Code Review Agent with Self-Reflection: GPT-4 vs. Gemini Pro 1.5

This video explores building a code review agent using AI, comparing the performance of Google's Gemini and OpenAI's GPT-4. The goal is to create an agent that not only analyzes code but also reflects on its own feedback and iteratively improves its review.

While both models attempt the task, GPT-4 demonstrates a superior understanding of the objective. It provides specific, actionable feedback on the code review itself, allowing the agent to refine its analysis and deliver a more comprehensive and valuable final report. In contrast, Gemini struggles with the self-reflection aspect, offering generic feedback that hinders the iterative improvement process.

Here's what you'll learn:

- The concept and implementation of a code review agent using large language models.
- Comparison of GPT-4 and Gemini in understanding and performing the self-reflection task.
- Evaluation of the final code review output generated by each model.
- Insights into the strengths and weaknesses of each model for this specific use case.

If you're interested in building AI applications and want to know about capabilities of different language models, this video provides valuable insights and a practical demonstration.