Good morning. Day four of the Morgan Stanley TMT conference. Keep the presentations going. We're super thrilled to have the management team from GitLab, CEO Bill Staples and new CFO, Jessica Ross. Bill, Jessica, thank you for joining us at the TMT conference. Absolutely. Thank you so much. Great to be here. Awesome. Before we get into the discussion for important disclosures, please see the research disclosure website at www.morganstanley.com/researchdisclosures. With that out of the way, Bill, I wanted to sort of level set the story and, you know, give us a sense of what the problem that GitLab solves for customers. Maybe we start with there and then a couple of follow-ups. Yeah. For those who are new to GitLab is an intelligent orchestration platform for software engineering. That's our new positioning that we just launched about a month ago. For the last decade, what we've provided organizations is the ability to manage their entire software life cycle in one unified platform. Historically, this space has been very fragmented. Developers have chosen lots of tools, a blend of both open source and commercial tools to do specific tasks to build software. Everything from, you know, the tools they use to plan, the tools they use to code, the version control systems that they use, the build systems that they use, the testing systems, the deployment systems, and so forth. There can be, in any given enterprise, a dozen or more tools to accommodate those tasks. What GitLab offers is one unified platform with an opinionated software engineering process that helps them take their code from planning all the way through deployment, and it's had proven ROI. Last year, we launched a independent survey that showed six-month payback period for our Ultimate product and 483% ROI in the first three years. That is the foundation that we're building on. We just announced this last quarter, just a few days ago on earnings, $1 billion in ARR. We delivered 26% revenue growth year-over-year last year. Do you want it? You wanna jump in with the [inaudible]? I can jump in there, yes. No. We just delivered $955 million in revenue, which was 26% year-over-year growth. We delivered $220 million in free cash flow, which is an 83% increase year-over-year, and 7 percentage points of margin expansion. Excited our customers are viewing us as more strategic to their core operations than ever before. Our million-dollar customer cohort grew 26% year-over-year. Our 100,000 customer cohort grew 18%, and Ultimate is now 56% of our ARR, and we also just announced our first-ever Share Repurchase Program. No, that's fantastic. Bill, I was wondering also, when we think about this part of software, you know, the software delivery life cycle, I think there's a lot of confusion on, like, what goes. You mentioned that there's, you know, a dozen plus different workflows. Coding is sort of one of them. Can you give a sense of, like, in terms of getting from idea to the software in the hands of your customers, how much of that is coding versus the workflows that you automate? Yeah. As we've done multiple surveys on this, there's other sources as well. The best estimates I've seen are between 10%-20% of the time developers spend, they spend writing code. The other 80%-90% is spent doing all of the other tasks around that code, that's where GitLab is today. We've never provided coding tools specifically, like an IDE or, you know, a code authoring environment. We've provided all of the things surrounding the code and the process or flow by which that code gets pushed all the way through to production. When you think of the, you know, you've been CEO for, you know, over a year now, can you share the insights that you've learned in terms of the pace of change that's happening in this market and how you sort of think about GitLab evolving with that pace of change? Yeah. You know, we've seen obviously this explosion in code authoring. What's interesting, I've spent about 30 years building software, with engineering teams and often with vendors like Microsoft, where I spent a lot of time in their developer division building tools for developers. I've studied the space a long, long time, and I'll say a couple things about what we're seeing today. First thing I would say is it's definitely the most fast-paced, innovative time that I've experienced in 30 years of building software. Every single day, every single week, there are new technologies, new tools, new innovation patterns emerging with the help of AI, which I think are really exciting. That's leading to this explosive growth in new techniques, new tools, new things to try. That pattern is actually age old. At least as long as I've been around, the code authoring space has always been very fragmented. There's always been different ideas and ways of doing that. Everything from, you know, very old open source tools. In fact, some of my developers in GitLab still use Emacs and Vi and Vim, which maybe some of you who've been around this space know that those were built 30+ to 40 years ago, something like that, in open source. Everything from that all the way to the latest, you know, coding agents like Claude Code, and everything in between. That fragmentation is a natural part of the developer community, and I think it will always be that way. That's part of just a developer preference in terms of having a tool that's fit for purpose for how they want to work. What's really important about this though is one of the evolutions that's happening is more code is getting generated. That code is now creating more bottlenecks downstream. The code reviews, the ability to secure that code, ensure it meets the engineering and organization's business standards, make sure it's compliant, make sure that the organization trusts the code. In particular, since it's not a human that they're employing to build it, but rather an independent agent that's autonomous and potentially