monday.com accelerates review cycles and improves code quality with Qodo

monday.com is a cloud-based work operating system that enables teams to plan, track, and collaborate on projects and workflows in one centralized platform. Built around visual, no-code building blocks like boards, dashboards, and automations, it is used by organizations worldwide to streamline collaboration and workflows. Founded in 2012, the company has grown to serve over 180,000 organizations globally.

The company’s R&D organization comprises approximately 500 developers spanning full-stack and DevOps engineering roles, who collectively maintain and evolve a complex technology stack that processes millions of daily user actions across the platform, demanding rigorous development practices and continuous innovation to ensure reliability at scale.

The Challenge

As monday.com scaled, its engineering teams faced the mounting complexity of maintaining code quality standards while preserving rapid development cycles. Their existing code review process relied on a combination of static code analysis, linter rules, and custom “danger rules” that, while effective at enforcing fixed standards, were limited to pattern matching. This approach couldn’t adapt to evolving coding patterns or catch context-dependent issues, leaving reviews heavily dependent on manual effort that was both time-consuming and inconsistent in capturing emerging best practices across the growing codebase.

monday.com’s engineering leadership sought to transform their development workflow by pursuing three strategic objectives:

1. Improve product quality through earlier bug detection in the development cycle,
2. Enhance pull request effectiveness while reducing the manual burden on senior engineers
3. Implement AI-based tools that could complement human expertise and scale intelligently with the organization’s growth.

The Qodo Solution

Qodo enhanced monday.com’s code review process by introducing an AI-powered layer directly into their CI pipeline, shifting from primarily manual reviews to an intelligent hybrid approach that combines human expertise with machine learning.

The platform automatically generates context-aware code suggestions, identifies potential issues before they reach production, and creates comprehensive PR descriptions, significantly streamlining the review workflow while elevating code quality standards across the organization.

To monday.com, what sets Qodo apart is its context enrichment capability that continuously learns from the larger codebase, historical developer decisions, and approved pull requests to provide increasingly relevant suggestions.

“By incorporating our org-specific requirements, Qodo acts as an intelligent reviewer that captures institutional knowledge and ensures consistency across our entire engineering organization,” said Liran Brimer, Senior Tech Lead at monday.com.

“This contextual awareness means that Qodo becomes more valuable over time, adapting to our specific coding standards and patterns rather than applying generic rules.”

Impact

Qodo now prevents an average of 800 potential issues from reaching production every month while saving monday.com developers approximately one hour per pull request. These metrics, achieved across monday.com’s 500-developer organization, translate to thousands of hours returned to innovation and feature development annually, while simultaneously strengthening code quality at scale.

Today, Qodo is deployed by default across monday.com’s entire engineering organization. By complementing human reviews, Qodo reduces the risk of overlooked issues, including critical security vulnerabilities. In one case, Qodo flagged where environment variables were mistakenly exposed through a public API, an issue that could have slipped past manual review.

“The security issue Qodo caught early on showed us we had gaps in our manual review process,” reflects Brimer. “Since then, Qodo has become a reliable part of our workflow.”

Key outcomes:

• Accelerated review cycles: Qodo’s automated PR analysis and contextual walkthroughs have reduced review time by an average of one hour per pull request, enabling engineers to focus on architectural decisions and business logic. Reviewers now engage with pre-analyzed, well-documented changes that highlight areas requiring human expertise.
• Quality gains without over-reliance: With an average of 800 potential issues prevented monthly, developers don’t see Qodo as a replacement but as an added safeguard. This dual-review model raises the overall quality bar without shifting responsibility away from engineers.
• Security and risk reduction: Beyond style and consistency, Qodo has proven capable of identifying meaningful vulnerabilities, adding an extra layer of trust in the safety of Monday’s codebase.
• Alignment across teams: By learning from historical PRs and team conventions, Qodo effectively codifies Monday.com’s engineering best practices, ensuring consistency across distributed teams and preserving institutional knowledge even as the organization grows and evolves.

monday.com’s implementation of Qodo demonstrates how AI-powered code review solutions can successfully scale engineering excellence without sacrificing velocity or developer autonomy. By integrating Qodo, monday.com transformed what was once a bottleneck—manual code review—into a strategic advantage that strengthens with every pull request.

The results speak to a broader truth about modern software development: as engineering organizations grow and codebases become more complex, traditional review processes alone cannot maintain the dual mandate of speed and quality. Qodo’s approach offers a sustainable path forward, one where AI amplifies human expertise rather than replacing it, and where institutional knowledge becomes embedded in the development workflow itself.