What Is Vibe Coding? Who It Suits and What It's Good At

Vibe coding is a way of building software where an AI writes the code and a person describes what they want in plain language, looks at the result and asks for changes. Often nobody reads the code at all: if it works, you move on.

The term started half as a joke, but it stuck for a serious reason. Someone who has never opened a terminal can now ship a working app. The interesting question isn’t whether that’s good or bad, it’s what it’s actually good for.

What vibe coding looks like in practice

You open Lovable, Bolt, Replit, v0 or an editor like Cursor and type: “Build a booking page for a hair salon: pick a service, a date, a form with a phone number.” A minute later you have a screen. You type “add email login.” Another minute, there’s a login. Then “save bookings to a database,” “email the stylist,” “add an admin page.”

The loop is always the same:

describe the task;
get code and immediately see how it behaves;
say what’s wrong;
repeat.

The difference from regular development isn’t that AI writes the code. Professional engineers use AI too. The difference is that in vibe coding, people judge the code by its behaviour, not its contents.

Who vibe coding suits

Founders without a technical team. To test an idea you don’t need perfect code, you need something you can put in front of people. Vibe coding gets you there in days rather than months.

Product managers and designers. A clickable prototype running on real data persuades better than a mockup and answers half the engineering questions before engineering starts.

Teams that need an internal tool. An admin panel, a report, a warehouse form: the things developers never have time for, used by five people in one office.

Developers doing boring work. Standard forms, layout, converting data from one format to another. An experienced person can check the result in a minute.

What it’s good at

Speed to a first result. From idea to a working screen in minutes.
Common patterns. Forms, lists, cards, auth through an off-the-shelf service, simple database tables. The AI has seen these millions of times.
Interfaces. Generated screens often look decent, especially if you give an example.
Learning. You can ask why something was done a certain way and get an explanation on your own code.
Cheap mistakes. A bad version is easy to throw away and regenerate.

What it’s bad at

The problems with a vibe-coded app don’t show up on day one. They show up when the project stops being small.

Security. AI makes things work, not hard to break. Keys shipped to the browser, data with no permission checks, forms with no validation are all routine.
Complex logic. Payments, subscriptions, schedules across time zones, several roles with different permissions. Here “works in the demo” and “works” are different things.
Code growth. Every new request adds code but rarely removes old code. A couple of months in, the same thing is implemented in three places and fixing one breaks another.
Debugging. When something breaks and nobody has read the code, you search for the cause blind. The AI may “fix” the symptom and bury the actual problem deeper.
Maintenance. Six months later you need to upgrade a library or move hosts, and it turns out nobody knows how the thing is put together.

Vibe coding and engineering aren’t enemies

A useful mental model: vibe coding produces a draft. A very fast draft, sometimes a surprisingly good one, but a draft. Its job is to prove that someone wants the idea. Once that’s proven, the project has real users, their data and their money, and the bar for the code changes.

From there you have two options. Keep vibe coding, but more carefully: small steps, checking each change, and someone who reads the code at least occasionally. Or hand the project to engineers who clean it up and leave you a foundation you can keep building on. Often the sensible answer is both, in turns.

There’s only one bad option: pretending the draft is the final version because it opens in a browser.

In short

Vibe coding is building software where AI writes the code and a person judges the result by behaviour, not by reading it.
It’s great for prototypes, MVPs, internal tools and standard screens.
Its weak spots are security, complex logic, a growing codebase and debugging.
Treat vibe-coded output as a draft that proves an idea, not a finished product.
Once real users and money arrive, the code needs review and an engineer’s eye.

If your project has outgrown the draft stage, SUBXCAT can take it to production without starting from scratch.