Why code review needs a telescope not a microscope

I'll be honest with you: when we started thinking about AI code review tools, we were frustrated. Not because there weren't enough options out there – quite the opposite. The market is flooded with AI-powered code review solutions that all seem to be solving the same problem in the same way. And that's exactly what bothered us.

Most AI code reviewers today are basically fancy linters with a GPT wrapper. They catch syntax errors, flag security vulnerabilities, and remind you about best practices. Don't get me wrong – these are important. But if that's all your AI code reviewer does, you're missing the forest for the trees.

We kept asking ourselves: why does code review exist in the first place? It's not just about catching bugs. It's about knowledge transfer, maintaining consistency, ensuring your codebase evolves in a sustainable direction, and ultimately, making your team better at what they do. Traditional AI tools were treating code review like a checklist, when it's actually a conversation.

That's why we decided to build something different.

Understanding Context, Not Just Code

Here's what drives me crazy about most AI code review tools: they look at your code in isolation. They analyze the pull request you just submitted without understanding what your application actually does, what problems your team is trying to solve, or what architectural decisions you've made over the past six months.