cubic ships code 60x faster with Claude

cubic, an AI-powered code review platform founded by former Instagram and Meta engineers, uses Claude to help engineering teams ship high-quality code faster in an AI-first development world.

Key results with Claude

• First review delivered in 2 minutes instead of 2 hours — 60x faster feedback cycle
• Teams ship code 28% faster after two weeks of using cubic
• 98% of AI-generated comments receive positive developer feedback

When AI coding creates new bottlenecks

As AI tools transformed software development, cubic founders Allis Yao and Paul Sanglé-Ferrière noticed code review becoming the new bottleneck. While developers could generate features at unprecedented speed, reviewing that code couldn't keep pace.

"Code review became the biggest bottleneck for engineering teams," said Yao, who previously led engineering teams at Instagram and Meta. "Before it was always about how quickly you could write a feature. Now, with autogenerated code, the focus shifts to quality—ensuring the architecture is sound, the code is bug-free, and it actually does what you intended."

This shift created entirely new challenges. Traditional code review processes, designed for human-written code, couldn't handle AI's rapid output. Even more concerning, developers began trusting AI-generated code without proper review, assuming it was correct. The very speed that made AI coding attractive was creating quality and oversight problems that existing tools couldn't address.

Selecting Claude for superior code understanding

cubic chose Claude Sonnet 4 for two critical capabilities: its ability to work with development tools and its well-calibrated confidence assessment. Claude's confidence calibration means that when it reports being 80% confident about something, it's typically correct about 80% of the time—making its confidence levels reliable indicators for teams.

Claude's ability to use tools enables cubic's unique approach to automated code review. "We give Claude essentially an IDE, just like a human would be reviewing code on their laptop," explained Sanglé-Ferrière. "It has a bunch of tools that allow it to navigate through the codebase and find problems."

Claude's confidence calibration also matches different teams' needs. "Different teams have different tolerances for what they like or what they don't," said Yao. "Having a model that can say 'I'm very confident in this but less confident in that’ is really important."

Reimagining code review as an AI-native experience

Claude powers cubic's approach to modernizing code review through several key capabilities:

• Intelligent file organization: Claude groups and orders pull request files by dependency relationships instead of alphabetical order, letting developers review code in a logical sequence from top to bottom
• Automated quality analysis: Claude runs comprehensive tests on code changes, checking for bugs and quality issues while learning from codebase patterns and user feedback
• Architecture visualization: When data flows change, Claude automatically generates architecture diagrams to show reviewers the broader impact
• Multi-language support: Claude delivers consistent code review quality across programming languages from TypeScript and Python to less common ones like Elixir
• Smart suggestions: Claude generates code improvement suggestions when confidence levels are high, helping teams maintain quality while moving faster

Transforming engineering velocity and code quality

cubic's AI-powered approach delivers measurable improvements for engineering teams. Teams using the platform ship code 28% faster while maintaining high quality standards, with first reviews completing in minutes instead of hours.

The impact extends beyond speed metrics. "We tell customers to do a two-week free trial and compare us against competitors," said Yao. "The real data is when people choose to buy us over other tools." The quality improvements are tangible. "We're catching more bugs and there's fewer false positives," she added.

For developers, cubic eliminates the mental overhead that traditionally slowed code reviews. Instead of scrolling through files trying to figure out where to start and how pieces connect, cubic organizes everything logically. "Developers don't even realize this is a problem until they experience cubic," said Sanglé-Ferrière. "You realize you don't need to do mental gymnastics to figure out what's going on because the AI has organized everything for you. You just scroll down, read the architecture diagrams and understand what's happening."

Building the future of AI-native development

As AI transforms software development, cubic expects fundamental changes in how teams work together. The traditional boundaries between writing and reviewing code will blur as AI changes development workflows. AI is also enabling more people to write code, including non-developers, which increases the need for effective code review tools.

cubic sees enormous opportunity ahead as AI capabilities grow. The company believes that even as AI becomes more sophisticated, code review will remain essential because software development requires collaboration and shared understanding across teams. As AI writes increasingly sophisticated code, cubic and Claude will continue building tools that help human teams understand, improve, and ship that code with confidence.