When AI Writes the Code, Who is the Programmer Now? — Vibe Coding

Imagine you want to build a new application.

In the past, you would open a code editor, choose a framework, start writing files, and then spend hours debugging and making adjustments.

Today, you can start with a single sentence:

I want an expense management app with a login, a dashboard, and charts showing monthly spending.

Then you let the AI start working.

It writes the code.

It creates the files.

It runs the project.

It detects errors.

And it modifies what it wrote.

And you?

Instead of writing every line yourself, you have become the one describing what you want and reviewing what has been built.

This is the essence of Vibe Coding.

But here a question arises that is worth stopping at:

If AI can write the code... what has the programmer's role become?

📌 Save the article from the beginning, because we are not just talking about a new way to write code, but about the change happening in the way software itself is built.

The most important question in the end will not be: Can AI write code?

But rather:

Can you know what should be built, why, and is what was built worth your trust?

What is Vibe Coding, really?

The term Vibe Coding might sound like a new programming method, but it actually describes a larger shift in how the software itself is constructed.

In traditional programming, you think of the solution and then translate it into code.

You decide the Architecture.

You choose the Libraries.

You write the Functions.

You handle errors.

And you test every part.

In Vibe Coding, you start from a different place:

You describe what you want to build, then let the AI handle a large part of converting that description into code.

You might start, for example, with:

I want a simple login page, responsive to mobile, using email and password.

The AI generates the code.

You run it.

You notice you don't like the design.

So you say:

Make the design simpler, and add a clear message when entering wrong data.

It modifies the code.

Then you discover another problem.

You ask to fix it.

Then you add a new Feature.

And so begins a cycle completely different from the way programmers are used to.

The real difference is not that AI writes the code

And here is a very important point.

AI has been able to write code for a while.

So why has Vibe Coding become a different topic?

Because the idea is not:

"AI helps me write code."

But rather:

"I treat AI as the person who executes most of the programming process, and I direct it and review the result."

And this is a fundamental difference.

In the first case, you are still the primary programmer, and the AI helps you.

In the second case, you shift more toward the person who defines requirements, tests the result, and decides what needs to change.

🤯

Vibe Coding doesn't just speed up writing code... it changes what it means to be a programmer.

Here the bigger picture begins to emerge.

Because when you reduce the time you spend writing code, you will find your time shifting to other things:

Thinking about the product.

Defining what should be built.

Testing what was built.

Discovering what is wrong.

And determining what needs to change.

This is why Vibe Coding is not just a faster way to write code.

It is an attempt to change who performs each step in the software construction process.

The question now is not whether AI can write an app...

That has become clear.

The harder question:

What happens when the app starts working, but you don't know exactly how it was built?

From writing code to describing what you want

To understand Vibe Coding better, compare how a programmer worked and how they can work today.

In traditional programming, you start with an idea:

I want an expense management system.

But this idea alone is not enough.

You have to turn it into requirements, then choose the appropriate technologies, then design the database, then build the interface, then write the API, then link the parts together, then test the system and fix errors.

Every step requires technical decisions.

With Vibe Coding, you can start from the same idea, but instead of converting it yourself into hundreds of programming details, you describe to the AI what you want the product to do.

Then it starts converting this description into an implementation.

Traditional Programming

Idea → Requirements → Architecture → Writing Code → Debugging → System Testing → Deployment

Traditional Programming

Vibe Coding

Idea → Describing Requirements → AI Builds → Run and Experience → Feedback → AI Modifies → Testing and Review

Notice the difference.

In the first method, code is the primary medium between your idea and the product.

In the second, description, experience, and review become a larger part of the process, while AI handles a large part of converting the idea into code.

Here one of the most important shifts in Vibe Coding appears:

You no longer always have to know how to write everything... but you must know how to define what should exist.

This does not mean technical knowledge has become worthless.

Quite the opposite.

The easier it becomes to produce code, the more important the ability to evaluate it and understand its implications becomes.

