Scaling Git for the agentic software factory

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What happened

To search repositories and projects, login to gitlab. com . Platform Execution & Workflows CI/CD Source Code Management Agile Delivery Artifact Management Security & Governance Application Security Testing Governance & Compliance Secrets Management Supply Chain Security Context & AI Agentic Orchestration Context Graph Visibility & Measurement Explore the Platform Why GitLab One platform for speed with control across your software lifecycle.

Where the sources line up

Solutions Outcomes DevOps Modernization Security Modernization AI Modernization By size Enterprise Small Business Startups Industries Financial Services Public Sector Telecommunications Automotive Education Aerospace View all Solutions GitLab Security Standard Learn how to harden your software factory and let AI agents earn autonomy, without trading away security.

Practical impact for readers

GitLab is building next-gen source control for agentic workloads, combining machine-scale performance with context, security, and governance to deliver trusted software.

Who should pay attention now

AI agents are fundamentally changing the economics of software development. As the cost of producing code falls, the volume of changes moving through the software factory is accelerating beyond what infrastructure designed for human developers was built to handle.

What is still unclear

GitLab anticipated this shift and began developing next-generation source code management (SCM) to support thousands of concurrent agents working against large repositories. In June, we announced next-gen SCM at GitLab Transcend, joined on stage by Nick G. from Anthropic's source control team. We've continued collaborating on the technical challenges of agent-scale development, and in August we shared more of our architecture and early performance results.

Source notes

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