Understanding Vibe Coding: Potential, Risks, and Real Impact

The developer community is divided when it comes to vibe coding. Some see it as a revolution, while others view it as a shortcut to poorly written code. What’s the truth? Somewhere in between.

In this post, I will share what vibe coding actually is, why it is being talked about so much, and why I believe we need it — but should use it wisely.

What is vibe coding?

Vibe coding is a programming approach where an AI model tries to “pick up the vibe” of the code — the context, style, intent, and patterns used in a project.

Instead of relying on simple autocomplete or generating code from a prompt, Vibe coding systems learn how a team or individual thinks and predict the next steps in that same style.

Vibe coding is the next logical step — AI that not only knows syntax but also understands context. It’s a tool for automation, not a substitute for thinking.

Technology doesn’t wait — we either adapt or fall behind.

And we have seen this pattern before, especially with tools that initially seemed unnecessary or even controversial.

Before: There was a time when IntelliSense (automatic code completion in IDEs) was viewed as something that would create developers who rely too much on it and do not know the syntax by heart.

Today: No serious professional writes code without it. We see it as a standard and essential tool for reducing typing and syntax errors.

Parallel: This is precisely how we will soon see vibe coding. It is simply the next level of assistance in our tools.

Vibe coding saves a significant amount of time in the coding phase — but it also makes code reviews and checks more thorough and sometimes slightly longer. Still, when everything is taken into account, the benefit is clear: we develop faster, and with discipline and attention, we maintain quality.

AI tools in development are no longer an add-on — they’re the standard. They speed up development, reduce repetitive tasks, and allow teams to focus on logic and architecture.

Ignoring vibe coding today is like ignoring Git ten years ago — you can, but not for long. And this becomes even more important in the enterprise environment.

Enterprise context

When a single line of code costs thousands of euros, every mistake becomes more than a bug — it becomes a cost, a reputational risk, and a loss of user trust. Deployment is not “click and see what happens” — these are processes that take hours, sometimes days.

Every change undergoes a multilayered pipeline, including testing, security validations, and change management procedures. In such an environment, vibe coding brings both potential and risk.

Vibe coding can help you write faster, cleaner, and more consistent solutions. But if the AI “assumes” something incorrectly, it can be extremely costly.

That is why quality control remains a core principle in enterprise teams.

Code review is not optional — it is mandatory.

Every AI-generated line of code must undergo the same process as manually written code — because security and stability always have priority over speed.

Conclusion

I want to emphasize this: vibe coding is not a magical solution.

In my experience, it can produce impressive results — but also a lot of unnecessary ones. It often assumes incorrect context, invents helper functions, or “fixes” things that were not broken. We should use it as support, not as a substitute for thinking.

We should not become too comfortable with its solutions — because every “captured vibe” carries the risk of missing an error the AI did not understand.

And at the end of the day, the real question is simple. Don’t ask whether AI will replace developers. Ask whether developers who know how to use AI will replace those who don’t.