How "Vibe Coding" Is Reshaping Software Engineering

You've heard the term. Fredsazy explains what "vibe coding" actually means — and why it's quietly changing how software gets built.

8 min read
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Software Dev
How "Vibe Coding" Is Reshaping Software Engineering

First there was pair programming. Then there was AI pair programming. Now there's something else entirely: vibe coding. It's loose. It's fast. It's messy. And it's spreading through engineering teams whether managers like it or not. Here's what vibe coding actually looks like, why developers love it, and where it breaks.


Let me start with a conversation I had last week.

I asked a developer how they built a feature. Expecting to hear about planning, documentation, tests.

They said: "I just vibed it."

I asked what that meant.

They said: "You know. Opened Cursor. Described what I wanted. Let the AI write. Tuned it with more prompts. Didn't worry about perfect. Just got it working. Vibed it."

That's vibe coding. It's not a joke. It's not a meme. It's how a growing number of developers actually work.

And it's reshaping software engineering — whether the old guard likes it or not.


What Is Vibe Coding? (No Jargon, Just Reality)

Let me define it simply.

Traditional coding: Plan. Design. Write. Test. Review. Deploy. Slow. Careful. Structured.

Vibe coding: Prompt. Generate. Tweak. Prompt again. Get something working. Move on. Fast. Messy. Fluid.

Vibe coding isn't about writing perfect code. It's about writing working code quickly, using AI as a partner, and caring less about elegance than about momentum.

The name sounds silly. The practice is serious.

I've watched engineers ship features in hours that would have taken days using traditional methods. The code isn't pretty. The tests aren't comprehensive. But the feature works. The user is happy. The business moves.

That's vibe coding.


Why Developers Are Flocking to It

Let me tell you what's driving this shift.

Reason 1 – Traditional coding is slow

Planning meetings. Design docs. Code reviews. Test coverage requirements. CI pipelines. Deployment windows.

All of these exist for good reasons. But they also kill momentum. Developers want to build. They don't want to wait.

Vibe coding removes the friction. Prompt. Generate. See results instantly. The feedback loop is seconds, not days. That's addictive.

Reason 2 – AI is actually good enough now

Two years ago, AI-generated code was mostly wrong.

Today? For many tasks — CRUD endpoints, basic UI components, data transformations — the AI gets it right more often than it gets it wrong.

Developers noticed. If the AI can write 80% of the code correctly, why spend hours writing it yourself? Write the 20% that matters. Let AI handle the rest.

That's vibe coding.

Reason 3 – "Good enough" wins in early stages

Not every project needs NASA-level reliability.

A prototype doesn't need perfect tests. An internal tool doesn't need elegant architecture. A weekend side project doesn't need a design review.

For these contexts, vibe coding is perfect. Fast. Flexible. Low ceremony. Get something working. Validate the idea. Refactor later if the idea survives.

Reason 4 – It's more fun

Let's be honest. Writing boilerplate is boring. Context-switching into planning mode is draining. Waiting for reviews is frustrating.

Vibe coding feels like playing. You describe. The AI generates. You tweak. You see results. You move forward.

Fun matters. Developers who enjoy their work do better work.


What Vibe Coding Actually Looks Like

Let me paint you a picture.

A developer opens their AI coding tool. No planning document. No ticket. Just an idea.

Prompt 1: "Build a simple form that collects email and name, saves to a database, and shows a success message."

The AI generates HTML, CSS, JavaScript, and a backend endpoint. Maybe 200 lines. Takes 30 seconds.

Prompt 2: "Make the form look nicer. Add some padding and a shadow."

The AI updates the CSS.

Prompt 3: "Add validation. Email must be valid. Name can't be empty."

The AI adds validation logic.

Prompt 4: "The success message disappears too fast. Make it stay for 3 seconds."

The AI tweaks the timeout.

Thirty minutes later, the feature is done. No formal review. No test suite. No deployment pipeline. Just working code.

That's vibe coding. It's not how you'd build a banking app. It's exactly how you'd build a prototype, an internal tool, or a weekend project.


Where Vibe Coding Breaks

I'm not saying vibe coding is always right. It's not. Let me tell you where it fails.

Failure 1 – Technical debt accumulates fast

Vibe coded projects start simple. Then they grow. More features. More users. More edge cases.

But the code wasn't built to scale. The abstractions aren't clean. The tests don't exist. The documentation is whatever the AI wrote.

Six months later, the project is a mess. Every change breaks something else. The vibe coder has moved on. Someone else is stuck maintaining it.

I've seen this happen. Multiple times.

