The Vibe is Vibe Coding: Why you shouldn't fall for it?
- Adonis Celestine
- Mar 23
- 4 min read
I had always been saying — IT is just like fashion. Remember when ripped jeans became a statement piece? No matter how impractical, people bought them because they were the vibe. Well, in the world of software development, the latest vibe is vibe coding—a hands-off, AI-assisted approach that looks great at first but quickly turns into a maintenance nightmare.
The term vibe coding—coined by renowned computer scientist Andrej Karpathy in February 2025—refers to an AI-dependent programming technique where developers describe a problem in a few sentences, feed it to a large language model (LLM), and let AI generate the code. Instead of manually coding, programmers now spend their time guiding, testing, and desperately trying to make sense of what the AI just spit out. It’s like letting autocorrect write your love letters—sometimes you get poetry, and sometimes you get a restraining order.
How Exactly is Vibe Coding Used?
Imagine you need a function to sort an array. Instead of thinking through the best approach, you simply type:
"Hey AI, write me a function to sort numbers."
Boom! A shiny piece of Python appears. Looks fine, right? Until three weeks later, when you discover it’s using bubble sort in a production system handling millions of transactions.There are even YouTube tutorials teaching you how to generate an entire application in 24 hours using vibe coding. Sounds amazing—until you realize you’ve just built a glorified house of cards.
Vibe coding with AI happens when:
You write vague prompts like "make an API thingy" and expect magic.
You copy-paste AI-generated code without testing because "it compiles, so it must be fine."
You rely on AI to write complex logic without understanding what it does.
You debug an AI-written function by asking AI to debug it, leading to an infinite loop of confusion.
Why is Vibe Coding a Problem?
1. A Maintenance Horror Show
Ever inherited a codebase where half the functions have variable names like data_thing_1 and do_magic()? That’s vibe coding. AI generates something, you move on, and six months later, when a bug surfaces, you have no idea what’s going on. Even AI looks at it and says, "I have no clue, dude."
Vibe coding feels magical at first—it’s like low-code tools. You spend one hour coding and 100 hours maintaining it instead of 100 hours coding and one hour maintaining it. You saved time today, but you’ve just signed up for a long-term debugging marathon.
2. AI is Confidently Wrong
AI can write code that looks right but is completely incorrect. It’s like that friend who explains quantum physics at a party after reading a Wikipedia summary. LLMs don’t “know” things; they just predict what sounds correct. Trusting them blindly is a great way to turn a minor bug into a full-blown system meltdown. Remember, LLMs are just word calculators, not all-knowing coding wizards.
3. Security
Ask AI to write a login system, and you might get one that stores passwords in plain text. AI doesn’t always prioritize security, so if you don’t review its work, you might as well leave your front door open with a sign saying, "Please don’t rob me." Plenty of CEOs have embraced vibe coding—only to regret it later when security vulnerabilities surfaced and customer data leaks made headlines.
4. The Debugging Nightmare
Debugging AI-generated code is like trying to decipher your own handwriting after writing in a rush—you thought it made sense at the time, but now it looks like ancient hieroglyphics. When something breaks (and it will), you’ll spend hours figuring out what the AI was “thinking” (spoiler: it wasn’t thinking at all).
5. Extensive Quality Assurance Required
As someone in quality assurance, I’d love to say my job is now more important than ever. But realistically, testing AI-generated code is a nightmare. Human developers make mistakes, but they follow a pattern. With AI, mistakes are unpredictable, and testing becomes an endless game of whack-a-mole. You don’t just need test cases—you need an entirely new strategy to handle the weird and wonderful errors AI will generate.
How to Use AI Without Vibe Coding Your Way to Disaster
Write clear, extensive prompts – Prompt engineering is 90% common sense. Provide context and be specific about your goals.
Read and understand the code – If you don’t know what it does, don’t use it.
Test everything – AI makes mistakes. Your app shouldn’t suffer because of them.
Pair AI with human peer review – AI is an assistant, not a replacement for engineering discipline.
AI-assisted coding is incredible, but relying on it blindly turns you into a glorified middleman between requirements and a product that barely works. The key is balance—let AI boost your productivity, but don’t let it replace your brain. Otherwise, you’re just vibe coding with extra steps, and that’s a one-way ticket to software chaos.
Have you encountered AI-driven vibe coding in your projects? Share your horror stories in the comments!
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