Because in the end, you won't just ask:

Does the app work?

Instead, you will need to ask:

Was it built the right way?

When code becomes just a means

Something important is happening here.

In traditional programming, a lot of time goes into converting an idea into instructions the computer understands.

You know what you want to build, but you have to translate this idea yourself into:

Functions, Components, APIs, Database Queries, State Management, and others.

This part is what makes learning programming take a long time.

But Vibe Coding tries to reduce this distance.

Instead of your primary task being:

How do I write this code?

It becomes:

What do I want to happen?

This is a small change in words, but very large in the way of thinking.

Imagine you want to add a search feature to an app.

A traditional programmer might start thinking:

What is the Endpoint?

How will I handle the State?

Should I use Debouncing?

How will I write the Query?

How will I handle Pagination?

How will I display the Loading State?

How will I handle errors?

In Vibe Coding, you can start from a higher level:

Add a fast search for products, with instant results, a loading state, and a clear message when no results are found.

The AI tries to convert this description into technical details.

Here, the programmer's value becomes more linked to their ability to know the details that should exist in the first place.

💡

When writing code becomes cheaper, knowing what to write becomes more important than knowing how to write it.

But here lies a big trap.

Because if you don't know what you are looking for...

You won't know if the AI chose the right solution.

It might give you code that works.

It might look excellent.

And no error might appear when running the app.

However, the engineering decision behind this code might be poor.

Here the real problem in Vibe Coding begins.

Making AI write code is much easier than knowing if the code it wrote is worth keeping.

The code works... but is it good?

Here begins the problem that doesn't appear in the first experiment.

You might ask the AI to build a login system, it writes the code, you run the app, and you find everything works.

You register an account.

You log in.

You log out.

And you come back again.

Everything looks perfect.

You say to yourself:

We're done.

But what if there is a security flaw that didn't show up in your test?

What if the database query is not optimized?

What if there is a problem that will appear when the number of users becomes 100,000 instead of 100?

What if the AI used an old library or a structure that will make developing the project harder after several months?

Here we reach a fundamental difference:

Making code work is one thing... and building a good program is another.

Imagine you asked the AI:

Add a payment system to the app.

And indeed, it created the payment page and linked it to the API, and everything works in testing.

But did you verify:

• What happens if the connection is cut during payment?
• Can the process be executed twice by mistake?
• Is the amount verified on the server?
• Is sensitive data protected?
• What happens if payment fails after the amount is deducted?
• Can the user manipulate the request?

These are not questions about writing code.

These are questions about software engineering.

Here the value of human experience appears.

⚠️

The most dangerous code AI writes is not the code that contains an Error... but the code that works while you don't know it's wrong.

This is why Vibe Coding does not mean the programmer no longer needs to understand programming.

It might mean the exact opposite.

The easier it becomes to produce code, the more important discovering bad code becomes.

AI can give you the first version within minutes.

But the question it cannot always answer alone is:

Is this the right way to build this system?

Does Vibe Coding kill programming?

Here the real debate begins.

Because the emergence of Vibe Coding made an old question seem more urgent:

If AI can write code, why should I learn programming at all?

The quick answer might be:

Because AI will still need a programmer.

But this answer alone is insufficient.

Because the truth is that part of the work the programmer used to do has already started shifting to AI.

Writing Boilerplate?

It became easier.

Creating Components?

It became faster.

Writing CRUD APIs?

It became faster.

Converting design to interface?

It became easier.

Writing initial tests?

It became faster.

So we cannot say nothing has changed.

It has indeed changed.

But the mistake is to equate programming with writing code.

The programmer does not sell the company the number of lines they can write.

The company doesn't need 10,000 lines of code.

It needs a system that solves a problem.

This is a huge difference.

If AI can write 10,000 lines in an hour, but the system is full of errors...

We gained nothing.

But if a programmer can build the right system using only 1,000 lines, with good Architecture, security, and tests...

