Mastering Vibe-Coding: 5 Essential Rules to Prevent Debugging Disasters

After dedicating two years to vibe-coding, I’ve honed my approach to avoid the chaos of endless debugging sessions. If you’re grappling with the frustrations of coding and AI tools, these five rules might just save you from a lot of headache.

1. Implement the 3-Strike Rule

A wise lesson I learned: if your AI assistant fails to resolve an issue after three attempts, it’s time to step back. My codebase once ballooned from 2,000 to 18,000 lines while attempting to fix a simple dropdown menu. By the end, I found the AI enclosing my entire application in try-catch blocks!

What to do instead:

• Take a screenshot of the malfunctioning UI.
• Begin a new chat session.
• Clearly articulate what you want the component to do rather than describing what’s going wrong.
• Allow the AI to reconstruct the element from scratch.

2. Beware of Context Windows

Here’s a critical realization: the AI’s memory can falter after about ten exchanges. On one occasion, my assistant thought I was developing a recipe blog instead of an AI voice platform because we spent too long troubleshooting a singular feature.

To improve this:

• Save functional code separately after every few interactions.
• Start anew with a fresh session.
• Share only the component that needs fixing along with a brief description of the app’s purpose.

This strategy reduced my debugging time by approximately 70%.

3. Apply the “Explain Like I’m Five” Principle

If you can’t succinctly describe the problem in a single sentence, you may be spiraling into complexity. I once wasted an entire six hours trying to explain that “the data flow is peculiar, and the state management seems problematic while the UI occasionally fails to update.”

Now, I stick to straightforward descriptions like:

• “Button fails to save user data.”
• “Page crashes upon refresh.”
• “Image upload results in undefined.”

Clarity leads to more effective solutions.

4. Use Version Control as a Safety Net

Commit your code after every single working feature, not simply at the end of each day or session. I learned this the hard way after losing three days of progress by continually optimizing code until it broke.

These were my results from last week:

• 42 total commits

• 31 served as rollback points