In the ever-evolving world of software development, new trends pop up faster than you can say “deprecated.” Some make sense. Others are marketing spin masquerading as progress. And then there’s vibe coding—a concept that sounds cool, feels empowering, but falls apart under scrutiny.
If you haven’t come across the term, vibe coding refers to the process of using AI tools to write software through natural language prompts, driven more by instinct or “feel” than by structured planning or traditional dev practices. The latest piece from MIT Technology Review laid it out clearly: vibe coding lowers the barrier to entry for non-programmers by letting them “vibe” their way into application creation.
But here’s the thing.
Lowering the barrier doesn’t remove the need for understanding.
And that’s where the whole thing gets shaky.
The Appeal: Magic at Your Fingertips
Let’s start with the obvious appeal. Vibe coding promises the dream many non-technical founders and aspiring indie hackers have always wanted: “I tell the machine what I want, and it builds it for me.” No more syntax. No more boilerplate. No more Stack Overflow rabbit holes.
In theory, that’s liberating. It opens the door for more people to experiment and innovate without needing years of technical training. And at the prototype level, this approach can be useful. A startup founder who needs a basic UI mockup to show investors might get something viable in an afternoon using a few smart prompts. A designer wanting to test out a form or interaction might skip Figma and jump straight to code.
But—and it’s a big but—that’s the limit of where vibe coding actually makes sense.
What Could Possibly Go Wrong?
Let’s say a novice user prompts an AI to build a login screen. They get back a block of code, maybe React or Flutter. It runs. They cheer. But what exactly did they receive? Did the AI use best practices? Is it storing passwords securely? Did it include error handling? Is there a hidden injection vector in the backend call?
Without experience, the user doesn’t know—and worse, they don’t know what they don’t know. It works, so they move on. The danger is invisible until it’s catastrophic.
The illusion of progress is not the same as actual competence.
Even if you refine the prompt, unless you fully understand the structure of the code you were handed originally, you can’t verify if the new response introduced new bugs, broke old functionality, or changed something critical in a subtle way. AI doesn’t issue changelogs. And unless you’re inspecting the diffs manually, you’re flying blind.
This becomes even more dangerous as systems grow in complexity. Interdependencies increase. Context expands. And vibe coding doesn’t scale contextually well. That’s where experienced developers earn their keep—knowing how systems evolve, where they break, and how to avoid creating a fragile monster held together with duct tape and dreams.
Debugging: Vibe Coding’s Achilles’ Heel
Let’s say your vibe-coded app stops working. Now what?
If you didn’t write the code—or worse, don’t understand it—you’re stuck. You either keep throwing new prompts at the AI, hoping it’ll “fix” itself, or you abandon the whole thing and start again. That’s not engineering. That’s superstition.
Real debugging requires understanding. It’s a skill that can’t be skipped, no matter how good the AI gets. When you remove the developer’s comprehension from the loop, you remove the ability to reason about behaviour, isolate faults, and apply proper fixes.
The No-Discipline Trap
Software development isn’t just about making things work. It’s about making them reliable, maintainable, and secure. It’s about writing tests, checking edge cases, handling errors gracefully, and thinking through future scalability.
Vibe coding tends to skip all of that. It gives you something that “runs,” which feels satisfying but often masks deep structural issues. There’s no guarantee of clean separation of concerns, no architectural consistency, and definitely no automated test coverage. If you want those things, you have to ask for them—and you need to know how to ask, and why they matter.
Otherwise, what you’re building is software with the appearance of sophistication and the foundation of a sandcastle.
What Happens When You Need to Update?
Let’s assume the app actually works long enough to gain traction. Now a library gets updated. An API changes. A browser update breaks something. Can the original “viber” fix it?
Doubtful.
Without a mental model of how the system works, updates are risky. You can’t just keep feeding new prompts into the AI and expecting consistent results. Even if the tool supports multi-round conversations, it doesn’t “understand” the deeper intention of your software. It’s regurgitating patterns and probabilities, not applying experience or foresight.
Eventually, someone with actual development chops will have to step in. And when they do, they’ll likely need to untangle a mess of undocumented, incoherent, AI-sourced code.
But What About Skilled Developers?
Now, let’s flip the lens.
For experienced developers, vibe coding can be a helpful tool—especially during the ideation phase. It’s great for sketching out small components, mocking up UIs, or even generating boilerplate. I’ve used it that way myself. In the hands of someone who knows what clean code looks like, what to inspect, and how to test, it can dramatically speed up development.
But that’s the key difference: they know what to look for. They don’t trust the output blindly. They treat it like an over-eager intern—useful, fast, and sometimes brilliant, but always in need of supervision.
Suggesting that vibe coding is a pathway to competence for novices is like saying Photoshop turns anyone into a great designer. It doesn’t. It just gives them a tool. The outcome still depends on the person using it.
Final Thought: Empowerment Without Understanding is a Mirage
Vibe coding is being marketed as a breakthrough for democratizing software creation. And in some narrow cases, sure—it makes spinning up a prototype or testing an idea easier than ever before.
But building something that lasts, scales, or earns trust? That still requires understanding.
Until we solve the deeper problem of education, vibe coding is a shiny shortcut that leads nowhere. It creates more tech debt, more fragile systems, and more confusion when things break.
Use it if you know what you’re doing. Avoid it if you don’t.
And stop pretending that throwing AI at a problem removes the need for human skill.
We’re not there yet. Not even close.
#StayFrosty!
