technical debt arising from deep vibe coding

 Here’s a clean, engineer-oriented English version of your article: The Technical Debt of Deep Vibe Coding: When AI Starts Making Things Worse After extensively using AI to build a web application—across multiple models and workflows—I started noticing a consistent pattern that doesn’t get discussed enough: Vibe coding works incredibly well at the beginning, but beyond a certain depth, it starts to accumulate technical debt rapidly—and then collapses. 1. The Breaking Point: Around Iteration 4–5 In the early stages (iteration 1–2 Examples： BAC Calculator web), AI performs at its best: Clear understanding of the problem Clean and coherent code generation High efficiency and strong signal-to-noise ratio By iteration 3, things are still manageable. But somewhere between iteration 4 and 5 , a shift happens. At this point, every new change introduced by AI begins to: Fix the current issue Reintroduce or expose previous issues Slightly degrade overall code quality You’re no longer buildi...