not trusted, they need to have auditability. They need to have governance. They need to have control over the code even more than they have in the past. What we see in GitLab is it's pretty interesting that all of our customers are adopting these various tools. It's an and. This is not in any way impacting GitLab other than it's actually driving more engagement than ever. A couple of days ago, we shared, for example, our CI/CD pipelines are up 35%-45% year-over-year. The number of secure projects that customers are creating inside GitLab Ultimate are up 60% year-over-year. All of that code getting generated is actually driving more engagement in GitLab and more value delivery. Our business model today didn't anticipate this. It's a seat-based model. Customers get unlimited platform access per seat. We're happy that we can provide that additional value delivery to them. What we're now doing to help accelerate the rest of the lifecycle is bringing agentic AI across every task. Just like we've seen the success with the Claude Code and other tools for code authoring, we just launched seven weeks ago what we call Duo Agent Platform that offers agentic AI across the software lifecycle so that customers can intelligently orchestrate their entire software delivery. Yeah, that's an important point. You're seeing more usage, higher velocity usage than you've ever had before. The game is how we capture that value. I want to revisit that topic. Before, let's also revisit, you just reported earnings this week. There's a couple of themes coming out of that. Jessica, as you mentioned, bookings was really strong. Your momentum with the large customers in Q4 was particularly strong. The trend line of the multi-year trend line of bookings has been slowing down. Can you talk about some of the forces weighing on growth, particularly for your Premium customer base? Bill, can you speak to the sort of five-point action plan that you are going to be putting in place or have already started to put in place to reinvigorate growth of the business? Yeah. Yeah. As I shared in my FY 2027 guide, there's a few components as we're thinking about growth deceleration going into FY 2027. Majority of our revenue is ratable, which means that the revenue we're recognizing today is based on booking trends that happened two, three years ago. One of the things that we shared in our call is that bookings have not paced with revenue growth over the past three years. There's an element as we're thinking about growth deceleration that is purely math and nothing that we can change operationally in there. There's also some elements of some one-time we had announced a couple of years we implemented a pricing increase on our Premium product and have been benefiting from some of those tailwinds over the past couple of years. That's also flowing through to FY 2027. I think going in last quarter, we did have strong bookings, but there was also some pressure that we saw coming out of the government shutdown in Q3. We only saw a partial recovery in Q4 as well. We've really identified this price sensitive cohort that makes up about 20% of our ARR that especially with budget proliferation and a lot of concepts and choice, there's been some more budget pressure there that we are addressing through some very specific ways to increase value to that cohort. Let me talk about the growth ahead. As Jessica mentioned, we've studied the business deeply to understand that bookings pattern. Why hasn't bookings kept pace scaled with revenue? We've identified five specific areas that we believe we need to invest in to reaccelerate bookings, which then would have a corresponding impact on revenue in the coming years as the ratable revenue model kicks in. The first area we started investing in last year, it's first orders. If you look at GitLab, it's historically a very strong land and expand business. In fact, we shared a few quarters ago, our 2016 cohort that landed has expanded 100x, if you can believe it, 100X. Every cohort since continues to expand about the same rate. Many of those customers have landed historically at very low contract sizes, $5,000 and less, but then expand 100x. As we study the first order pattern, we identified that first orders had also been decelerating over the last couple of years. The root causes of that are pretty clear. The sales force had always taken a more general field approach to both land and expand, meaning there was no specialization. The sellers were able to fulfill their quota any way they could. As the business grew larger and as we moved up market, the easiest way to meet your quota is to do a large expansion. Without that dedicated focus on first order, as well as the shift up market, some of the product-led growth initiatives as well, we have a very large and vibrant open source community, also didn't get the care and attention that we think they deserve. Our first focus here is on re-accelerating first orders. The good news is in FY 2026, we already stabilized first order growth, so it had been decelerating for multiple years. On the sales-led side in Q2, the first orders had stabilized. We also then in Q3 and Q4 announced that we're putting a dedicated first order team in place on the sales organization for the first time with compensation that's aligned specifically to landing new logos. Now we have a global leader in place reporting to the CRO. We've got four regional leaders in place, and we're rapidly hiring and onboarding sellers there. For FY 2027, we see a path to sustained re-acceleration on first orders. In Q3, we also brought in a new product and marketing leader who has the entire funnel from top of funnel all the way through product conversion inside the product for monetization. They also have put in place a set of improvements in that funnel that have led to stabilization and the beginning of reinflection on product-led growth, new logos. Mm-hmm. That's