In this paper, the authors introduce a novel approach powered by a Large Language Model (LLM) designed to automate and improve the code review process. Here are key highlights:

• The LLM-based AI model is trained on extensive code repositories to identify potential issues and optimize code quality.
• Unlike traditional static analysis tools, this model predicts future potential risks, enhancing both code quality and developer knowledge.
• The effectiveness of this AI agent in enhancing the code review process is explored through detailed analyses and developer feedback.

Opinion and Importance: This research is crucial as it not only automates the tedious task of code review but also enhances the learning curve of developers by providing insights into potential risks and improvements. This can be a significant step forward in developing more robust, error-free software applications in the future. The ability to predict future issues before they become problematic could transform software maintenance.