🚫 Hot Take: "Vibe Coding" Is NOT the Future — Here's Why You Should Care

“What I cannot create, I do not understand.” — Richard Feynman

This quote has stuck with me for years. It’s simple, but profound — and it resonates now more than ever as we enter the era of AI-assisted development.

Let me start with this: I love the advancements in AI. Models like Claude 3.5 Sonnet, GPT-4, Gemini, and others have dramatically boosted my productivity — sometimes by 10x, even 100x. AI tools have become my assistants, and in many cases, my creative collaborators.

That being said, we need to have a serious conversation about the culture emerging around what's called “Vibe Coding.”

🎭 What Is Vibe Coding?

Vibe Coding is not an official term, but it perfectly captures a specific mindset that’s becoming increasingly common: the act of leaning heavily — sometimes entirely — on AI to write your code, with little to no understanding of what that code is actually doing.

Here’s what it often looks like in practice:

• You have a task or a bug to fix, and instead of thinking through the problem, you immediately open up your AI assistant.
• You write a natural language prompt describing what you want.
• The model returns code that seems to do the job.
• You copy-paste it directly into your editor.
• You run it. It works. You move on.

On the surface, this feels efficient. You got a solution in seconds. You didn’t have to dive into documentation or explore Stack Overflow. You didn’t even need to understand the syntax deeply. It’s like magic, right?

But here’s the catch: while you’ve achieved a result, you’ve skipped the most important part of the process — the thinking.

🚨 Why This Is a Problem

At first, this workflow may seem harmless — maybe even smart. Why reinvent the wheel if a model can generate it for you? But over time, the cost becomes clear:

You didn’t struggle. You didn’t debug. You didn’t question the approach. You didn’t analyze trade-offs. You didn’t build an internal mental model of what’s actually happening.

And all of that means: you didn’t learn.

Vibe Coding gives the illusion of progress — because your code runs, your app looks complete, and your bug disappears. But under the surface, you’re slowly becoming more and more dependent on something else to do the thinking for you.

It’s like getting to the top of the mountain via a helicopter instead of hiking. Sure, you reach the summit — but you didn’t build the muscle, endurance, or wisdom that the climb would’ve given you. And when it comes time to navigate the next mountain — one the AI can’t easily fly you over — you’ll find yourself stranded.

🛠️ AI Is a Tool — Not a Crutch

These models are extraordinary — but when you allow them to replace your thinking, you’re outsourcing the very thing that makes software development powerful: your problem-solving mindset.

Developers don’t just write code — they:

• Design systems
• Anticipate edge cases
• Optimize for constraints
• Think in layers and abstractions

When you skip that process in favor of quick wins, you're not accelerating your growth — you're bypassing it.

I’ve seen this firsthand: developers hitting walls because they didn’t debug, didn’t understand the libraries they were using, or didn’t stop to ask, “Why does this work?” They let AI do the thinking — and it showed when things went wrong.

You should use AI to enhance your learning, not replace it.

💡 Real-World Projects Show AI’s Limits

In many of the projects I’m involved with — from complex front-end ecosystems to tightly coupled architectures with domain-specific logic — no state-of-the-art model can fully solve the problems at hand.

Not because the models aren’t advanced, but because they lack:

• Long-term project context
• Familiarity with subtle architectural decisions
• Awareness of business and user constraints
• And most importantly, human intuition built through experience

AI excels at pattern recognition. But building production-ready systems requires judgment, trade-offs, and foresight — qualities developed through real-world coding, debugging, and iteration.

🧠 “Coding Is Dead” Is a Lie — It’s More Alive Than Ever

Lately, I’ve seen a growing narrative:

"Coding is obsolete." "Tools like v0, Cursor, and Lovable will replace developers".

Let’s set the record straight: coding is not going anywhere.

Despite what some loud voices might be saying online — that “coding is dead,” that AI tools will replace developers — the truth is actually the opposite. Coding is not only alive and well, it’s entering what may be its most exciting era yet.

Yes, the landscape is changing. Yes, AI is playing a bigger role. But far from making coding obsolete, AI is actually making it more accessible to more people than ever before.

Here’s what’s different now — and why this is great news for anyone interested in learning to code:

1. The Tools Are Incredibly Powerful

Modern development tools — whether it’s full-featured frameworks like Next.js, build systems like Vite, or design systems like ShadCN/UI — give you the ability to build professional-grade applications with fewer lines of code and faster iteration cycles than ever before.

You no longer need to wrestle with manual Webpack configs or low-level memory management just to ship something real. The modern stack is geared toward productivity, velocity, and creativity.

2. Documentation Has Never Been Better

Gone are the days of cryptic manuals and poorly maintained libraries. Today’s open-source ecosystem is supported by rich documentation, interactive examples, and vibrant communities. Whether you’re learning JavaScript, building with React, or experimenting with WebGL, chances are the answers are out there — clearly written, community-supported, and AI-searchable.

Combine that with video tutorials, live coding sessions, blogs, newsletters, and platforms like Stack Overflow, and you’ve got an ecosystem where anyone — with curiosity and persistence — can learn to build.

3. The Barrier to Entry Is Lower

You don’t need a computer science degree to become a successful developer. You don’t need to master C before touching JavaScript. You don’t need to understand recursion before deploying your first website.

With tools like GitHub Copilot, ChatGPT, and browser-based IDEs, beginners can prototype ideas in real time, get unstuck quickly, and build confidence faster. That means more people from non-traditional backgrounds are entering tech, solving unique problems, and enriching the field with diverse perspectives.

4. The Ability to Launch Has Skyrocketed

Want to build an app? You can deploy a full-stack product with authentication, payments, database, and responsive UI — in a weekend.

Platforms like Vercel, Netlify, Firebase, Supabase, and Railway remove the infrastructure barriers that used to make deployment painful. You can focus on your idea, not on DevOps.

You can ship fast. You can iterate faster. And you can reach global audiences almost instantly.

✅ So how do we use AI productively — without falling into the Vibe Coding trap? Here's what I recommend:

• Use AI as a mentor, not a magician — Ask why, not just what
• Dissect the code it gives you — Understand the patterns, not just the output
• Build real projects — Push through ambiguity and make mistakes. That’s where mastery forms
• Debug often — Every bug is a learning opportunity in disguise
• Stay curious — Read documentation, explore source code, experiment with alternatives
• Reflect intentionally — Ask: What did I learn? How could this have been done differently?

AI can be a brilliant learning tool when paired with intentional effort and critical thinking.

🧭 Final Thoughts

Feynman said it best: “What I cannot create, I do not understand.”

If you aren’t creating with purpose — if you’re only assembling AI-generated fragments — you’re not building understanding. And in the long run, that’s what makes great developers stand out.

So don’t settle for vibe-based shortcuts. Use AI. Don’t let AI use you.

Build. Break things. Learn. Reflect. Repeat.

That’s how we grow.