What Is Vibe Coding? An Introduction To Next Gen AI Development
Is vibe coding an overhyped trend or a real threat to your job security?
Vibe coding is an AI first approach to software development. Instead of meticulously structuring code, debugging line by line, and sweating over syntax, developers now interact with AI models like ChatGPT, Deepseek & Claude to generate and refine their code.
This is a step further forwards than just copying your bugs into a model and asking it to fix them. With vibe coding you are using language to text processing to converse what you want the model, which acts as the programmer to do.
The phrase “code is liquid” sums it up. The process is fluid, dynamic, and intuitive. Instead of rigidly constructing code, you “vibe” with it, guiding AI in a collaborative workflow.
Sounds amazing, right? Well, it is… and it’s about to get a whole lot better.
Now, before you fire up Cursor and start calling yourself a project manager, let’s break down what vibe coding does well.
1. Rapid Prototyping
If you need to build something simple fast, like a startup MVP, a quick data pipeline, or a small web app, the AI we have today excels at this type of work.
In the future, imagine launching a startup over the weekend… without hiring a single developer. The frontend, backend, payment gateway, customer support is all built for you, deployed and launched. That’s what vibe coding makes possible.
People have already built fully functional web apps with database integrated backends without knowing how to code.
AI tools let you go from idea to execution quickly, taking “move fast and break things” to the next level.
2. Increased Productivity
For experienced developers who could write the program from scratch, AI minimizes cognitive overhead. Forget typing boilerplate functions or handling repetitive syntax. AI takes care of that natspec documentation that you hate doing anyway. This leaves the developer to act in a broader curator role.
Ever felt like coding is 25% typing and 25% thinking and 50% browsing stack overflow? What if AI could handle the typing and some of the thinking, so you can focus on what really matters?
In a few years time a single CTO or even non-technical founder will be able to leverage AI systems to do the work of a team of frontend and backend devs. This is going to make startups a lot less nerdy for better or worse.
3. Creative Experimentation
Vibe coding is a great way for bouncing ideas around, tweaking existing products and generally causing chaos within a code repository.
You just throw out ideas and let AI generate a solution. And if it doesn’t work? You tweak the prompt and regenerate. Or spend your time having a full on argument with the model about tabs and spaces.
In the same way we can use LLM’s to brainstorm titles for a YouTube video, we can bounce ideas for sections within an app or call to action buttons on a landing page.
4. Lower Barrier to Entry
Non-coders can now build things. Whether that’s good or bad depends on how much you value your job security (we’ll get to that). But the point is, AI makes software development way more accessible.
It’s like no-code platforms, but with code and slightly less useless.
But here’s the thing, just because AI can write code doesn’t mean it writes good code all the time. Let’s talk about why AI isn’t perfect, yet.
1. Hallucinations
AI doesn’t know code, it predicts code based on it’s training data. It generates solutions that look right, but sometimes are complete nonsense. The current models are still a long way from AGI where it would have some level of common sense.
Ask AI to write a complex function, and it might produce something that works… or it might summon a demon from the depths of some npm library that never needed including in the first place. When it goes wrong or bloats your applications, debugging AI-generated spaghetti code can be a nightmare.
2. Debugging and Maintenance
Eagleson’s Law “Any code of your own that you haven’t looked at for six or more months might as well have been written by someone else.”
If you’ve ever been in that situation where you’ve had to try and fix a code base that no longer makes sense, or if you are an expert in deciphering ancient hieroglyphics, you’ll have a good background for debugging AI generated code. At its worst this is like trying to get your head around code written by someone you hate in a foreign language.
Screaming curses at Sam Altman while keyboards are getting launched out the window is not the vibe we were promised.
Even worse, what if it sort of works, but has subtle errors? How do you catch them before they cause serious problems? Sure you can get the AI model to generate unit tests and what not but it’s still a regular issue given the current model capabilities.
3. The Complexity Ceiling
Vibe coding excels at small projects and scripting tasks. But things break down if you are working on a complex, niche or frontier project. If you are building something new that hasn’t been done before or using an unusual programming language or framework, the model doesn’t have any training data to base it’s response on.
The result is a less than compelling experience where you end up just doing it yourself.
4. Team Collaboration
The challenges discussed are compounded when there is a team working on a larger code base. The different devs are working with isolated models which aren’t syncing with each other or their users goals.
Many organisations are restricting the use of AI for developers currently but to some degree it’s just slowing down an inevitable future.
So, where does this all go?
We’re heading toward a world where AI isn’t just assisting coding, it’s doing the coding.
Imagine a future where you don’t even read code, it’s written in some low level language you’ll never understand, you just describe what you want, and AI figures it out.
We’re also seeing AI self-improvement loops, where AI writes code, runs it, evaluates performance, and refines it automatically. This is incorporated into hardware containers so that you can build entire apps without needing to deploy anything manually.
Now on to the big question, does this kill developer jobs? In our lifetime will we witness the end of coding as a profession?
Vibe coding lowers the barrier to entry. Non-technical people can now build simple software, in the future they’ll be able to build complex software. Founders can prototype without hiring engineers. CTOs can scale products without hiring a team of junior devs.
The truth is… the demand for developers is going to plummet over the next decade as models become more advanced and capable.
The junior developer role will be first to go, finally confirming that “entry-level job requiring 5 years of experience” was just a bad joke all along.
There is still going to be some work for senior devs, architects, and engineers who understand systems, security, and large-scale software design. But the truth is we lived through a golden era where developers became billionaires and geeks were celebrated heroes. At least that’s how I’ll tell it to my grandkids.
This evolution in how we build software will drive down salaries as the supply and demand shifts from a shortage of capable engineers to a surplus of unrequired talent.
It’s both an exciting time and a terrifying time. If you’re a developer, you can’t stop progress so better to start adapting now and embrace the emergence of AI and vibe coding.
