What is your experience with AI code review tools?

[anjit6]

I am looking for personal suggestions on using AI code reviews. Did any of the tools actually help you with the code review process? If yes, what exactly did it help you with? Did you come up with any special workflow to ensure it works for you?

Also, I am curious about AI code review tools. How does it have an impact on who is reviewing? For example, can a mid-level dev manage the quality of a senior dev with the help of these tools?

[edvaldodfreitas]

Great to see this topic coming up! I work at Kodus, so I’m closely involved with both the development and real-world application of AI-powered code review tools.

From my experience (and from what I hear from users), AI really helps raise the bar for code reviews: it catches bugs, suggests style improvements, flags inconsistencies, and helps maintain security and quality standards. What I find most interesting is how the AI learns from the team’s own history, so the suggestions become more and more aligned with the reality of each project.

At Kodus, we built Kody, an AI agent that integrates with GitHub, GitLab, Bitbucket, and Azure DevOps. Kody provides contextual suggestions and evolves with your team’s feedback. A cool feature is that Kody can analyze your project’s review history and suggest custom rules, which makes it much easier to maintain standards and retain knowledge as your team grows.

For mid-level developers, I see AI as a powerful ally: it brings objective criteria, suggests best practices, and speeds up learning—making it easier and more comfortable to participate in reviews, even alongside more experienced developers.

If you want to learn more, Kodus is open source, easy to integrate, and very flexible. You can check it out at https://kodus.io

Bottom line: AI doesn’t replace human reviewers, but it really helps speed up the process, standardize practices, and support team growth. If you want to chat more or have questions about Kodus, feel free to reach out!