This is the real value.

⚔️ What happens to the programmer's role?

The shift can be simplified like this:

Traditional Programming

The programmer was directly responsible for writing code, implementing technical details, searching for the appropriate Syntax, handling errors manually, and building system parts from scratch. A large part of their time went into converting the idea into instructions the computer understands.

With Vibe Coding

The programmer has become more focused on defining requirements, making technical decisions, analyzing problems, directing the AI, and then reviewing and modifying what is built. Instead of focusing on implementing every detail themselves, a larger part of their focus shifts to the final result and the quality of the system being built.

This does not mean the programmer will leave the code entirely.

It means that code might stop being the largest part of the value they provide.

🤯

Vibe Coding does not eliminate the programmer... but it reduces the value of the part of their work that relied on writing code manually.

Here the question becomes more precise:

Will the programmer who only knows how to write code still be enough?

Most likely...

No.

Because the person who only knows Syntax can be largely replaced by AI helping with that skill.

But the person who understands:

Why are we building this system?

How should it work?

What risks exist?

How do we test it?

And what happens when it fails?

There is still very great value in their experience.

In fact, these skills might become more important when producing the code itself becomes easier.

Is Vibe Coding suitable for everyone?

Here we must distinguish between the possibility of using Vibe Coding and the ability to use it well.

Yes, it has become possible for someone without much programming experience to build a simple app using AI.

And this is very important.

Because the barrier to trying a new idea has become much lower.

Someone with an idea for a small project is no longer necessarily forced to learn all the details of programming before seeing the first version of their idea.

They can start, experiment, modify, and learn while building.

But the problem begins when moving from:

I want to try an idea

to:

I want to build a real system people depend on.

Here the story is completely different.

Imagine someone built a complete e-commerce store using Vibe Coding.

The interface works.

Products appear.

The cart works.

And login works.

The project might look successful.

But what happens when they need to change the way prices are calculated?

Or when a Bug appears that they cannot reproduce?

Or when two libraries conflict?

Or when they discover the database design is unsuitable?

Here it won't be enough to say to the AI:

Fix this

Because you first need to understand the problem itself.

This is the difference between using Vibe Coding as a tool that helps you build...

And using it as a complete substitute for understanding what you are building.

💡

Vibe Coding lowered the starting cost in programming, but it did not eliminate the cost of understanding.

In fact, it might have made understanding more important.

Because the person who understands what is happening can use AI as a massive lever.

As for the person who doesn't understand what's happening, they might be able to build something quickly...

But they might not know why it works, when it will stop working, and how to fix it when it fails.

When is Vibe Coding an excellent idea... and when does it become a risk?

Vibe Coding is not a suitable alternative for every type of software.

In some cases, it can be one of the fastest ways to get from an idea to a working model.

Want to build a Prototype?

Excellent.

Want to try an idea before investing significant time and money?

Excellent.

Want to create a Landing Page or a simple internal tool or a personal project?

Here the speed provided by Vibe Coding can be a huge advantage.

Instead of spending days setting up the project and writing repetitive parts, you can reach an initial version in a short time, then start testing the idea itself.

This is a very important point:

Sometimes you don't need perfect code... you first need to know if the idea is worth building.

But the picture changes when the program is responsible for sensitive things.

A system that handles payments.

An app that stores personal data.

A medical system.

A financial platform.

An Authentication system.

Or any program where a small error might lead to loss of money, data leakage, or service disruption.

Here it is not enough to say:

"The app works."

Rather, you must know how it works, why it works, and what could happen when someone tries to use it in a way you didn't expect.

⚔️ The Simple Rule

The higher the cost of error, the less you can rely on Vibe Coding without real engineering review.

If you are building a small tool for yourself, speed can be more important than perfection.

But if you are building a system thousands of users will depend on, Architecture, security, testing, and review are not things that can be left to chance.

Here the best way to deal with Vibe Coding appears:

Don't use it instead of software engineering.

