Vibe Coding Without Fundamental is Garbage

The rise of generative AI has brought about a fascinating, terrifying new trend in software development “vibe coding”.

Don’t get me wrong. coding with AI is an incredible superpower. It’s a massive productivity booster that can eliminate boilerplate and speed up development time exponentially. If your foundational programming knowledge is shaky, your prompts will be terrible, and the code you get back will be a tangled, unmaintainable mess.

The core issue is simple. If you don’t understand programming basics, you cannot write prompts that enforce proper coding conventions. You can’t set architectural boundaries. You’re not engineering a system, you’re just wishing upon a silicon star and hoping for the best.

The Garbages

Let’s look at what actually happens when “vibe coding” meets a complete lack of foundational knowledge.

Latency

Imagine you’ve built an endpoint, and you notice your application is suddenly crawling. Naturally, you turn to your AI assistant and type: “Make this code run faster and reduce latency.”

It sounds like a reasonable request, but you have absolutely no idea how code optimization actually works. Are you CPU-bound or I/O-bound? Is the algorithmic complexity quadratic when it could be linear?

If you don’t know the “how”, how are you going to validate the AI’s solution? The AI, trying to be helpful, might decide to aggressively cache everything, completely ignoring memory constraints. Or worse, it might strip out essential error handling and data validation just to shave off a few milliseconds on a benchmark. It looks faster on the surface, but underneath, it’s a ticking time bomb.

Concurrency

Now, let’s step it up a notch. You want to process a massive dataset faster, so you prompt the AI “Implement concurrency here.” The problem? You don’t understand thread scheduling, race conditions, or resource management.

Let’s say you are writing a backend script to parse and validate 50,000 transaction records. You write a basic loop, but it takes forever. Doing some classic vibe coding, you prompt the AI “Make this process the whole list at the same time so it’s instant.”

The AI obediently does exactly what you asked. It wraps your execution block in an unbounded concurrent loop, spawning a new goroutine or thread for every single item in that list simultaneously. Because you lack the fundamentals of connection pooling, worker pools, or rate limiting, you look at the code, think wow, that was easy, and happily run the script.

The result ? Your script instantly opens 50,000 simultaneous connections to your database. You exhaust the connection pool in a matter of milliseconds, crash your database, and effectively DDoS your own infrastructure. You achieved “concurrency,” but because you didn’t understand the underlying mechanics, you completely broke production.

Readability Crisis

Here is a golden rule of software engineering that vibe coders often forget, Code is read many more times than it is written. Over its lifetime, a single piece of code will be read hundreds, maybe thousands of times and clarity is paramount because all software is written by humans to be read by other humans. The fact that software is also consumed by machines is secondary.

Let’s say you need to write a validation script to audit a complex data structure. You prompt the AI “Write a script to validate this payload and make it as short as possible.”

The AI happily spits out a dense, hyper-optimized, recursive one-liner filled with chained higher-order functions and regex from hell. It works perfectly. You copy-paste it, merge the PR, and feel like a genius.

Fast forward six months. A new edge case appears, or a bug is reported in the validation logic. You (or worse, your teammate) open that file. You stare at the code, and it looks like ancient hieroglyphics. Because you didn’t enforce a proper design pattern, use clear variable naming, or structure the code with early returns, you are completely lost in your own codebase. You saved five minutes writing it with AI, but you will now spend five hours trying to decipher it. The machine understood the “clever” one-liner perfectly, but the human maintainers are left stranded.

In the end, you spend days trying to debug code you never understood in the first place. You burn through API tokens, waste your money, and end up with a system that is fundamentally broken. 😆

The Takeaway

To get the most out of AI, you have to be the architect. You need to learn the fundamentals, understand the architecture, and use the AI to do the heavy lifting of writing the syntax. You have to know what clean, structured, human-readable code looks like before you can ask an AI to write it for you. Otherwise, you’re just paying for the privilege of creating legacy code faster than ever before.

AI will transform the process, and humans will be the definition