AI made writing code dramatically faster, but the work between opening a merge request and merging it has stayed almost entirely manual. Assigning reviewers, addressing feedback round after round, untangling conflicts, rebasing before merge — each step still requires a developer's attention. The bottleneck moved but the tools didn't adapt.
GitLab 19.0 changes that. Developer Flow now extends across the full MR lifecycle: a single AI agent that addresses reviewer feedback, resolves conflicts on long-running branches, researches unfamiliar codebases, and splits MRs that grew too large. Paired with autonomous merge conflict resolution and one-click rebase and merge, it cuts the manual work between opening an MR and merging it.
Developer Flow is part of a new category of AI coding tools. The first wave accelerated the next line of code. The second wave gave developers a chat window. What's emerging now is different: agents that participate across the work, not for a fixed moment. Developers can now stay above the loop, delegating and reviewing while the agent handles execution.
We launched Developer Flow last year to turn an issue into a merge request. Automating the repetitive setup work between "here's what needs to be built" and "here's an MR to review" was only a starting point. But it was one task, and once the MR existed, the work of iterating on it was still entirely manual.
This new iteration of Developer Flow picks up the rest of the manual work. An agent that does the work a developer would otherwise do now extends across the lifecycle of an MR.
Here’s what Developer Flow looks like in practice:
Triggers at any stage. Start Developer Flow from an issue with the Generate MR button, assign the Duo Developer service account directly to an issue or MR, or invoke it from any discussion thread on an issue or merge request with the new @mention trigger. The agent picks up the conversation and iterates on the same MR, instead of producing a new one you have to reconcile.
Handles the work that surrounds the code. Developer Flow can now address reviewer feedback across multiple rounds in the same MR, resolve merge conflicts on long-running branches, research an unfamiliar codebase or evaluate an approach and report back, split an MR that grew too large, and implement features from scratch.
Is rebuilt to take actions across the entire lifecycle. Under the hood, Developer Flow is now a single agentic loop with a full developer toolset (read, grep, edit, run commands) that decides for itself which to use and when. More importantly, it's the architectural foundation that lets a single agent participate across the whole MR lifecycle.
Includes the proper project setup to be able to go further than AI coding tools. Developer Flow reads AGENTS.md for what isn't in the code: non-obvious bash commands, project conventions, environment quirks, and architectural decisions the agent needs to get things right the first time. agent-config.yml prepares the coding environment with the right dependencies, tooling, and configuration so the agent can run tests, execute pre-commit hooks, and close the loop before it commits. It is how you give the agent a machine that is ready to go, so the output matches your standards instead of creating rework.
You stay above the loop: steering, reviewing, deciding. The agent handles execution.
The new Developer Flow capabilities are available with GitLab Duo Agent Platform on Premium and Ultimate.
Merge conflict resolution is one of the most painful recurring tasks in an MR workflow, and the more complex the code is, the more likely it is for bugs to emerge. Resolving a conflict means reconstructing the intent of two branches at the same time, in your head, in a text editor, with no tests running. For teams managing backports and cascading MRs across multiple release branches, this isn't an occasional annoyance. It's a recurring tax on delivery velocity.
In GitLab 19.0, you can hand that work to an agent without leaving the MR. The Resolve with Duo button (now in beta) appears directly on the MR conflict page and in the merge checks widget.
The agent reads the MR's intent, looks at both branches, picks a resolution strategy, edits the conflicting files, commits, and pushes the fix. When the agent is done, it leaves a comment summarizing the conflict it found and the path it took to resolve it, so the next reviewer doesn't have to reverse-engineer the decision, and the audit trail stays intact. If the agent can't resolve the conflict safely, it tells you that instead of guessing.
The capabilities above handle the work inside an MR. Another 19.0 feature removes friction at the end of the workflow when you merge the MR: One-click rebase and merge (now in beta).
For teams using semi-linear history or fast-forward merge methods, rebasing before merge used to be two clicks with a wait in between: rebase, watch, come back, merge. Now it's one. This feature is available across Free, Premium, and Ultimate tiers.
With all of these capabilities, AI handles the judgment-heavy work: writing code, addressing feedback, and resolving conflicts. Automation handles the mechanics, such as rebasing before merge. They're different capabilities aimed at the same outcome: less manual work between opening an MR and merging it, and less of the developer's day spent on the parts of the MR that shouldn't need their attention.
Current GitLab customers can experience the benefits of Developer Flow by starting a free trial of GitLab Duo Agent Platform. If you’re already on Premium or Ultimate with Duo Agent Platform, you can use Developer Flow on your next merge request today, regardless of which version you are on. If you're on a version earlier than 19.0, you may need to set up the mention trigger manually to use the @-mention workflow.
If you are already using GitLab in the Free tier, you can sign up for GitLab Duo Agent Platform by following a few simple steps.
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