GitLab in the AI stack

The business and what the filings show

GitLab sells a DevSecOps platform: one application for planning, writing, testing, securing and deploying software, priced per user, with an open-source core. Over its latest four quarters it reported $1.1B of revenue, +23% on the year before, at an 86% gross margin, the third-highest in the software layer, and a −9% operating margin, with free cash flow of $214M.

Its AI product is GitLab Duo, and the Duo Agent Platform, which its 10-K describes as orchestrating teams and AI agents that carry out tasks across planning, development, security and deployment. GitLab’s argument is that AI coding assistants make writing code faster, which moves the bottleneck to reviewing, testing, securing and shipping it, the steps its platform covers.

AI coding is also the clearest threat to per-seat developer tools: if fewer developers produce more code, seat counts could fall, and AI-native coding tools compete for the same budget. GitLab’s growth against the layer and its ability to charge for agents rather than seats are the test.

How AI shows up in the numbers

AI shows up at GitLab as Duo features and agents sold on top of its platform, and indirectly as more code flowing through the pipelines it runs. Its filings do not separate AI revenue, so the read is growth, gross margin as agents add compute cost, and how specific its earnings releases are about AI adoption.

For scale, GitLab’s revenue over the latest four quarters equals 0% of the $566B the five largest buyers spent on capital projects over their latest four quarters. Their capex rose +81% on the year before, while GitLab’s revenue grew +23%: slower than the spending, so it is capturing a smaller share of each new capex dollar, or more of its business sits outside the build-out.

How it talks about AI

In its latest earnings release, furnished to the SEC on September 1, 2026, GitLab mentioned AI 2 times in 786 words of narrative text, about 2.5 mentions per 1,000 words. Of its 2 sentences about AI, 1 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to March 3, 2025, AI mentions per 1,000 words went from 3.3 to 2.5.

Specific claims are easier to check against the numbers than general enthusiasm, which is why the share of AI sentences that carry a figure is worth watching alongside how often AI is mentioned. The sentences below are quoted from the release as published, after removing safe-harbor text and company boilerplate.

• “Expanded context for AI agents with GitLab Orbit, available in public beta, by connecting code, work items, pipelines, deployments, and production signals into a unified context graph, helping agents respond up to 11x faster with up to 45x fewer hallucinations in internal testing.”
• “As AI drives more software creation and more work through the development lifecycle, the context, security, governance and control GitLab provides become increasingly valuable.”

Source: earnings release (Form 8-K, Exhibit 99.1), September 1, 2026.

The trend in the numbers

Since the start of 2023, GitLab’s largest quarter by revenue was Q2 2026 at $286M, and its highest gross margin was 90% in Q4 2023. The latest quarter set the revenue record for the period.

Quarter by quarter, GitLab’s revenue grew +25% in Q3 2025, +23% in Q4 2025, +23% in Q1 2026, +21% in Q2 2026 on the same quarter a year earlier. Growth has been slowing, though from a high base.

Gross margin in the latest quarter was 84%, against 88% a year earlier, so more of each new dollar is passing through to costs. Operating margin moved from −8% to −20% over the same span. Over the latest four quarters it turned 21% of its revenue into operating cash flow and spent 1% of revenue on capital projects, against 1% a year earlier.

Where it sits in the stack

GitLab sits in the software and applications layer of the AI stack. It sits at the top of the stack, where revenue from end customers has to come from; its own spending flows to AI clouds.

Among the 27 companies in this layer on our map, it ranks number 25 by revenue and number 12 of 27 by revenue growth. Its gross margin of 86% compares with 78% for the layer as a whole, a sign that it keeps more of each dollar than its neighbors. The full layer analysis is on the software page.

Latest four quarters for 10-Q filers; latest fiscal year for 20-F filers. Companies under $100 million of revenue are left out.

Against the 27 US-listed companies in its layer, GitLab grew +23% over the latest year versus +19% for the layer combined, and converted 20% of revenue into free cash flow versus 33% for the layer. It is growing roughly in line with its layer.

What has to go right, and what could go wrong

What has to go right. AI has to increase the volume of software companies ship, making the review, security and deployment steps GitLab sells more valuable, priced in a way that doesn’t depend on developer headcount.

What could go wrong. If AI coding tools absorb more of the development workflow, or customers buy fewer seats as developers become more productive, GitLab could grow more slowly even as AI raises the amount of code written.

These describe the conditions the business depends on, as the filings show them. They are not a view on the stock.

Through the lens of Investing in AI

Rob May’s book offers six mental models for telling AI moats from traps. The one most useful for GitLab’s layer is “AI challenges traditional SaaS assumptions”: Per-seat pricing, zero marginal cost, smooth ARR curves, and automatic land-and-expand break down when software does work on your behalf. The mistake is not using SaaS instincts. It is using them automatically.

The question it asks of any company is: What work is this product actually doing, and how does pricing map to it? Applied to GitLab, the filings on this page are the place to start: the margin trend shows whether it holds scarce value or passes it through, the customer and financing disclosures show who it depends on, and the commitments show what it has promised before the revenue arrives.

Customers and concentration

US companies must disclose any customer that accounts for 10% or more of revenue, and foreign filers usually describe their largest customers. Concentration matters because a company’s growth is only as durable as the handful of buyers behind it, and in the AI stack those buyers are often the same few companies.

• “There were no individual customers whose revenue represented more than 10% of total revenue during the years ended January 31, 2026 , 2025 and 2024 .” 10-K, March 17, 2026

Commitments and backlog

• Backlog. GitLab reports $1.2B of remaining performance obligations, 1.1 times its revenue over the latest four quarters: contracted revenue not yet earned.
• Purchase commitments. $228M of unconditional purchase obligations as of January 31, 2026 (10-K): what it has contracted to buy from its own suppliers.

What to watch

GitLab’s next quarterly report will cover the quarter ending around October 30, 2026. Large companies must file a 10-Q within 40 days of a quarter’s end and a 10-K within 60 days of the fiscal year’s end, so the new figures should arrive by about December 29, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Revenue growth against the layer: AI should lift it if more code means more use of the platform.
• Gross margin, where the cost of running Duo would show.
• Any move from per-seat to usage or agent pricing.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from GitLab’s SEC filings, latest period ended July 31, 2026. Other companies: all company pages.