Use it to speed up software engineering.

And that is a big difference.

How to use Vibe Coding correctly?

The difference between someone using Vibe Coding to build something real, and someone who just clicks on the AI and takes the first result, is not in the tool they use.

The difference is in the way of working.

The biggest mistake is to give the AI a huge idea and ask it to build the entire project at once.

For example:

"Build me a complete e-commerce store with login, payment, dashboard, notifications, and a shipping system."

You might indeed get a project that works.

But the larger the task, the harder it becomes to know what happened inside it, and discovering and fixing errors becomes more complex.

The best way is to handle the project in stages.

Start with the goal.

Then ask the AI to set a plan.

After that, build one Feature.

Run it.

Test it.

Review the code.

Then move to the next Feature.

In this way, you don't let the AI build the project instead of you...

Rather, you make it build it with you step by step.

📊 A simple workflow for Vibe Coding

🎯 Goal → 📝 Plan → 🤖 AI Builds → ▶️ Run and Experience → 🔍 Review → 🐛 Discover Errors → 🤖 AI Modifies → ✅ Test → 🚀 Move to the next step

A simple workflow for Vibe Coding

Most importantly:

Do not accept code whose function you do not understand in the important parts of the system.

You are not required to memorize every line the AI wrote.

But you must know what is happening in the Architecture, how data moves, where the weaknesses are, and how to handle errors.

💡

Use AI to increase your speed, not to replace your understanding.

When you deal with Vibe Coding this way, the speed the AI gives you becomes a real advantage.

Because you don't let it lead the project...

You lead, and it executes.

Should you learn programming if you use Vibe Coding?

Here one of the most asked questions by Vibe Coding appears:

If AI can write code, why should I learn programming at all?

The answer is not that everyone should become a professional software engineer.

But if you want to move from just trying an idea to building real programs and relying on them, understanding programming will remain very important.

Not necessarily in the old way.

You don't need to memorize hundreds of lines of Syntax before building your first project.

And you don't need to write all the Boilerplate yourself.

But you must understand the things that make you capable of judging what the AI produces.

Such as:

• How APIs work.
• How apps deal with databases.
• How data moves between system parts.
• What Authentication and Authorization mean.
• How to discover Bugs.
• How tests work.
• What is meant by Architecture.
• Where security problems can appear.

Because when you know these basics, you can look at the code written by AI and ask the right questions.

If you don't know them, you might see a beautiful project working in front of you...

And assume it's good.

Here the style of learning programming itself can change.

Instead of spending a long time trying to memorize everything before building any project, you can learn while you build.

Want to know how an API works?

Use AI to build one, then ask it to explain it.

Want to understand databases?

Build a table, write queries, and see how data moves.

Want to understand Authentication?

Apply it, then try to understand every step happening behind the scenes.

In this way, AI becomes a teacher, an assistant, and an accelerator at the same time.

But there is a rule you must not break:

⚠️

Do not let the AI learn programming on your behalf. Use it to learn programming faster.

Because the difference between the two will appear the moment the first problem occurs that a Prompt cannot solve.

What will happen to the programmer?

Perhaps this is the question that makes Vibe Coding different from just a new tool.

Because we are not just talking about a program that helps you write code faster, but about the possibility of the shape of the programmer's job itself changing.

In the past, a large part of a programmer's day went into converting requirements into code.

Reads the requirement.

Searches for the solution.

Writes the code.

Tests it.

Fixes errors.

Then repeats the cycle again.

When AI can take over a large part of these tasks, it is natural for the programmer's focus to shift to other things.

The question will become less related to:

How do I write this?

And more related to:

What is the best way to build this?

And that is a big difference.

Imagine a programmer in front of a new project.

Instead of starting by writing the first file, they might start by defining requirements, then ask the AI to suggest an Architecture, discuss options, create a Prototype, and write initial tests.

Then they start reviewing the decisions.

Discovers a problem.

Changes the design.

