The real gate on parallel AI development isn't model capability — it's whether you can turn "requirement alignment / correctness verification / architectural oversight" into loops the agent can close itself. This post is the method I worked out after burning a few thousand dollars of tokens.

Recently, VibeCoding has become a new trend in the development community. With tools like Cursor and Claude Code, developers only need to describe requirements and AI can automatically generate code. From batch completing repetitive code to quickly building prototypes and refactoring legacy code, it greatly improves development efficiency. In our attempts, we found it can fully handle medium-difficulty engineering development work. The productivity boost it brings is impressive. However, many people feel disappointed when first encountering it: AI-written code doesn't run, changes mess up the project, and they end up returning to manual coding or asking questions in regular AI chat interfaces while writing.

This article is intended for security researchers who have developed scripts and personal projects and want to learn more about engineering development.