As cloud project tracking software monday.com’s engineering organization scaled past 500 developers, the team began to feel the strain of its own success. Product lines were multiplying, microservices proliferating, and code was flowing faster than human reviewers could keep up. The company needed a way to review thousands of pull requests each month without drowning developers in tedium — or letting quality slip.That’s when Guy Regev, VP of R&D and head of the Growth and monday Dev teams, started experimenting with a new AI tool from Qodo, an Israeli startup focused on developer agents. What began as a lightweight test soon became a critical part of monday.com’s software delivery infrastructure, as a new case study released by both Qodo and monday.com today reveals. “Qodo doesn’t feel like just another tool—it’s like adding a new developer to the team who actually learns how we work,” Regev told VentureBeat in a recent video call interview, adding that it has “prevented over 800 issues per month from reaching production—some of them could have caused serious security vulnerabilities.”Unlike code generation tools like GitHub Copilot or Cursor, Qodo isn’t trying to write new code. Instead, it specializes in reviewing it — using what it calls context engineering to understand not just what changed in a pull request, but why, how it aligns with business logic, and whether it follows internal best practices. “You can call Claude Code or Cursor and in five minutes get 1,000 lines of code,” said Itamar Friedman, co-founder and CEO of Qodo, in the same video call interview as with Regev. “You have 40 minutes, and you can’t review that. So …
