cubic is an AI-powered code review platform that automatically reviews PRs and gives human reviewers superpowers. It’s tool of choice for fast-moving teams like cal.com and n8n.
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Best
Thanks for sharing this with us. It is the best than others
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I'm really impressed with the features of mrge, especially the AI-powered code review that can pick up patterns and leave comments directly on changed lines. The human-friendly review workflow is also a game-changer, making it easier for developers to review PRs quickly and efficiently. I'm excited to see how mrge can help streamline our code review process and improve the overall quality of our codebase
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I love how mrge is designed to augment human code reviews, rather than replace them. The AI review is a great way to catch subtle bugs and patterns, but at the end of the day, it's still up to human reviewers to make the final call. The platform's focus on making human code reviews easier is spot on, and I think it's going to make a big difference for teams like ours who handle a lot of PRs every day.
Love the focus on empowering human reviewers, not replacing them. Curious though—how does mrge handle highly domain-specific code where patterns aren’t obvious even with full repo context?
@shreyans_assistiv Right now, mrge learns from both your codebase and your team’s actual feedback—so when someone replies to an AI comment (“good catch” / “not relevant for our product”), mrge picks that up and gets better at handling your specific patterns over time. It's not just a generic model; it adapts as your team reviews code.
For really niche or domain-specific logic, we see the best results when teams quickly flag (or correct) anything that’s off—so the model gets direct signals about what matters for your code, vs. just guessing from repo context.
TL;DR: You absolutely can teach it as you go, and the more your team interacts, the sharper mrge gets for your unique codebase!
Congrats on launching mrge, Paul and Allis. Surely it will be a time saver.
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Wow, this looks incredibly promising! 🚀 With AI-generated code becoming the norm, reviewing subtle bugs is getting harder, and I love how mrge tackles this with a thoughtful, human-first approach. The idea of grouping changes logically and providing visual highlights sounds like a real game-changer for faster, safer shipping.
This is 🔥. The focus on making human code reviews faster and more thoughtful really hits home. Love the design inspiration from tools like Linear—feels like that’s exactly what code review has been missing. Excited to try mrge with our team!
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Mrge has revolutionized the traditional code review process, transforming it into a more efficient and streamlined experience for developers. Typically, code reviews can be a time-consuming and often cumbersome task, requiring multiple iterations and back-and-forth communication between team members. However, with Mrge, this process is simplified, allowing developers to focus more on coding and less on administrative overhead.
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Thanks for sharing this with us. It is the best than others
I'm really impressed with the features of mrge, especially the AI-powered code review that can pick up patterns and leave comments directly on changed lines. The human-friendly review workflow is also a game-changer, making it easier for developers to review PRs quickly and efficiently. I'm excited to see how mrge can help streamline our code review process and improve the overall quality of our codebase
I love how mrge is designed to augment human code reviews, rather than replace them. The AI review is a great way to catch subtle bugs and patterns, but at the end of the day, it's still up to human reviewers to make the final call. The platform's focus on making human code reviews easier is spot on, and I think it's going to make a big difference for teams like ours who handle a lot of PRs every day.
AskCodi
Love the focus on empowering human reviewers, not replacing them. Curious though—how does mrge handle highly domain-specific code where patterns aren’t obvious even with full repo context?
cubic
@shreyans_assistiv Right now, mrge learns from both your codebase and your team’s actual feedback—so when someone replies to an AI comment (“good catch” / “not relevant for our product”), mrge picks that up and gets better at handling your specific patterns over time. It's not just a generic model; it adapts as your team reviews code.
For really niche or domain-specific logic, we see the best results when teams quickly flag (or correct) anything that’s off—so the model gets direct signals about what matters for your code, vs. just guessing from repo context.
TL;DR: You absolutely can teach it as you go, and the more your team interacts, the sharper mrge gets for your unique codebase!
Jupitrr AI
Awesome. Congrats on the launch @paul_sangle_ferriere1
Congrats on launching mrge, Paul and Allis. Surely it will be a time saver.
Wow, this looks incredibly promising! 🚀 With AI-generated code becoming the norm, reviewing subtle bugs is getting harder, and I love how mrge tackles this with a thoughtful, human-first approach. The idea of grouping changes logically and providing visual highlights sounds like a real game-changer for faster, safer shipping.
Kalyxa
This is 🔥. The focus on making human code reviews faster and more thoughtful really hits home. Love the design inspiration from tools like Linear—feels like that’s exactly what code review has been missing. Excited to try mrge with our team!
Mrge has revolutionized the traditional code review process, transforming it into a more efficient and streamlined experience for developers. Typically, code reviews can be a time-consuming and often cumbersome task, requiring multiple iterations and back-and-forth communication between team members. However, with Mrge, this process is simplified, allowing developers to focus more on coding and less on administrative overhead.