GitLab / agentic-ai

Introducing GitLab Credits (opens in new tab)

GitLab is transitioning from seat-based pricing to a usage-based model with the introduction of GitLab Credits, a virtual currency designed for the GitLab Duo Agent Platform. This shift addresses the limitations of traditional licensing, which often creates "AI haves and have-nots" by making access too expensive for light or occasional users. By pooling resources across an entire organization, GitLab aims to provide equitable access to agentic AI for every developer while ensuring costs align with actual consumption. ## The Shift from Seat-Based to Usage-Based AI * Traditional seat-based models are poorly suited for agentic AI, which can be triggered by background SDLC events rather than just direct user interaction. * The credit model allows every member of a Premium or Ultimate organization to use AI capabilities without requiring an individual "AI seat." * Usage-based pricing automatically offsets the costs of power users against lighter users, lowering the total cost of ownership for the organization. ## Mechanics of GitLab Credits * Credits function as a pooled resource consumed by both synchronous interactions (like Agentic Chat in the IDE) and asynchronous background tasks. * Supported capabilities include foundational agents (Security, Planner, Data Analyst) and specific workflows such as Code Review and CI/CD pipeline fixing. * The system integrates with external models like Anthropic Claude Code and OpenAI Codex, as well as custom agents published in the GitLab AI Catalog. * Each credit has an on-demand list price of $1, with volume discounts available for enterprise customers who sign up for annual commitments. ## Governance and Usage Controls * Administrators can monitor consumption through two dedicated dashboards: a financial oversight portal for billing managers and an operational monitoring view for administrators. * Granular controls allow organizations to enable or disable Duo Agent Platform access for specific teams or projects to prevent unexpected credit depletion. * Proactive email alerts are triggered when consumption reaches 50%, 80%, and 100% of committed monthly credits. * A sizing calculator is available to help organizations estimate their monthly credit requirements based on patterns observed during the platform's beta period. ## Transitioning and Promotional Access * Existing GitLab Duo Pro and Duo Enterprise customers can roll over their current seat investments into GitLab Credits with volume-based discounts. * As part of a limited-time promotion, GitLab is providing $12 in monthly credits per user for Premium subscribers and $24 per user for Ultimate subscribers. * Self-managed and GitLab Dedicated customers will gain access to these credit-based features starting with the 18.8 and 18.9 releases. For organizations looking to scale AI across the software development lifecycle, the credit-based model offers a more flexible and cost-effective path than rigid seat licenses. Current Premium and Ultimate subscribers should leverage their monthly promotional credits to baseline their usage before committing to larger annual credit bundles.

Announcing general availability for GitLab Duo Agent Platform (opens in new tab)

The GitLab Duo Agent Platform has reached general availability, marking a shift from basic AI code assistance to comprehensive agentic automation across the entire software development lifecycle. By orchestrating intelligent agents to handle complex tasks like security analysis and planning, the platform aims to resolve the "AI paradox" where faster code generation often creates downstream bottlenecks in review and deployment. ### Usage-Based Economy via GitLab Credits * GitLab is introducing "GitLab Credits," a virtual currency used to power the platform’s usage-based AI features. * Premium and Ultimate subscribers receive monthly credits ($12 and $24 respectively) at no additional cost to facilitate immediate adoption. * Organizations can manage a shared pool of credits or opt for on-demand monthly billing, with existing Duo Enterprise contracts eligible for conversion into credits. ### Agentic Chat and Contextual Orchestration * The Duo Agentic Chat provides a unified experience across the GitLab Web UI and various IDEs, including VS Code, JetBrains, Cursor, and Windsurf. * The chat utilizes multi-step reasoning to perform actions autonomously, drawing from the context of issues, merge requests, pipelines, and security findings. * Capabilities extend beyond code generation to include infrastructure-as-code (IaC) creation, pipeline troubleshooting, and explaining vulnerability reachability. ### Specialized Foundational and Custom Agents * **Foundational Agents:** Pre-built specialists designed for specific roles, such as the Planner Agent for breaking down work and the Security Analyst Agent for triaging vulnerabilities. * **Custom Agents:** Developed through a central AI Catalog, these allow teams to build and share agents that adhere to organization-specific engineering standards and guardrails. * **External Agents:** Native integration of third-party AI tools, such as Anthropic’s Claude Code and OpenAI’s Codex CLI, provides access to external LLM capabilities within the governed GitLab environment. ### Automated End-to-End Flows * The platform introduces "Flows," which are multi-step agentic sequences designed to automate repeatable transitions in the development cycle. * The "Issue to Merge Request" flow builds structured code changes directly from defined requirements to jumpstart development. * Specialized CI/CD flows help teams modernize pipeline configurations and automatically analyze and suggest fixes for failed pipeline runs. * The Code Review flow streamlines the feedback loop by providing AI-native analysis of merge request comments and code changes. To maximize the impact of agentic AI, organizations should move beyond basic chat interactions and begin integrating these specialized agents into their broader orchestration workflows to eliminate manual handoffs between planning, coding, and security.

Agentic AI, enterprise control: Self-hosted Duo Agent Platform and BYOM (opens in new tab)

GitLab 18.9 introduces critical updates designed to provide regulated enterprises with governed, agentic AI capabilities through self-hosted infrastructure and model flexibility. By combining the Duo Agent Platform with Bring Your Own Model (BYOM) support, organizations in sectors like finance and government can now automate complex DevSecOps workflows while maintaining total control over data residency. This release transforms GitLab into a high-security AI control plane that balances the need for advanced automation with the rigid sovereignty requirements of high-compliance environments. ## Self-Hosted Duo Agent Platform for Online Cloud Licenses The Duo Agent Platform allows engineering teams to automate sequences of tasks, such as hardening CI/CD pipelines and triaging vulnerabilities, but was previously difficult to deploy for customers under strict online cloud licensing. This update makes the platform generally available for these environments, bridging the gap between cloud-based licensing and self-hosted security needs. * **Usage-Based Billing:** The platform now utilizes GitLab Credits to provide transparent, per-request metering, which is essential for internal chargeback and regulatory reporting. * **Infrastructure Control:** Enterprises can host models on their own internal infrastructure or within approved cloud environments, ensuring that inference traffic is routed according to internal security policies. * **Deployment Readiness:** By removing the requirement to route data through external AI vendors, the platform is now a viable option for critical infrastructure and government agencies. ## Bring Your Own Model (BYOM) Integration Recognizing that many enterprises have already invested in domain-tuned LLMs or air-gapped deployments, GitLab now allows customers to integrate their existing models directly into the Duo Agent Platform. This ensures that organizations are not locked into a specific vendor and can leverage models that have already passed internal risk assessments. * **AI Gateway Connectivity:** Administrators can connect third-party or internal models via the GitLab AI Gateway, allowing these models to function as enterprise-ready options within the GitLab ecosystem. * **Granular Model Mapping:** The system provides the ability to map specific models to individual Duo Agent Platform flows or features, giving admins fine-grained control over which agent uses which model. * **Administrative Ownership:** While GitLab provides the orchestration layer, administrators retain full responsibility for model validation, performance tuning, and risk evaluation for the models they choose to bring. For organizations operating in high-compliance sectors, these updates offer a path to consolidate fragmented AI tools into a single, governed platform. Engineering leaders should evaluate their current model investments and leverage the GitLab AI Gateway to unify their automation workflows under one secure DevSecOps umbrella.