super important because every time we bring a new customer in, it expands the cohort of those who we believe will grow with us for years to come. That's number one. Number two is as we looked at bookings growth, we also saw a really interesting correlation between our investment in sales capacity and the bookings growth itself. They're very highly correlated over multiple years. We believe that that represents a supply constraint to the increasing demand for GitLab. We see, again, increasing demand in terms of first orders. We see an expanding TAM with AI, and we wanna have the capacity to go after that with full focus. We began expanding the sales and marketing envelope and hiring in FY 2026. We enter now FY 2027 with the highest capacity we've ever had. We see line of sight to a Q3 step function increase in terms of productive capacity. We're excited about that as a growth lever. Number three, as we studied bookings, we realized one of the things that's been trending as well is customer feedback around the pricing and packaging. Customers are saying they want to do more with us. We have really two coarse-grained products, Premium and Ultimate. Premium at $29 per user, Ultimate at $99 per user. It's a 3x jump for a lot of capability. They have been requesting for some time more granular ways to opt into value. We believe the right way to do that is to start introducing new monetizable SKUs this year as additional value points and additional monetization levers. We've announced artifact management as one very commonly requested capability that customers today have to go to outside vendors to fulfill. We have their source code. We build their binaries. We don't store them today. They're saying, "Why don't you just store those inside GitLab? Give me the versioning and the signing, right inside GitLab. I will pay more for that." We're gonna deliver that this year, and they're excited because we're gonna meet them where they are along with the rest of the platform. They're gonna be able to run that on-premise in their own environment, in air-gapped environments, as well as in the cloud. The choice is theirs. Another one that we're delivering is Secrets Management. This is really important because every bit of software has embedded tokens in it that connect to various systems, and to do that securely is super important for the safety of the business, and we have not provided a solution there. We've referred them to external parties. We're gonna have a paid solution directly within GitLab. We see multiple other opportunities, I won't go into all of them, in addition to GitLab Duo Agent Platform that we just launched for additional monetization in FY 2027. The fourth one is around the price-sensitive cohort that Jessica just described a little bit. There is a cohort of customers that we raised prices on about three years ago by 50%. They went from $19 to $29, we did that at a time unknowingly when the AI coding tool boom happened. That as well as other AI tools that those companies are wanting to spend money on, puts pressure on their ability to expand with us or to upgrade to Ultimate. We're asking for more price. We're not necessarily delivering more value in the last several years. To address that, we're doing multiple things. First, we're including credits to our new agentic platform for every Premium user. They now get $12 in included credits to explore and hopefully fall in love with Duo Agent Platform before they have to make any kind of commitment or pay for any additional value. We think that's a significant investment in their value. Second thing we're doing is we're adjusting coverage ratios to give them more connection to GitLab. Historically, we've been pushing more and more up enterprise. We're gonna continue to invest there. Adjusting a little bit more to give them additional connection points. We've had some reps with hundreds of customers. We're gonna bring that down so that they have. You know, someone that they can contact, as well as additional technical services to get adoption and value realization better. That should also stimulate growth in that price-sensitive cohort. Finally, we're making the add-on packages also available to them. Rather than have to step up 3x to get to Ultimate, they can buy the artifact management. They can buy, you know, additional capabilities at incremental price. The fifth and final one is Duo Agent Platform. You know, historically, we launched a few years ago a Duo product line, and we focused on specific AI use cases that we thought would be interesting to our customers. What we realized last year is that agentic was the future of AI, and we needed to build a platform approach that could unlock thousands of use cases, and that customers can adopt and use for any task across the life cycle. Rather than build those as turnkey use cases one at a time, we embedded AI directly into our platform, and we've now launched that six, seven weeks ago, and customers now have access to multiple things that really can accelerate their entire software life cycle. For example, we provide out-of-the-box agents, as well as deeply integrated Claude Code and Codex agents, right inside of GitLab. They can apply those agents to any phase of the software life cycle, to planning, to CI, pipeline creation, to troubleshooting those pipelines, to analyzing security vulnerabilities, and everything else. Finally, we also provide a stitched context for all of the life cycle data that's inside GitLab. Not just your code, but all of the capabilities that you interact with and use within GitLab are being stitched together as a service that can, in our testing, accelerate agentic outcomes at higher quality and at lower cost. Really excited to bring that to market and, you know, excited to see the adoption ahead. Awesome. One, follow-up question. On the kind of new add-on module capability, are both Premium customers and Ultimate customers, are