The Pitfalls of Vibe Coding: How to Use AI Coding Tools the Right Way

Vibe coding—a rising trend among novice developers—is the practice of handing over coding responsibilities to AI tools and sitting back as the machine attempts to build it all. While entertaining in theory, reality paints a different picture. Many developers have found themselves dealing with AI-generated codebases that are barely functional, full of bugs, and difficult to maintain.

The Rise and Risks of AI-Driven Development

Bugs are a natural part of software development, but it’s particularly frustrating when AI, the very tool meant to speed things up, becomes the root cause of recurring issues. Inexperienced developers often fall into a loop where the AI introduces bugs, fixes them incorrectly, and introduces new ones in the process.

Senior developers aren’t particularly surprised. They know too well that rapid iteration often sacrifices robust planning and thoughtful architecture. The promise of lightning-fast development is tempting—but without guidance, it leads straight into chaos.

The Core Issue: Context is King

The most fundamental flaw in poorly prompted AI code generation is its lack of context. Ask ten developers how to build a feature, and you’ll likely get ten different answers—all technically valid.

• There’s rarely a single best way to build software.
• The best approach depends entirely on the context.

Let’s imagine a worst-case scenario: a feature implemented in a sub-optimal way and without the right context. Perhaps the code makes too many database calls, lacks proper validation, or can’t scale. Even a good implementation must be evaluated under the project’s specific conditions—load levels, latency requirements, expected scalability, and so on.

That’s why every line of code must be contextualized in the bigger picture. Future-proofing a codebase means developing with foresight and understanding—not just copy-pasting code suggestions from AI.

AI-Driven Mediocrity: When the Magic Fades

Junior developers and non-technical entrepreneurs are often the most enthusiastic adopters of AI tools. Why? Because magic is only magical if you don’t know the trick.

Someone without experience sees an AI generate a to-do app or a mobile prototype and gets impressed. But seasoned developers know you can build a complete game engine in Python with under 100 lines, using libraries like pygame. The “wow” factor evaporates quickly when you realize how much you’re missing—especially in terms of code quality and maintainability.

Let’s say a novice wants to build an app: “I want to create a mobile app that helps students with their homework by letting them scan a sheet of paper.” The AI generates functional code, but it’s built on superficial assumptions and fragile implementations. Fast forward a few prompts later, and the project sputters into an unmanageable mess.

Why does this happen? Because beginners don’t critically assess the AI’s output. They keep prompting, switching between LLMs like Claude, Sonnet, or Mistral, only to end up with broken code and growing frustration. Ultimately, they turn to Reddit or Twitter, pleading for help.

The Real Problem

The core problem can be distilled into one sentence: There are infinite ways to build software, but only a handful will meet your specific requirements effectively.

So ask yourself:

• Who is the target user? What grade or subject is the app for?
• What platform should it support—iOS, Android, both?
• Which database and framework will support scale?

When developers say “it doesn’t matter, just make it work,” they’re abdicating responsibility. They let the AI make fundamental product and architectural decisions. As a result, the outcome is predictable:

• The wrong product gets built (not enough context)
• The right product is developed inefficiently (bad design)
• Or both

Software development is a complex decision tree. Each choice affects the next. And only you—the human—know where you’re trying to go. Relying on AI to make those decisions without supervision is a recipe for disaster.

The Right Way to Use AI for Coding

This doesn’t mean you should stop using AI. It means you should use it better. Here’s the key question: “How can I use AI coding tools in a way that avoids building the wrong thing and ensures robust, future-proof development?”

The answer lies in this single principle:

Tell the AI how to build it, not just what to build.

When beginners prompt the AI with both the what and the how missing, they give the AI too much autonomy. Instead, tell the AI your implementation strategy. This results in more superficial decisions being delegated—details that can be easily revised.

Benefits of Specifying the “How”

• You stay familiar with your codebase
• You understand the reasoning behind design choices
• You learn from the process
• You can iterate effectively

Next time you’re about to prompt a feature, pause and ask: “How should this be built?”

If unsure, use AI to explore the pros and cons of different approaches. Decide consciously before coding begins.

3 Practical Tips for Smarter AI-Assisted Coding

1. Start with an idea of the implementation – Know what you want before prompting.
2. Document everything – Create a detailed README.md with your app’s goals, user stories, and domain logic.
3. Use project configs – Tools like cursor.directory with .cursorrules files can inject structured context into your development environment.

These practices dramatically increase the quality and maintainability of AI-generated code.

Final Words

Despite the criticism, I remain optimistic about AI’s role in software development—especially for those who learn how to use it wisely. Personally, AI accelerates my workflow and motivates me to explore new technologies. That curiosity leads to growth, and every mistake becomes a stepping stone.

So yes, use AI. Just use it intentionally, with clarity and precision. Over time, you’ll build more maintainable code and avoid dead ends. And when challenges arise, they’ll become learning opportunities—not roadblocks.

Thanks for reading. I share tech insights to help you use technology for freedom and self-growth. Follow me on Twitter: @itsfilipk.