This study presents a Large Language Model (LLM) based AI agent designed to improve code review processes by identifying potential issues and suggesting improvements. Key takeaways are:

• Utilizes extensive data from code repositories for training.
• Capable of detecting code smells and potential bugs.
• Provides proactive suggestions for improving code and developer education.
• Demonstrates potential for reducing post-release bugs through better code reviews.

Importance: This research highlights how AI can transform traditional coding practices to enhance software development efficiently. The integration of LLMs in code reviews has shown promising results in not only improving code quality but also in educating developers about best practices. Future research could focus on the scalability of such systems and their impact on software engineering methodologies.