Kodus

Engineering teams are writing more code with AI every month. An agent opens a PR with a few hundred lines in minutes, the code compiles, the tests pass, and nothing looks wrong on a first read. Delivery got faster, but review did not keep up: the same reviewers now have to cover far more code, […] The post AI code review for regulated environments in 2026: tools compared appeared first on Kodus.

There are plenty of open-source AI code review tools today, and at first glance, they all seem to do more or less the same thing. But they don’t. Some are pretty simple and handle the basics inside CI. Others go further by pulling context from the codebase, applying team-specific rules, and giving you more control […] The post 7 Open-Source AI Code Review Tools Compared for 2026 appeared first on Kodus.

I have been using AI to write code since GPT and Claude 3.5 Sonnet made it useful enough for real work. For a long time, I used it as a copilot. I wrote the code, made the decisions, and asked the model to complete functions, explain unfamiliar parts, or help when I got stuck. Around […] The post WTF does code quality mean when humans stop reading the code? appeared first on Kodus.

We started with a concrete target: find more of the 136 known bugs in our evaluation set. After roughly 20 experiments, the best high-recall configuration moved our AI code review recall from about 53% to 62%. The baseline found 72 bugs and produced 170 false positives. The high-recall configuration found 84 bugs and produced 328 […] The post We ran 20 experiments to improve AI code review recall appeared first on Kodus.

If everyone can use the same models, why are some AI code reviews better? Finding the right code was not the issue in one of our evaluations. A pull request passed a user-controlled URL to Ruby’s Kernel#open method. The reviewer inspected the right part of the diff and raised several findings nearby. It even traced […] The post What makes an AI code review agent actually work appeared first on Kodus.