GitLab makes the platform that large companies use to write, review, test, and deploy software. Think of it as the organised workspace where a company's entire technology team operates. On Monday, it announced layoffs, a reduction in the number of countries it operates in by up to 30%, the removal of several layers of management, and a reorganisation of its engineering teams into roughly 60 smaller, more independent units. The exact number of jobs being cut will not be disclosed until a June 2 earnings call.
The stock dropped 8% after the announcement. That is not what usually happens when a company presents a bold growth plan. It is what happens when investors hear a growth story and do not fully believe it.
The scepticism is earned. GitLab's share price has fallen roughly 50% over the past year, even as the broader technology sector has largely benefited from AI excitement. The company grew revenue by 25% year over year as recently as late 2025, which is genuinely strong. But analysts at Morgan Stanley, Barclays, and Cantor Fitzgerald all downgraded the stock in recent months. The concern is not what GitLab has done. It is what it might be facing.
Here is the core problem. GitLab's business is built on the idea that organisations will always need more software, built by more developers, who all need tools to coordinate their work. AI is now writing a growing share of that code. If it writes enough of it, the number of human developers a company needs could shrink, and with it the number of software management seats GitLab can sell. That is the bear case, and it is not irrational.
The bull case, which GitLab's CEO Bill Staples is making explicitly, is the opposite. If AI makes software cheaper and faster to build, demand for software will explode. Every company that could not afford custom software before will build some. Every process that was not yet automated will be. More software means more pipelines, more deployments, more security reviews, more of everything GitLab manages. The market could get dramatically larger, not smaller.
Both arguments are coherent. The problem for GitLab is that it is making this bet from a position of competitive weakness. GitHub, which is owned by Microsoft, commands roughly 38% of the source code management market. GitLab holds about 16%. GitHub Copilot, Microsoft's AI coding tool, has 20 million total users and is deployed at 90% of Fortune 100 companies. GitLab's equivalent product, called Duo, only reached full general availability in January 2026, roughly five years after GitHub's first AI tools launched.
GitLab does have real strengths. It offers a genuinely integrated platform where security scanning, deployment, and AI assistance all live in one place, without needing to piece together separate tools. For organisations in regulated industries like financial services, insurance, or defence, that matters enormously. GitLab can run entirely inside a company's own infrastructure, meaning sensitive code never leaves the building. That is something GitHub's cloud-first model cannot easily match.
But the restructuring raises a question that GitLab has not answered clearly. If this is truly the largest opportunity in the company's history, why is the response to reduce headcount and pull back from 30% of your operating countries? The company says the savings will be reinvested. The June 2 earnings call will be the first real test of whether investors accept that story.
The broader pattern here is also worth watching. Atlassian, which makes workplace collaboration tools, cut 10% of its workforce in March 2026 using nearly identical language about AI investment. Block, the payments company, went further and cut closer to 40% of its staff. In every case, the framing was AI-driven efficiency. In most cases, the stock initially fell anyway. The market is getting better at distinguishing between companies that are genuinely repositioning and companies that are cutting costs and hoping the AI label provides cover.
For non-technology organisations that use GitLab or similar platforms to manage their own software teams, or who rely on technology vendors built on these tools, the signal is this: the economics of software development are changing fast, and the companies that manage that process are under real pressure to adapt. The tools your teams use today may look substantially different, or cost substantially more, within 18 months.