Cursor Rules: Optimizing AI-Generated Code for Production

The author shares their experience of using Cursor, an AI-powered coding assistant, and the challenges they faced with inconsistent code patterns. They developed a set of production-grade rules to ensure the AI generates code that adheres to their team's conventions, and now sells these rules as a paid product.

Details

The author was working on a SaaS product with a tight deadline and faced issues with inconsistent code patterns generated by Cursor, an AI coding assistant used by the team. They spent a weekend writing specific rules to ensure the AI generates code that adheres to their team's conventions, such as using constructor injection, proper error handling, and Docker best practices. \n\nThe author realized these rules had become the most valuable artifact in the project and decided to package them up and sell them as a product. They argue that while developers can write their own rules, the hard part is finding the right balance of specificity to prevent real bugs while remaining general enough to work across the entire codebase. The author's rules are the result of real-world debugging and code reviews, and they claim these rules can save developers 1-5 hours per week, easily justifying the $27 price tag.\n\nThe author offers five language-specific rule packs (Java, Kotlin, C#, Go, Docker) that include 6+ battle-tested rules with examples and explanations. They position this product as a time-saver for teams using Cursor or other AI coding assistants who want to avoid the hassle of inconsistent code patterns.