🦊 GitLab

Build software faster. The DevSecOps Platform enables your entire organization to collaborate around your code.

[🦊 GitLab @gitlab]

Every enterprise already runs a software factory, but most organizations have built theirs from separate tools for coding, planning, source code control, CI/CD, security, artifact management, and deployment.

As AI agents accelerate software development, that fragmentation creates more handoffs, breaks context, and makes it harder to trace changes, govern what reaches production, or measure the impact of AI investments.

GitLab is announcing the foundation for a governed software factory to help organizations optimize software development so they can move from intent to production with greater speed, governance, and visibility.

See what’s new 🧵

[🦊 GitLab @gitlab]

Ever had a build fail because a public repository went down? Been there. Never doing that again with Artifact Central caching our packages 🥳

Watch the full demo here to see how pulling the same packages took less than half the time 👉 https://t.co/JsnetOoDyZ

[🦊 GitLab @gitlab]

A little less pressure to keep up. A little more focus on moving forward together 🚀

@Steve_Yegge shares why AI adoption needs a human pace and how AI can help teams find a shared language.

[🦊 GitLab @gitlab]

AI agents are sending more and more code into review queues built for human-paced work.

A coding assistant can speed up code writing, but it can’t show you whether review, security checks, and release approvals can keep pace with all that extra code.

AI-native engineering is the practice of intentionally designing the engineering process so people and agents each do what they are best suited to. It starts with identifying delivery bottlenecks, then deciding how much autonomy agents should have and how to maintain control as you scale.

Read the blog to learn more: https://t.co/GDj7cXV5W3

[🦊 GitLab @gitlab]

Get every merge request in front of the right reviewer, faster.

Most organizations do not lack capable reviewers. They lack a consistent way to get each merge request in front of the right one. With Recommend Reviewers Flow, now generally available in GitLab 19.5, GitLab recommends the best individual reviewer when you create a merge request, based on workload, time zone, availability, and expertise defined by approval rules and CODEOWNERS. The flow explains why it chose each reviewer and lets you assign them in one click, so reviews start sooner and review load spreads across every qualified engineer.

Read the blog: https://t.co/UoqyCob1lO

[🦊 GitLab @gitlab]

GitLab Secrets Manager is now generally available.

Built on OpenBao, it keeps build-time and runtime secrets under the permissions and audit trail that govern your code. Each secret reaches only the jobs that declare it and fall within its scope.

Learn more. https://t.co/youvFTUdRl

[🦊 GitLab @gitlab]

GitLab has joined the Open Secure AI Alliance, hosted by the @LinuxFoundation, to support open approaches to AI security and responsible AI.

We’re looking forward to sharing the open-source tools and transparent practices we’re building to help teams use AI with greater choice, control, and trust.

Read more from our CISO Chaim Mazal: https://t.co/lwnH3gwLLg

[🦊 GitLab @gitlab]

The GitLab MCP server is now generally available.

Any MCP-compatible agent can run core GitLab workflows from the client your team already works in, with dozens of tools across code, merge requests, work items, and pipelines. Each action runs under your existing GitLab permissions.

Read the blog to learn more. https://t.co/BSTlCHeYac

[🦊 GitLab @gitlab]

A walking red flag in your workflow? An agent that acts first and explains later 🚩

Put it back in the loop. Some decisions still need your sign-off.

[🦊 GitLab @gitlab]

Speed you can trust, all the way to production.

With GitLab 19.5, you connect any MCP-compatible agent to GitLab from the client your team already uses. You keep secrets under your existing permissions and get every merge request to the right reviewer, faster.

Learn more about the 19.5 release: https://t.co/pzuvPwUTOB

[🦊 GitLab @gitlab]

Gemini 4 Argon is now available on GitLab Duo Agent Platform.

As AI models take on longer, multi-step work, teams need results they can trust. In internal evaluations, Argon completed 93.3% of GitLab’s software engineering benchmark tasks. Your engineers can delegate the work with confidence and spend their time reviewing the result.

Read the blog: https://t.co/KaCBym4Pb5

[🦊 GitLab @gitlab]

Commercial space companies are utilizing new AI tech to build faster and more efficiently. 🚀

Brian Butcher and Dami Alugo of Intuitive Machines talk about how they are using GitLab to get there, how AI is changing the way spacecraft are developed, and where the technology could go next.

Listen to the full episode: https://t.co/8KYziMwwjY

[🦊 GitLab @gitlab]

As AI agents take on more software development, source control needs to keep pace with the scale and concurrency of agentic workloads.

That’s why GitLab has been developing next-generation SCM for thousands of concurrent agents working against large repositories. We announced this work at GitLab Transcend in June, joined on stage by Nick G. from Anthropic’s source control team. Anthropic’s post today shows how quickly these demands are growing.

Read more on our blog: https://t.co/HARCigmfCJ

[🦊 GitLab @gitlab]

Gemini 4 Argon from @GoogleDeepMind is now available on GitLab Duo Agent Platform, across all tiers and deployment models.

Stuart Moncada, VP of Product Management at GitLab, shared why this matters for teams building with AI:

“As software development becomes more agentic, teams need models that can support long-running, multi-step work across all stages of the development lifecycle. Gemini 4 Argon is designed to help organizations bring AI into development, security, and operations while keeping it within established enterprise workflows and controls.”

[Google DeepMind @GoogleDeepMind]

Gemini 4 Argon is now globally available.

Built to solve your hardest problems from start to finish, the model brings frontier capabilities across coding, enterprise workflows, and cyber defense.

[🦊 GitLab @gitlab]

We are excited to recognize Dhairya Majmudar, a Level 3 contributor, as this month’s Notable Contributor!

Dhairya contributed to offline transfer and Organizations support for import, so that groups, projects, and their memberships can move between GitLab instances. Learn more here: https://t.co/sr9bU0K5tR

[🦊 GitLab @gitlab]

Want to see how GitLab Artifact Central actually works?

Tim Rizzi and Corinne Dent go deep on the architecture, the migration path, and what it means for teams building with AI agents.

Watch the full deep dive, then read more on the blog: https://t.co/JsnetOoDyZ

[🦊 GitLab @gitlab]

GitLab CEO @bstaples sat down with Darren Wilkes, CTO at COCC, to talk through how his team runs GitLab Duo, where hundreds of agents now carry engineering work from requirement to production with everything traceable back to source.

Watch the conversation:

[🦊 GitLab @gitlab]

✨ GitLab Transcend limited-edition merch is here!

Transcend is a moment to celebrate, and now we have merch to match.

From iridescent tanuki tees to travel accessories and customizable macropads, you don’t want to miss this drop. Quantities are limited.

Shop the collection.🛍️ https://t.co/4KMi2bz41x

[🦊 GitLab @gitlab]

Need it fast? Claude Haiku 5.5 is here.

The fastest model in the Claude 5.5 family is now on GitLab Duo Agent Platform, across all tiers and deployment models. Built for high-volume, speed-sensitive workloads.

Try it today.