Asks for an adjustment.

Tests the result.

And finally decides what goes into Production.

In this case, the programmer has not disappeared.

But their center of work has moved.

From writing every detail...

To making the decisions that shape the product.

This might make some skills relatively less important, while the value of other skills rises.

Skills that manual reliance on may decrease

• Writing Boilerplate.
• Creating repetitive components.
• Writing traditional CRUD.
• Converting simple designs to code.
• Searching for Syntax for every small problem.

Skills that become more important

• System Design.
• Architecture.
• Debugging.
• Security.
• Testing.
• Understanding Business Logic.
• Code Review.
• Ability to define the problem accurately.
• Ability to judge the quality of the solution.

💡

The easier it becomes to produce code, the more valuable the decisions behind the code become.

Therefore, the future of the programmer might not be to write more code.

But to build better systems using less code, more tools, and more accurate decisions.

Here we reach a very important point:

The programmer who treats Vibe Coding as a way to escape understanding programming might find themselves in trouble.

As for the programmer who treats it as a means to raise their productive capacity...

They might become much stronger than the programmer who works in the traditional way alone.

The danger no one talks about in Vibe Coding

There is another problem that might be more dangerous than AI writing bad code.

That it writes code good enough... to make you stop learning.

And this is an important difference.

You might start your first project using Vibe Coding, and discover that you can build a complete interface within hours instead of days.

You get excited.

Then you build a second project.

And a third.

Every time, when you face a problem, you ask the AI.

It explains.

It fixes.

It suggests.

It writes.

Over time, you might find yourself capable of building many things without deeply understanding how they work.

Here a strange paradox appears:

You became faster at building programs... but you didn't necessarily become better at programming.

Imagine you have an app that works perfectly.

Then a problem occurred in Production.

The API became slow.

Some users are getting wrong data.

And you don't know the reason.

You ask the AI:

Fix the issue.

It suggests an adjustment.

You try it.

The problem is still there.

You ask for another adjustment.

Then a third.

Suddenly you find yourself spinning in a loop of attempts, because you don't have a clear mental model of what is happening inside the system.

Here the problem is not that the AI is weak.

The problem is that you don't know the questions you should ask it.

⚠️

Complete reliance on Vibe Coding might make you good at producing code... and weak at understanding it.

Therefore, there is a difference between someone who says:

AI built the app for me.

And someone who says:

I used AI to build the app, but I understand its Architecture, and I know how to test, fix, and develop it.

The first owns a product.

The second owns a capability.

And this capability is what will stay with you even if the tool you use today disappears and a new tool appears tomorrow.

Therefore, the best way to deal with Vibe Coding is not to let the AI think for you.

But to make it expand your ability to think and build.

Because the goal in the end is not to become the person who can make AI write the most code.

The goal is to become the person who knows what should be built, and how to make sure what was built is worth going out into the world.

Take note: Vibe Coding doesn't mean building everything with AI

Here we need to correct a very common misconception.

When someone hears the term Vibe Coding, they might imagine that the ideal way is to open an AI tool and ask it to build the project entirely, then wait for the result.

But this is often not the best use of the idea.

Real power appears when you know which part of the building process is worth handing over to the AI, and which part you should keep for yourself.

For example, you can let AI handle:

• Creating Boilerplate.
• Building repetitive Components.
• Writing initial tests.
• Converting design to code.
• Suggesting solutions for a specific problem.
• Analyzing errors.
• Executing Refactoring.
• Documenting parts of the project.

In return, you keep the decisions that need an understanding of the context:

• Choosing Architecture.
• Defining Business Logic.
• Security decisions.
• Designing sensitive systems.
• Reviewing important code.
• Determining what goes into Production.
• Determining if the suggested solution is suitable in the first place.

🤯 The most important idea

Vibe Coding is not making AI work instead of you.

It is making AI handle the parts that don't need to consume your time and experience, so you can focus on the parts that really need your experience.

