Using Large Language Models (LLMs) to autonomously review code presents a new paradigm in software development. This research evaluates the practical effectiveness and implications of an LLM-based code reviewing tool.

Detailed analysis:

• Enhanced accuracy in identifying and suggesting fixes for code issues.
• Reduction in post-release bugs as a direct consequence of improved code reviewing processes.

Significance: The integration of LLMs into the code review process not only improves code quality but also serves as an educational tool, aiding developers in adopting best practices. The potential to streamline the software development lifecycle through LLM applications is vast, making this a significant contribution to both software engineering and AI application in real-world scenarios.