code-reviews are not a good use-case for LLMs. here's why: LLMs shine in usecases when their output is not evaluated on accuracy - for example, recommendations, semantic-search, sample snippets, images of people riding horses etc. code-reviews require accuracy.
What is a useful agent in the context of code-reviews in a large codebase is a semantic search agent which adds a comment containing related issues or PRs from the past for more context to human reviewers. This is a recommendation and is not rated on accuracy.
What is a useful agent in the context of code-reviews in a large codebase is a semantic search agent which adds a comment containing related issues or PRs from the past for more context to human reviewers. This is a recommendation and is not rated on accuracy.