, but while learning every concept.
Less passive learning
Watching videos is easy, but it doesn't force you to think. Reading, solving problems, and writing code helps you understand much more deeply.
The New Problem: Vibe Coding
Today, a new version of tutorial hell is starting to appear.
Some people call it "vibe coding." Instead of copying tutorials, people rely heavily on AI tools to generate code.
They describe what they want, the AI writes the code, and things seem to work.
But when something breaks, they don't know how to fix it.
This creates a similar problem: You can produce code, but you don't fully understand how the system works.
Why Fundamentals Matter
Technology changes quickly. New frameworks and tools appear all the time.
If you try to chase every new trend, you will always feel behind. But the core ideas behind programming change much more slowly.
Things like:
- problem solving
- understanding how programs run
- debugging systems
- breaking down complex problems
These are skills that stay useful for decades.
Learning to Think Like an Engineer
The goal of learning programming is not just to make things work.
The real goal is to understand why they work.
When you understand the fundamentals, you can:
- learn new technologies faster
- debug difficult problems
- build larger systems with confidence
That's why Sigmaschool focuses on deep understanding instead of quick shortcuts. It may take longer at first, but it builds skills that last for an entire career.
What Is "Vibe Coding Hell"?
A few years ago, many people learning to code got stuck in something called tutorial hell.
Tutorial hell looked like this:
"I can't build anything without following a tutorial."
"I don't understand the documentation. Is there a video explaining this?"
"To do this simple task, I guess I need a huge framework."
People could follow tutorials step by step, but when it was time to build something on their own, they got stuck.
Today, a new version of this problem is starting to appear. Instead of depending on tutorials, some learners now depend heavily on AI coding tools.
This creates what some people call vibe coding hell.
It sounds like this:
"I can't do anything without AI helping me."
"I built something cool… but it only works on my computer."
"Why did the AI add thousands of lines of code just to solve a small problem?"
Modern learners are not unable to build things. In fact, many are building more projects than ever before.
But sometimes these projects don't actually improve their understanding of how software works.
Instead of learning how systems work, they spend their time:
- fighting bugs caused by AI-generated code
- trying to understand confusing solutions
- relying on tools that hide the real logic behind the code
This can create a situation where someone can generate a lot of code, but still struggles to understand what the program is actually doing.
AI Coding Is Still the Future
That said, AI coding tools are not going away. They are already part of modern software development.
Many developers use AI tools to:
- speed up repetitive tasks
- check their work
- brainstorm solutions
These tools can be helpful when used correctly. But they don't replace the need to understand programming fundamentals.
In fact, developers still need strong problem-solving skills to review, debug, and improve AI-generated code. AI can help you write code faster, but it does not automatically teach you how software works.
The Risk for New Learners
One of the biggest risks today is not AI itself.
It's the mindset that can come with it.
Some learners start thinking: "Why should I learn this? AI can do it for me."
If too many people think this way, we may end up with a generation of workers who rely on tools but lack deep understanding.
This is sometimes called the Dunning–Kruger effect — when people with less knowledge believe they understand more than they actually do.
In the long run, real skill still comes from learning, practicing, and understanding the fundamentals.
AI can help along the way, but it cannot replace the process of learning how to think like an engineer.
Is AI Good for Learning?
Not everyone learning to code today is discouraged. In fact, interest in software development is still very strong.
So a new question appears: Is AI actually good for learning programming?
There are reasons to be optimistic. AI tools can help explain ideas, generate examples, and help developers work faster.
However, there are also some serious problems we need to be aware of.
The "Yes-man" Problem
One issue with AI is that it often tries to agree with you.
Sometimes it doesn't challenge your assumptions. Instead, it responds in a way that sounds helpful and confident, even if the reasoning is incomplete or inconsistent.
If you frame the question in one way, it might conclude that your results are better than expected.
If you frame the same question differently, it might conclude that your results are worse than expected.
Both answers may sound logical and confident, even though they lead to opposite conclusions.
The problem is not that AI is always wrong. The problem is that it often tries to fit its answer to the direction of your question.
This can create a false sense of understanding.
Why This Is Dangerous for Learning
When we learn difficult subjects, we need feedback that challenges us.
In the past, developers would ask questions on forums, in chat rooms, or on sites like Stack Overflow. Sometimes the responses were blunt, but they helped people correct their mistakes.
AI systems behave differently.
Instead of telling you that your thinking might be wrong, they sometimes guide the conversation in a way that feels supportive.
This can make learning feel easier in the short term.
But real learning often requires someone to tell you: "That approach is wrong."
If learners only receive answers that confirm what they already believe, it becomes harder to develop strong reasoning and problem-solving skills.
AI can be a powerful learning tool, but it works best when used alongside critical thinking, experimentation, and real practice.
When AI Is Useful for Learning
Even though AI has some downsides, it can still be an extremely powerful tool for learning when used correctly.
In many ways, it has never been easier to learn programming than it is today.
AI can help students:
- explain confusing concepts
- guide them when they get stuck
- suggest different ways to approach a problem
However, the key is how it is used.
If AI simply gives the answer immediately, it can prevent students from thinking through the problem themselves.
A better approach is when AI helps guide the student step by step, asking questions and encouraging deeper thinking.
This way, AI becomes more like a learning assistant, not just an answer machine.
When used properly, it can help students move forward without removing the thinking process that real learning requires.
How Do You Escape Vibe Coding Hell?
The answer is simple, even if it's not very exciting. It's the same way people escaped tutorial hell.
Stop letting someone else write the code for you.
In tutorial hell, the solution was to stop relying on step-by-step videos and start coding on your own.
In vibe coding hell, the solution is similar. If AI is writing most of the code, you are not actually practicing the skill.
What Not to Do
When you're learning, try to avoid tools that automatically write the code for you.
For example:
- AI auto-complete tools that generate large blocks of code
- "Agent" tools that build projects automatically
- letting AI solve the entire problem before you try it yourself
These tools can be useful for experienced developers, but they can slow down learning for beginners.
What AI Is Good For
AI can still be very helpful if you use it the right way.
Good uses of AI include:
- asking questions about concepts you don't understand
- requesting examples of how something works
- asking the AI to guide you through a problem instead of solving it
A helpful technique is asking the AI to ask you questions instead of giving the answer immediately. This forces you to think through the problem step by step.
You can also ask AI to include links to documentation or sources so you can learn from the original material.
Struggle Is A BIG Part of Learning
Learning programming is sometimes uncomfortable.
You will get stuck. You will feel frustrated. You will spend time debugging things that don't work.
This is normal.
Tutorial hell avoided this discomfort by letting you watch someone else write the code.
Vibe coding hell avoids the discomfort by letting AI write the code.
But real learning happens when you are the one solving the problem. When you struggle with a problem and eventually figure it out, your brain builds stronger mental models of how the system works.
That's how real skill develops.
The Goal
Great developers aren't the ones who rely on tools the most. They are the ones who understand what the code is doing and why it works.
AI can help you along the way. But the most important part of learning still belongs to you:
thinking, experimenting, and solving problems yourself.
Happy coding!