Failure 2 – No one understands the whole system

When ten different people vibe-coded ten different features, no one understands how everything connects.

The AI wrote each piece in isolation. There's no unifying architecture. No shared patterns. No documented decisions.

Good luck debugging a production issue across that codebase.

Failure 3 – Security and compliance get ignored

The AI doesn't know your security requirements. It doesn't know your compliance obligations. It doesn't know that you can't store credit card numbers in plain text.

Vibe coders often miss these things. Not because they're careless. Because they're moving fast. Security checks slow them down.

That's a real risk. I've seen vibe-coded prototypes accidentally expose internal APIs. The code worked. The security did not.

Failure 4 – Team coordination breaks down

Traditional coding has pull requests, code reviews, shared style guides. These are annoying. They also create alignment.

Vibe coding often skips these. Everyone builds their own way. The team fragments. What works for one person breaks for another.

I've watched teams split over this. The vibe coders want freedom. The traditionalists want structure. Both are right. Both are frustrated.


The Middle Ground That Actually Works

Let me tell you what I've seen work.

Use vibe coding for exploration, not production

Vibe coding is incredible for prototypes, proofs of concept, and internal tools. Use it there.

When a project proves valuable, rewrite it properly. Don't let the vibe-coded version become the production version. That's how debt accumulates.

Set vibe coding hours

I know a team that does this. Mornings are for traditional coding — planning, reviews, tests. Afternoons are for vibe coding — fast exploration, rapid prototypes, loose experimentation.

Both modes have their place. Separate them intentionally.

Vibe code alone. Review together.

The generation can be loose. The review should be tight.

Let individuals vibe code their features. Then bring the team together to review, align, and refactor. You get the speed of vibe coding and the quality of collaboration.

Document what the AI wrote

This is simple and most teams skip it. When the AI generates something, add a comment: "Generated by AI for X purpose on Y date."

Future developers will thank you. They'll know not to trust it without review.


What Traditionalists Get Wrong

Let me push back on the critics for a moment.

"Vibe coding isn't real engineering."

Maybe not. But it gets features shipped. And shipped features beat elegant architecture that never sees users.

"You can't maintain vibe-coded code."

You can't maintain unreviewed vibe-coded code. But reviewed, refactored, and documented vibe-coded code is fine. The problem isn't how the code was written. It's what happened after.

"Vibe coding lowers standards."

It lowers ceremony. That's different. Standards about security, testing, and architecture can still apply. Vibe coding just changes how the first draft gets written.

"Real developers don't vibe code."

Real developers use whatever works. I've seen principal engineers vibe code. I've seen juniors do traditional planning. The tool doesn't define the engineer. The outcome does.


What Vibe Coders Get Wrong

And let me be fair to the other side.

"Reviews are a waste of time."

They're not. Reviews catch mistakes. They spread knowledge. They build shared ownership. Skipping reviews saves time today. Costs time tomorrow.

"Tests slow me down."

They do. They also save you from shipping broken features. The right balance isn't zero tests. It's smart tests. Critical paths only. Smoke tests. Not full coverage for every prototype.

"Documentation is for old people."

Documentation is for future you. When you debug this code at 2 AM, you'll want to know why you made that weird choice. Write it down. Future you will be grateful.


The Brand Takeaway

Here's what I want people to think when they hear Fredsazy talk about vibe coding:

"They understand the trade-offs. Speed matters. So does quality. They don't pick one. They balance both."

Anyone can say "vibe coding is the future" or "vibe coding is destroying engineering." Both are wrong.

The truth is messier. Vibe coding is a tool. It's great for some things. Terrible for others. The best engineers know when to use it and when to put it away.

That's what I want you to take from this. Not hype. Not fear. Clarity.


One Last Thing

Try vibe coding yourself this week. Pick a small task. Something you'd normally spend hours on. See how fast you can get to working code.

Then look at what the AI wrote. Is it maintainable? Is it secure? Would you trust it in production?

Your answers will tell you where you stand.

Not me. Not the internet. Your own judgment.

That's the only opinion that matters.


Written by Fredsazy — because "vibed it" is now a legitimate answer in standup.


Iria Fredrick Victor

Iria Fredrick Victor

Iria Fredrick Victor(aka Fredsazy) is a software developer, DevOps engineer, and entrepreneur. He writes about technology and business—drawing from his experience building systems, managing infrastructure, and shipping products. His work is guided by one question: "What actually works?" Instead of recycling news, Fredsazy tests tools, analyzes research, runs experiments, and shares the results—including the failures. His readers get actionable frameworks backed by real engineering experience, not theory.

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