Executive Overview: GitLab reported a strong second quarter with revenue of $235.96 million, up 29% year over year, and non-GAAP operating income of $39.6 million, equating to a 16.8% non-GAAP operating margin. The company maintained full-year revenue guidance of $930–$942 million while raising profitability, underscoring disciplined growth execution amid a broader go-to-market (GTM) transformation. Gross margins remained best-in-class (non-GAAP gross margin at 90%), and free cash flow reached $46 million (20% of revenue), highlighting the durability of GitLab’s land-and-expand model and scalable SaaS footprint.
Strategic Positioning and Growth Engine: Management reinforced a dual GTM approach—sales-led and product-led growth—tied to a broad AI-enabled roadmap. Highlights include two parallel tracks to accelerate first orders and accelerate value realization, a newly appointed Chief Product & Marketing Officer, Manav Khurana, and a portfolio expansion that includes GitLab Ultimate (53% of ARR) and Duo (AI-enabled agent platform). The company cited robust customer momentum, with 10,338 customers generating ARR of at least $5,000 and 1,344 customers with ARR above $100,000, while DBNRR stood at 121%. Near-term guidance reflects continued strength in enterprise, tempered by SMB softness.
Outlook and Key Risk Factors: Q3 revenue guidance of $238–$239 million implies ~23% YoY growth; FY2026 revenue guided at $930–$942 million (approximately +24% YoY). Management noted incremental softness in SMB could persist through the year. The China JV (Jihu) remains a headwind in the modeling of expenses for FY2026, with ~$18 million of Jihu-related costs anticipated. Investors should monitor the GTM transition progress (six-to-nine month ramp for new enterprise sellers; adoption of product-led growth to broaden self-serve channels), Duo usage monetization (hybrid seat-plus-usage model), competitor dynamics in AI-assisted development, and the ongoing impact of macro conditions on SMB budgets. Overall, GitLab remains well-positioned as a cloud-agnostic, model-neutral DevSecOps platform with embedded AI capabilities and a growing ecosystem of strategic partnerships, poised to capture accelerated value from AI-native software development.