they gonna be able to, you know, buy the artifact management capabilities just in terms of how you're sort of pricing that or making that available? Absolutely, yeah. They get the incremental value for incremental cost without the big steps required. Excellent. Jessica, Bill just laid out a strategy to reinvigorate growth. It's gonna require some investment. In the context of your margin guide, it did come down about 400 basis points versus what you delivered in fiscal year 2026. Can you speak to the factors driving the margin guidance? How will you know, and when will you know that the investments you're making will generate the return you're looking for? No, thank you. That's a great question. I would just step back again and frame this as a year that we are viewing as investment and execution for long-term growth. As you think about that step down in margin starting from the top of the P&L, I look at gross margin. There's about 300 basis points of margin evolution that's happening there. Some of that, and there's really two factors. The first, when we IPO'd, we disclosed that with the shift of and growth of our SaaS business, we would expect margins to evolve closer to 85%. You know, in 2023, SaaS was about 22% of our business. It's now 32% of our business. Some of that is intentional with growing that business as intended. The second part, as Bill just shared, is we launched Duo, which is our AI product. That comes with a higher cost structure. This is a year, again, of investing as we are turning pilots into production and growing that business. That accounts for, you know, the rest of that gross margin. Then kinda going down to P&L, I also shared with our earnings a very clear capital allocation strategy. Our number one priority is organic growth, R&D, sales and marketing, and then G&A. With the priorities that Bill laid out, there's an investment cost in there. I also wanna be clear, like one of the reasons that I joined this business is because it's been very disciplined in how it's grown over the past, you know, since inception. We've delivered 1,700 basis points of margin expansion over the past two years. With these investments, we're monitoring them very closely internally. There's an expected ROI, but that muscle of margin discipline is not going away. I wanna come back, Bill, to the question around capturing value. Wherever we land on, you know, what's gonna happen to developer seat count, I actually think it's gonna be, we're gonna see more developers. Wherever we land on that debate, I think there's no debate that there's just a ton of software being developed and created. When you think about these dynamics through the lens of a pricing model, market seems to be shifting towards a hybrid pricing model combining both seats and usage. With Duo Agent Platform being the clearest example of that for GitLab. Can you share the aspects of the pricing model when it was specifically with respect to the Duo Agent Platform, and how are you striking the balance between facilitating adoption and usage and then ultimate monetization? With GitLab Duo Agent Platform, we now have that hybrid model. It's seats plus credits, usage on credits. The way it works is, for every Premium and Ultimate user, we've decided to make a promotional credit available for every user. They get $12 in credits as a Premium user. They get $24 in credits as an Ultimate user. We've done that because we wanna remove all friction from adoption. They don't need anything other than a version of GitLab that supports GitLab Duo Agent Platform, and they need to unlock Duo. They can start using the agent and getting value. Once they've reached the limit on the included credits, they can make a choice. By default, they can opt into on-demand credits, where they pay effectively $1 per credit, and they can use those as many as they want at any time, and we bill them monthly on demand for those credits. If they want an additional discount, this is where our salespeople can come in, and we'll take that as a product qualified lead. They can come in and say, "Hey, I see you're spending this much on on-demand credits. I can give you a discount." If they're willing to commit to a monthly minimum number of credits, then they earn a discount on credits themselves. The other really important thing here to realize is, we believe our pricing model is more transparent and fair versus other AI alternatives at the moment, in that when you make a monthly commitment, you're making it on a shared pool of credits that the entire organization can depend on. Rather than having a per-seat upfront price and then charging you overages on top of that, you're buying a shared pool, and you can spread the distribution of usage across the entire organization. That's definitely a unique angle to pricing. A lot of the investor conversations that I have when it comes to GitLab and broadly this part of software kind of relates to competition and competition from AI startups as well as some of the research labs. I'd be glad to get your perspective on are the startups focusing more on the code generation agent code development, or do they expand beyond code assistance, the broader software development workflows that you guys play in? Can you speak to the defensibility of GitLab on the potential for some of the AI natives and the research labs to move into expand beyond code development into more of the CI/CD workflows and the other areas that GitLab's involved in? I get this question a lot, I think it's easy to confuse if you're not deep into technology what the AI startups and AI natives are doing versus what GitLab does and how they relate. The best analogy that I've heard and that I share often is to think about it like our bodies. You should think about agents and AI as like our nervous system, right? It starts with our brain, and it goes down through our body, and it innervates all of our, you know, our bodies. That's