Using AI to write better code more slowly (nolanlawson.com)

A new perspective on AI-assisted coding emphasizes the potential for writing high-quality code more deliberately, countering the prevalent notion that AI is best utilized for rapid, low-quality output. The author champions the use of large language models (LLMs) not just for generating code quickly but for meticulously reviewing and improving existing codebases. By employing multiple AI tools, such as Claude, Codex, and Cursor Bugbot, developers can effectively identify and prioritize bugs, ranging from critical security issues to subtle performance flaws, thereby enhancing overall code quality. This approach, often referred to as "vibe coding," shifts the focus from sheer productivity to a deeper understanding of the codebase. While it may not speed up the development process in terms of output volume, it fosters a healthier coding environment, encourages learning, and prevents overlooked issues. The author suggests that this method also allows for a more satisfying development experience, reinforcing that quality should take precedence over speed in software engineering. By embracing this slower, more thoughtful coding style, developers can enhance their work and contribute to the long-term success of their projects.