Ensuring consistently high code quality poses major challenges for software developers on a daily basis. In particular, the consistent application of clean code principles requires a high degree of discipline, experience, and continuous training. At the same time, there is a growing desire to make development processes more efficient, not only to ensure quality but also to continuously improve it. This is where the targeted use of AI as a supporting tool comes in.
With our project, we developed the Clean Code AI Agent — a solution based on ChatGPT that is specifically designed to identify violations of Clean Code principles and provide concrete suggestions for improvement.
In the first version, the agent focuses on four essential principles of the Clean Code Initiative. These rules were defined as system prompts and supplemented with positive and negative examples so that the AI can reliably identify good and bad patterns. The agent goes far beyond simple rule checks: Even with more complex code examples, it provides precise and practice-relevant tips for improvement.
The Clean Code AI agent not only serves as a feedback tool, but also as a learning tool. Developers can use it to understand clean code principles in a practical way and apply them directly to their own code.
The Clean Code AI agent effectively supports developers in increasing the quality of their code and identifying typical sources of error at an early stage. Through immediate feedback, it promotes a conscious application of proven principles and contributes to a sustainable improvement in software development.
Our experience shows that AI does not replace the clean code developer — it makes him better. The targeted use of the Clean Code AI agent enables teams to make development processes more efficient, improve code quality in the long term and at the same time continuously expand developers' know-how.