What does “vibe coding” actually mean?
Vibe coding is a way of building software where you describe what you want in plain English, and an AI tool writes the code for you. Instead of typing out lines of code by hand, you type (or speak) an instruction like “build me a page that lists my products with a search box” and the AI generates the working code. You then look at the result, ask for changes, and repeat until it does what you need.
The “coding” still happens. It just happens inside the AI tool rather than at a keyboard, line by line. The person driving the process reacts to what comes back, nudges it in the right direction, and keeps iterating. That back-and-forth, more feel than formula, is where the “vibe” comes from.
It is worth being precise about one thing: in its purest form, vibe coding means moving quickly and not scrutinising every line the AI produces. In practice, most people doing this for anything that matters do look at the code, or at least test it properly, before it goes anywhere near real users. We will come back to why that distinction matters.
Where did the term come from?
The phrase was coined by Andrej Karpathy, a well-known figure in AI research and one of the founding members of OpenAI, in a post in February 2025. He used it to describe a style of coding where you lean fully into AI-generated code, describe intent in natural language, and accept suggestions without reading every diff line by line. The term caught on quickly because it captured something a lot of people were already starting to do with tools like ChatGPT, Claude, and GitHub Copilot: treating the AI as the one actually writing the code, with a human steering from the outside rather than typing every character.
Since then, the term has broadened. People now use “vibe coding” loosely to describe almost any AI-assisted development where natural language is the main input, whether or not they are following Karpathy’s original “don’t look at the code” approach. That looser usage is the one most people searching for the term will encounter day to day.
What vibe coding is genuinely good for
Used sensibly, this approach has real, practical value. It shines in a specific set of situations:
Prototypes and proof-of-concepts. If you want to test whether an idea works before committing budget to it, vibe coding can get a clickable version in front of you in hours rather than weeks. That is valuable for pitching an idea internally, testing a concept with customers, or simply deciding whether something is worth building properly.
MVPs (minimum viable products). Early versions of a product, built to learn from real users rather than to last forever, are a good fit. Speed matters more than polish at this stage, and AI-assisted coding is fast.
Internal tools. A dashboard for your team, a simple stock tracker, a form that pulls data into a spreadsheet: tools used by a handful of people you know, for a specific job, with low consequences if something is slightly off. These are ideal candidates because the bar for “good enough” is lower and the audience is forgiving.
Automations and one-off scripts. Connecting two systems, tidying up a spreadsheet, generating a report automatically each week. This kind of task is narrow, testable, and doesn’t need to survive years of unattended use in front of paying customers.
In all of these cases, the appeal is the same: you get something working fast, you can see whether the idea has legs, and the cost of being wrong is low.
Where it falls short
This is the part that gets glossed over in a lot of the hype, and it matters more the moment real customers, real money, or real data are involved.
Production hardening. Code that works when you test it once is not the same as code that keeps working under real-world conditions: unexpected inputs, high traffic, patchy internet connections, users doing things you didn’t anticipate. AI-generated code is often written to satisfy the immediate request, not to survive the messiness of production use. Getting it properly production-ready usually takes as much work as writing it did, sometimes more, because you are debugging code you didn’t write and don’t fully understand.
Security. This is the sharpest edge. AI tools can and do generate code with security weaknesses: exposed data, weak authentication, ways for someone to manipulate a form or a database that the tool never flagged. If nobody with the right experience reviews it, those problems sit there until someone finds them, and by then it is often a customer data issue rather than a code review comment. Anything handling customer details, payments, or logins needs proper scrutiny before it goes live, full stop.
Maintainability. Six months from now, someone (possibly you) will need to change this thing. If the code was never reviewed, structured sensibly, or documented, that change becomes a slow, expensive guessing game. AI tools are good at producing something that works today; they are not automatically good at producing something a human can safely edit later without breaking it.
None of this makes vibe coding bad. It makes it a tool for a specific job: getting to a working version quickly, not skipping the engineering that makes something safe and durable.
What this means if you’re not technical
If you run a business and you’re not a developer, the practical takeaway is this: vibe coding is a genuinely useful way to explore ideas, test concepts, and build small internal tools cheaply and quickly. It is not, on its own, a safe way to build something customer-facing, something that touches payments or personal data, or something you plan to rely on for years.
The risk for non-technical business owners is not the tool itself, it’s not knowing where the line sits between “quick prototype” and “production system”, and finding out the hard way after a launch, a data issue, or a costly rebuild. A tool that got you most of the way there in an afternoon can still need real engineering time to close the remaining gap, and that gap is usually where the risk and the cost both live.
The sensible approach is to use AI-assisted coding for what it’s genuinely good at, prototypes, internal tools, testing ideas, and bring in proper technical oversight before anything goes near customers, payments, or sensitive data.
Getting help
If you’ve had something built this way, or you’re weighing up whether an idea is ready to move from prototype to production, it’s worth getting a second pair of experienced eyes on it before you commit further budget or go live. We help business owners assess AI-built prototypes, work out what needs hardening, and plan a sensible route from “it works on my laptop” to something you can safely put in front of customers.
Have a look at our AI consultancy and development services if you’d like an honest, practical assessment of where you stand.
And if you would rather see the approach in action than read about it, our Vibe Coding Sprint turns one idea into a working prototype, with a fixed scope agreed up front.
