🔗 AI coding tip 027 - Force code standards

Style errors double when nobody enforces them. Maximiliano Contieri outlines a critical aspect of AI coding: enforcing standards. A CodeRabbit analysis revealed that AI-generated code contains about 1.7 times more defects than human-written code, particularly in the areas of naming and style consistency. Instead of relying on human memory to remember coding standards, Contieri advocates for integrating machine-checkable rules through hooks and validators. This can block violations before any human review occurs, allowing developers to focus on design rather than mechanical checks. With each violation logged as a rule, the enforcement grows stricter over time, promising a measurable drop in defects and allowing for faster reviews. This shift emphasizes the need for automation in maintaining code quality.