AI and Code Quality: Building a Synergy with Human Intelligence by Arthur Magne

The quality of AI-generated code is directly influenced by the quality of the data and coding standards it receives. In an environment where AI acts as a co-pilot for the development team, the code it generates will ultimately be read, maintained, and extended by the team itself. To ensure that the time saved by AI isn’t lost on tedious maintenance tasks, it is crucial that the generated code adheres to the team’s established best practices, including security constraints, design patterns, accessibility, and technical decisions. Moreover, maximizing the benefits of AI requires highly skilled individuals who can establish clear standards and critically evaluate the AI's output.At Packmind, we aim to tackle this challenge by accelerating developers’ skill growth through AI coaching and by integrating team best practices with AI coding assistants.In this session, we will explore how teams can easily and continuously define and maintain their development standards, and how AI can help extract those standards from the current codebase. Once these standards are established, AI can assist in enforcing them, help train the entire team, and generate code that aligns with validated human expertise. Through concrete examples, we will demonstrate how AI can become a true co-pilot for the team, contributing to the project's success while continuously improving the team’s development practices.