GitLab Expands Access to Agentic AI Across Lifecycle

GitLab Inc. has announced the release of GitLab 18.10, introducing enhanced agentic AI capabilities designed to streamline software development and reduce bottlenecks across the DevSecOps lifecycle. The update focuses on making AI-powered features more accessible, cost-effective, and practical for organizations of all sizes As AI-assisted coding accelerates code creation, development teams are increasingly challenged by the numerous tasks that follow, such as code review, testing, and security validation. GitLab addresses this shift by embedding AI deeper into these workflows, helping teams move faster from code creation to deployment.

A key highlight of the release is the broader availability of the GitLab Duo Agent Platform. Organizations using the GitLab.com free tier can now access these capabilities through a shared credit-based model. Instead of per-user licensing, teams can purchase GitLab Credits on a monthly basis, allowing all members within a group to use AI-driven features. A centralized dashboard provides visibility into credit consumption, enabling organizations to track usage and manage costs effectively.

GitLab has also introduced more affordable agentic code review capabilities. Manual code reviews often create delays in development cycles, especially in large or fast-moving projects. The new automated system reviews merge requests across repositories by analyzing code, pipelines, and security policies in context With a fixed, low-cost pricing model, organizations can scale code reviews across all changes, reducing delays and improving overall efficiency.

In addition to improving development workflows, GitLab 18.10 enhances security operations. The platform now includes general availability of AI-driven false positive detection for static application security testing (SAST). After each scan, the system evaluates high-severity findings and assigns a likelihood score indicating whether an issue may be a false positive. This helps security teams prioritize real risks more effectively while maintaining control over final decisions.

By integrating AI into both development and security processes, GitLab aims to simplify adoption while maintaining trust and transparency. The platform connects AI activity directly to software delivery outcomes, giving organizations a clearer understanding of how automation contributes to productivity and cost savings With this release, GitLab continues to evolve its DevSecOps platform into a more intelligent, end-to-end solution enabling teams to scale development, improve security, and accelerate innovation in an increasingly AI-driven software landscape.