Here the programmer becomes like a leader of the process.

Gives the direction.

Sets the constraints.

Reviews the results.

And intervenes when there is a need for a decision that cannot be left to the machine.

The best Vibe Coding is not the one that makes AI write the most code... but the one that makes the programmer focus on the things worth thinking about.

This is perhaps the most important difference between using Vibe Coding as a shortcut for programming...

And using it as a new way to build software.

What should a programmer learn in the age of Vibe Coding?

If writing code has become easier and faster, this does not mean the programmer needs fewer skills.

It means that the type of skills they need has started to change.

The goal is no longer to be the fastest person at writing Syntax.

AI can help you with that.

The most important thing is to be the person who can look at the problem from above, understand the system, and discover if the solution suggested by AI is actually suitable.

Therefore, a set of skills will become clearly more important.

1 - Understanding Programming Basics

You don't need to memorize everything.

But you must understand how things work:

Variables, Functions, APIs, Databases, Authentication, HTTP, Git.

Because without these basics, you will find it difficult to know what is happening when the AI makes a mistake.

2 - System Design and Architecture

The easier building components becomes, the more important the way of linking these components together becomes.

Is the database designed correctly?

Is the API suitable?

Is the system scalable?

Is the choice of technology logical?

These are decisions that cannot be reduced to just writing code.

3 - Discovering and Fixing Errors

It's easy to ask AI to fix an error.

But the strong programmer is the one who can understand:

What is the cause of the problem?

Where did it happen?

And why did it happen?

Then uses the AI to reach the solution faster.

4 - Software Testing

When AI can write code quickly, testing this code becomes more important.

It's not enough to say:

"It worked for me."

You must ask:

"Will it still work when conditions change?"

Here comes the importance of Unit Tests, Integration Tests, and Edge Cases.

5 - Software Security

And this is one of the most dangerous points.

AI can write Authentication, Payments, and APIs in a short time.

But the existence of the code doesn't mean it's safe.

You must understand at least the basic principles that allow you to discover vulnerabilities and dangerous practices.

💡

In the age of Vibe Coding, your value will not be in your ability to write every line... but in your ability to know which line is worth writing in the first place.

This does not mean learning programming has become less important.

In fact, it might have become more important for those who want to go beyond the stage of "I can build something that works" to the stage of "I can build something that can be trusted."

Will the programmer become less important or more?

Perhaps this is the biggest paradox in the age of Vibe Coding.

At first glance, it seems that AI is taking a large part of the programmer's work.

But at the same time, it opens the door for the programmer to accomplish things that previously needed more time and a larger team.

The programmer who spent hours writing repetitive code can now use this time to understand the product.

And the programmer who stopped at a small technical problem can try several solutions quickly.

And the programmer who needed days to build a prototype can reach a testable version in a short time.

So the problem is not:

Will the programmer disappear?

The better question is:

Which type of programmer will become more valuable?

The value of the person whose primary advantage is speed of writing code only is likely to decrease.

Because this speed has become something AI can multiply significantly.

But the value of the programmer who can understand the problem, design the system, discover errors, make the right decisions, and review what the AI produces...

May rise more.

Because AI can produce many options quickly.

But someone still needs to decide:

Which option is best?

🤯

The better AI becomes at writing code, the less a good programmer depends on writing code and the more they depend on understanding it.

Here an important shift in the definition of "programmer" might occur.

Perhaps the programmer in the future won't just be the person who sits for hours in front of a code editor.

Rather, the person who can take a real problem, turn it into a working system, use AI as part of the building process, and then take responsibility for the final result.

Code will still exist.

But the way to reach it...

Might change significantly.

Where does speed end and responsibility begin?

There is something that makes Vibe Coding different from just using a new tool.

Speed has become available to almost everyone.

But speed alone does not guarantee a good result.

Two people can use the same tool, ask to build the same app, and get completely different results.

The first asks:

Build me an inventory management app.

