3 Vibe Coding Mistakes That Break Your First AI App

Key Takeaways

• Planning before implementation prevents AI from making inefficient choices like N+1 queries instead of SQL JOINs
• Vibe coders with programming knowledge produce significantly better results than those relying entirely on AI
• Discussing changes during the planning phase saves time compared to rewriting generated code

Vibe coding sounds simple. Describe what you want, let the AI write the code, ship it. But Zunaid Ali, a tech writer and developer, discovered that this approach consistently produced what he calls "half-baked products with broken features."

After months of experimenting with GitHub Copilot for personal projects, Ali identified three techniques that separate working vibe-coded apps from failed experiments. The lessons apply whether you're using Copilot, Claude, or ChatGPT for code generation.

The Rush-to-Code Trap

Ali's biggest mistake was jumping straight into implementation. The logic seemed sound: get it done quickly by letting the AI start writing code immediately.

The result was consistently broken. Without upfront planning, he couldn't anticipate how the AI would approach specific features. One recurring problem: the AI would use N+1 database queries instead of SQL JOINs. For non-developers, that's the difference between your app making 100 database calls versus one. It works in testing, then crashes under real load.

The fix is counterintuitive for vibe coding. Before asking the AI to write anything, ask it to plan. Describe your requirements and have the model explain its approach. You'll catch bad architectural decisions before they're buried in hundreds of lines of generated code.

Why Planning Saves Hours

Ali found three specific benefits to planning first.

1. You see the AI's approach before it writes code. If it's about to use an inefficient method, you can redirect it upfront.
2. Changes are cheap during planning. Rewriting a plan takes seconds. Rewriting generated code that's already integrated into your project takes hours.
3. You maintain context. When you understand the plan, you can better evaluate whether the generated code actually implements it correctly.

This last point matters more than it seems. Vibe coding often fails not because the AI writes bad code, but because the human can't tell whether the code matches what they asked for.

Programming Knowledge Changes Everything

Ali makes a claim that might frustrate non-technical founders hoping to build apps without learning to code: vibe coders with programming knowledge produce significantly better results.

This isn't gatekeeping. It's practical reality. When you understand concepts like database queries, API design, or basic debugging, you can catch problems the AI introduces. You can also give better prompts because you know the right terminology.

The N+1 query example illustrates this perfectly. A non-developer wouldn't know to specify "use JOINs instead of separate queries" because they wouldn't know the distinction exists. The AI would happily generate working but slow code, and the problem wouldn't surface until the app had real users.

The Iterative Approach

Ali's workflow now follows a clear pattern: plan, review the plan, implement in small chunks, test each chunk before moving on.

The "small chunks" part is critical. When you ask an AI to build an entire feature at once, debugging failures becomes nearly impossible. You're staring at 200 lines of code you didn't write, trying to figure out which part broke. When you build incrementally, you know the new code is the problem because everything worked before you added it.

This approach is slower upfront. But Ali found it's faster overall because you spend less time untangling AI-generated spaghetti code.

When Vibe Coding Actually Works

Despite the challenges, Ali believes vibe coding can produce "quality software products" when done correctly. The key is treating the AI as a junior developer who needs clear direction, not a magic box that produces working apps from vague descriptions.

The best use cases are projects where you understand the domain well enough to evaluate the output. If you're a marketer building a landing page, you can tell whether the generated HTML looks right. If you're building a complex backend system without backend experience, you're gambling.

Practical Implementation Tips

• Start every session by describing the overall project context, even if the AI should "remember" from previous conversations
• Ask the AI to explain its approach before writing code
• Specify constraints upfront: database type, framework versions, performance requirements
• Build one feature at a time and verify it works before moving on
• When something breaks, isolate the problem by reverting to the last working state

These aren't revolutionary techniques. They're standard software development practices. The insight is that vibe coding doesn't exempt you from them. It just changes who writes the actual code.

Frequently Asked Questions

Do I need to know how to code to use vibe coding?

You can produce basic projects without coding knowledge, but developers with programming fundamentals catch more AI mistakes and give better prompts. The quality difference is significant.

Which AI tool is best for vibe coding?

GitHub Copilot, Claude, and ChatGPT all work for vibe coding. The techniques in this article apply regardless of which tool you use. Choose based on your existing workflow and IDE integration needs.

How do I know if the AI-generated code is good?

Test each piece of functionality before adding more code. If you can't evaluate code quality directly, build incrementally so you can identify when something breaks.

What's the biggest mistake in vibe coding?

Jumping straight into implementation without a planning phase. This leads to inefficient code patterns and architectural decisions that are expensive to fix later.

Can vibe coding replace professional developers?

For simple projects with clear requirements, sometimes. For complex systems, vibe coding works best as a productivity tool for experienced developers, not a replacement for development skills.

Source: How-To Geek