RT by @janwillemmeije6: Merge pull request 10x faster with AI

RT by @GillyFat: 10X speed, 10X quality in code reviews with AI

R to @bemijonathan: I think AI can go a long way in automating giving objective feedback in code reviews. Especially with teams that have a healthy culture of documenting their decisions on styles, architecture, enforced habits, etc.

R to @mykeels: I have been part of the team working on this tool @coderabbitai I think we have gone a long way to be able to reduce this cost by automating it with ai. We have an open source version which is also completely free 🤗

R to @DeveloperHarris: I've been using @coderabbitai for this (so affiliation). It does GPT PR summaries + comments on code. It has been extremely effective and caught a lot of bugs. Highly recommend.

R to @coderabbitai: 10x the bugs

🚀 Exciting Product Update! CodeRabbit customizations made easy! You can now customize CodeRabbit using a YML file from your repository. Refer to our documentation for further details 👇 https://coderabbit.ai/docs/get-started#1-customize-coderabbit-using-a-yml-file

R to @coderabbitai: farted n sharted

CodeRabbit reviewing it. That's when you know it's gold! 🥇

RT by @eTheJackForge: It doesn’t matter how long you’ve been programming. Code reviews can be stressful. Thankfully there are apps being developed that aim to crush impostor syndrome and have you writing better code. I recently started using one of these applications: @CodeRabbitAI. CodeRabbit is an app that fully integrates into your GitHub repos, reviews your code, and then suggests changes that should be made. These changes are based on CodeRabbit analyzing your pull requests and offering suggestions that it feels would be most beneficial to your product. Designed with larger scale businesses in mind, the low barrier of entry to @CodeRabbitAI makes it an invaluable tool for those seeking a competitive edge. The application deeply understands what you’re working on and can look at the whole picture, rather than a small snippet that you feed into it. Any major issues encountered during a review will be flagged for a more detailed review by you or a knowledgeable member of your team. While smaller issues can be resolved quickly without taking up valuable time. I’ve only been using CodeRabbit for a few weeks, and it has completely changed my workflow. Now I can complete my work, push my code to a branch, and then scan the review from CodeRabbit to see if there are any recommended changes. This all happens in seconds. Saving me and my team a ton of time. Even better, is how you can ask CodeRabbit for suggestions on how to make fixes, directly through GitHub. Take a look at the code in the images below. After analyzing the pull request, CodeRabbit discovered an issue with how rankPosts are sorted in a social media algorithm. In the comments on Github, I asked for a potential fix and it offered a suggestion that would resolve the potential issue. This was done in the time that it took me to refresh the browser. Try it out for yourself (link in replies). It’s very easy to set up and you can try out all of the features for FREE for 7 days. Thank you to @CodeRabbitAI for sponsoring this post.

RT by @eTheJackForge: If you'd like to check out @CodeRabbitAI for FREE, you can sign up right here: 👇 https://coderabbit.ai/

RT by @eTheJackForge: Code reviews can take up a ton of time, but new solutions are being introduced to make the process easier. Development tools designed to save you from spending unnecessary development hours on your project. Let’s take a look at one of the best: @CodeRabbitAI is an application that integrates into your GitHub repositories, monitors the activity on your pull requests, and flags anything that may require a more in-depth look. How does it work? When a PR is created, CodeRabbit automatically goes to work. For every change that is made, a review is conducted with the help of artificial intelligence. CodeRabbit will then suggest changes that can be made to increase the structure and reliability of the code. Giving the reviewer a chance to quickly scan these suggestions and make any changes that they deem necessary. For larger, more critical changes - CodeRabbit will flag them for a more detailed review from a member of your team. Suggestions will be made by utilizing an LLM (large language model), but actual changes must be approved and signed by the person reviewing the issue. CodeRabbit then discards any code that was used in the analysis, ensuring that data is not being stored or used to train their models. It’s extremely fast and convenient for teams that don’t have time to review code that doesn’t have any glaring issues. Through leveraging AI, the quality of the code reviews has increased substantially compared to what was previously available for teams. The application functions more like an active member of your team, instead of a static tool that doesn’t truly understand your code as a whole. By eliminating the need to review every small change, you’ll be given detailed feedback that can be immediately implemented. Resulting in faster development time and higher quality code being written. Check it out for yourself. It takes about a minute to set up through the @CodeRabbitAI site with GitHub integration. It also has a very generous FREE tier that comes with a 7-day trial for the Pro subscription. 👇