Then accepts the first result.

And the second starts by defining requirements, divides the project, tests every part, reviews important decisions, and ensures security and performance before considering the project ready.

The tool is one.

But the way of using it is completely different.

Here the programmer's responsibility appears.

When you make AI write a large part of the code, this does not mean you have given up responsibility for this code.

If an error occurs in Production, the answer won't be:

The AI is the one who wrote it.

The user doesn't care who wrote the code.

They care that the product works.

And the company cannot say to the customer:

The problem is from AI.

Because the responsibility ultimately lies with the team that decided to use this code and launch it.

⚠️

The more AI's ability to execute increases, the more important the human who decides what should be executed becomes.

This sets a very important rule for Vibe Coding:

Do not hand over responsibility to the AI just because you handed over execution.

You can make it write code.

You can make it suggest Architecture.

You can make it search for errors.

You can make it write tests.

But in the end...

You are the one who decides what is worth going out to users.

Here exactly Vibe Coding turns from just a fast way to write programs...

To a real test of the programmer's ability to think, review, and make decisions.

What remains for the programmer after Vibe Coding?

Vibe Coding did not make programming worthless, but it changed where the value lies.

Code has become easier to produce, but understanding the problem, designing the solution, reviewing the result, discovering errors, and taking responsibility for the product have become more important.

The programmer who will benefit from this shift is not the person trying to compete with AI in writing code quickly.

But the person who knows when to use it, what to ask of it, and how to review what it produces.

💡

The future is not for the programmer who writes code faster than AI... but for the programmer who knows what should be built and why.

In the end, perhaps the question is no longer:

Will AI take the programmer's job?

Rather, it has become:

Is the programmer ready to work in a new way?

Conclusion: The programmer hasn't disappeared... but they are changing

Vibe Coding does not mean programming is over.

Nor does it mean every person can describe an idea to an AI and then become a software engineer.

What has changed is the human's place within the building process.

AI has become capable of writing large parts of code, creating prototypes, fixing errors, and performing repetitive tasks.

But there are still questions that cannot be ignored:

What are we building?

Why are we building it?

Is this the right structure?

Is the system secure?

Can it be relied upon?

And what happens when it fails?

Here the value of the programmer appears.

Not as the person who writes every line themselves...

But as the person who understands the problem, leads the building process, reviews what the AI produces, and takes responsibility for the result.

🔥

Perhaps the future of programming is not writing more code... but building better things using less code.

Vibe Coding will not make everyone a programmer.

But it will make the programmer who knows how to use it correctly faster and more capable than before.

And the real question is no longer:

Can AI write code?

It has proven it can.

The question now:

Can you know what it should build?

Here exactly begins the difference between someone who uses Vibe Coding...

And someone who actually builds with it.

📌 Before you close the article... keep this rule

If you are going to use Vibe Coding, do not treat it as a way to get rid of programming.

Treat it as a way to raise your ability to build.

Start with the idea, clarify the requirements, let the AI help you in execution, then review and test everything that is important.

And always remember:

Speed is not quality.

Code that works is not necessarily good code.

And AI that can build does not necessarily know what should be built.

Therefore, the more your ability to use AI increases, make sure at the same time to increase your ability to understand, review, and make decisions.

In Vibe Coding, the time you spend writing code may decrease... but do not let it decrease the time you spend thinking.

📌 If you found that this article changed your way of thinking, save it in your Bookmarks.

Not just because it explains a new tool...

But because it explains a shift in how software is built, and how the programmer's role can change with the spread of Vibe Coding.

And if you have a different opinion, or see that Vibe Coding will change programming in another way I didn't address, tell me in the comments. I will be happy to read and discuss it.

Prepared and written by: Adel Ahmed

X: @AdelDeveloperX

💙 If you benefited from the article, don't forget to save it (Bookmark) and share it with your friends interested in programming and AI, as this article might be a starting point for understanding how the way software is built is changing, not just the way code is written.