Code Review Practice helps software engineers build one of the most overlooked interview and workplace skills: giving high-quality code reviews. Instead of solving coding problems, you'll review real code, identify issues, and compare your feedback with AI-generated suggestions. Perfect for: 💻 Software engineers 🎓 Students preparing for interviews 👥 Anyone wanting to become a better reviewer Current beta features Practice reviewing real code AI-generated review suggestions
How does the AI actually know what feedback is "good" here, is it comparing against some kind of ground truth or just generating suggestions and letting me decide?
@yaardeveciektr The AI is trained to recognize established code review best practices, common bug patterns, maintainability concerns, readability issues, and potential performance or security risks. Rather than treating its output as absolute "ground truth," it generates context-aware suggestions with reasoning, leaving the final decision to the developer. We're also continuously improving the quality of feedback based on real-world usage and developer input, so the recommendations become increasingly practical and actionable over time. We'd love to hear what kinds of feedback you'd find most valuable!
How do you handle languages or frameworks the AI might not be familiar with? Curious whether the suggestions get shaky when you throw something niche at it.
@zl_ates80384 The AI performs best on widely used languages and frameworks where there's plenty of established knowledge and best practices. For niche languages or less common frameworks, it still analyzes the code using general programming principles—such as readability, maintainability, potential bugs, and logic—but framework-specific recommendations may be less precise. We prefer to be transparent about that rather than overstate confidence, and we're continuously expanding support and refining the quality of suggestions as we learn from real-world usage. If you have a niche stack in mind, we'd love to hear about it and test it!
the side-by-side comparison between your notes and the ai's suggestions is genuinely clever, it turns reviewing into a learn-by-doing loop instead of just another quiz format
@fahribryam5g4c Thank you! We're really happy that feature stood out to you. The side-by-side comparison was designed to make code reviews an active learning experience rather than a passive one. By comparing your observations with the AI's suggestions, you can identify gaps, reinforce good review habits, and gradually build stronger review instincts. We appreciate you trying it out, and we'd love to hear any ideas that could make the learning experience even better!
Tried reviewing a few real snippets and the AI suggestions caught things I'd usually miss, like subtle naming issues. It's a neat way to sharpen review instincts without bothering teammates.
@lyasfrancec6us Thank you for trying it out! We're really glad it was able to catch some of those subtle issues. One of our main goals is to help developers build stronger review habits and spot things that can easily slip through the cracks, whether it's naming, readability, or maintainability concerns. It's great to hear that you found value in using it independently before involving teammates. We appreciate the feedback and would love to hear any suggestions as you continue exploring it!
Love that you focused on the reviewer side of things instead of yet another leetcode grind. The AI feedback comparison feels especially useful for spotting blind spots in my own review style.
@sedagoncal Thank you! That was exactly the motivation behind building it. We wanted to create something that helps developers improve a skill they use every day, rather than just solving coding challenges. We're really glad the AI feedback comparison resonated with you—that feature is designed to help uncover blind spots, encourage different perspectives, and make every review a learning opportunity. We truly appreciate your support, and we'd love to hear any ideas you have as you continue using it!
Tried this for a few minutes and the AI suggestions caught a subtle naming issue I totally missed. This could actually level up how engineers approach reviews instead of just rubber-stamping PRs.
@melahatakgzhvi We're thrilled to hear that. Catching subtle issues like naming, clarity, and maintainability is exactly the kind of value we hope to provide. Our goal is to help reviewers spend less time on routine checks and more time on meaningful discussions about design and overall code quality. Really appreciate you trying it out, and we'd love to hear any feedback or ideas as you continue using it!