what our nervous system does. You can think about artificial intelligence as exactly that, an artificial brain that does reasoning and can drive action. A brain without a body, without muscles, is nothing, right? Like, it can't do anything. What these coding agents do is they can take source code out of GitLab, and they can work on it locally, but then they have to push it back to GitLab to do the rest of the software life cycle. That's why we're seeing, as I shared, increased engagement in, you know, CI/CD pipelines and security projects and everything else. You should think of GitLab, if we're carrying on with that analogy, the GitLab DevSecOps capabilities as the motor system in the body. In order to have a full platform that's capable of functioning and building software and deploying it, you have to have both a nervous system and a motor system. That's the, you know, that's what Duo Agent Platform does for GitLab. We now have both the nervous system with agents, including Claude Code and Codex embedded directly within GitLab, and we also have the motor system that we've been building up for more than a decade. That platform, that infrastructure, is incredibly complex and sophisticated. It's tens of millions of lines of code. It's been built up for more than a decade. It's operated largely as a duopoly despite multiple attempts by large cloud providers to try and provide alternative services here. I think that speaks to both the technical, the data, and the business modes that GitLab has for that motor system. Great, great context. I'd love to hear about how the AI code development boom is what impact that's having on your own product engineering organization in terms of their productivity and how it impacts your hiring plans. How is that impacting GitLab internally in terms of your own engineering efforts? Yeah. Like every engineering team, our team sees those tools, experiments with those tools, and uses Duo internally as we've been building it out to do their own work. In fact, we've been, you know, building the platform and then using it internally, which is always a little bit fun because you're not getting a finished product. You know, you're getting a new product effectively every day that gets a little bit better and sometimes has bugs. We've been seeing an increase over time as the platform has gotten better from our own engineers' productivity. In fact, those engineers who heavily use, you know, moderate to heavily use Duo internally, we see up to 4x more MRs per developer than those who don't engage heavily. Think about that kind of acceleration in terms of, you know, innovation velocity. That's pretty exciting. We're also, you know, now using what I said earlier about the full value proposition, we're using it across the software lifecycle. Whenever epics or issues, those are kind of the documentation around the code, are created, most of the time, I'm seeing those created agentically now. When pipelines fail, that's when the code is actually being built and tested. I've got so many stories, anecdotes of our own engineering team saying, "Oh my goodness, like, I had a pipeline fail, and it took, like, two hours. I sat there and tried to debug it for, like, two hours, and I even brought Claude in and tried to fix the pipeline, I couldn't get it resolved. Then I remembered Duo has this new, you know, workflow that can fix pipelines. I tried it, and two minutes later it was fixed." You know, like, stories like that just warm my heart because I think that's what we're, you know, that's the value that we're, I'm looking forward to customers seeing and realizing because we fundamentally have a structural advantage versus external agents. Mm-hmm. External agents, again, can sync the source code and work on that locally. GitLab agents are where the work happens. It's right next to the source code in the same compute and data layer that GitLab runs in. They have access not just to the, you know, few files that you wanna make code changes. They have access to, if you want, the entire repository to all of your projects, to all of the issues related to this code, to all of the security scans that have been done on this code, to past failures. That additional context can drive higher quality outcomes at lower cost. Yeah. That's definitely a strong foundation to build on. As we wrap up, talk a little bit about, you know, Bill laid out the growth strategy. When we think about the capital allocation side of the question, the company has north of $1 billion in cash. How should investors think about your priorities, Jessica, between organic investment, share repurchases, M&A, and maybe speak to what's your latest thoughts on stock-based compensation with that trend? Yeah. Again, I just shared we just announced our first-ever Share Repurchase Program, $400 million. In terms of capital allocation, we really have three priorities. First is organic growth, and I laid out that's R&D. It's R&D first, how do we advance the product roadmap and innovation, sales and marketing, and then G&A. The second is balance sheet resilience. I really think in an environment like today, you wanna have resilience and optionality. We do have about $1.3 billion of cash and short-term investments on our balance sheet. Finally, share repurchases and returning cash to shareholders, which I do think it's a great lever to both manage dilution, and that's something that we are watching, but also return cash and value to shareholders, especially in times of share price dislocation. Again, I think the theme for us is we're in a great position. We do have a lot of optionality, but organic growth first, and then we've got flexibility to manage capital in a very effective and strategic way. Well, thank you, Bill. Thank you, Jessica, for giving us the update on the GitLab story. Fiscal year 2027 looks to be exciting, and hopefully we see better growth ahead. Thank you so much. Thank you.