Okay, hi everybody. I know you guys are thoroughly sick of looking at me, but you'll be very pleased to know this is the last time you'll do so. I've saved the best to last, so this is my last fireside, my last chance to learn a little bit more from a couple of software executives in Bill and James. So proud to have GitLab here. I think it's very public knowledge that UBS is an extraordinarily large customer of GitLab, so I think we've got a pretty happy IT executive team as well. And I trust, Bill, we've been paying our bills lately. Yes, you're a great customer. Thank you so much. Okay, terrific. Okay, great. So, Bill, you haven't been in the seat for that long, but as you sort of close out your first year-ish, I think, do you want to kind of give us a little bit of the State of the Union, look back at the year, what went well, you know, what could have gone a little bit better? Yeah, I was just looking at my phone because tomorrow is the one-year anniversary. Oh, okay. Congratulations. Yeah, it's been such a fantastic year. You know, I came to GitLab, because I've spent most of my career building developer tools and platforms, and the opportunity to do that at GitLab, which is kind of one really rare and unique opportunity. It's a world-class company that's really the backbone of our customers' software factories. There's only kind of two companies at scale for DevSecOps like GitLab, and so the opportunity to be part of that, but also part of this AI wave, which I truly believe is going to change all of our lives in the coming decades, both as consumers and as professionals. And that all starts with the software workload, bringing AI to the software workload. So not only being part of an amazing DevSecOps company, but the ability to shape the future of software innovation is why I'm here. And it's been an incredible ride. We've made a ton of progress as a company, and I'm even more excited today than I was a year ago. Well, for those that are new-ish to the story, could you put your finger on what the one or two, you know, key, endearing strengths of GitLab are? Because GitLab has scaled over the last 5+ years, I think you would agree, in a fairly competitive market where, you know, you were going up against Microsoft, frankly, with Azure DevOps and GitHub. You've got Atlassian in the space. You've got a whole host of private tool vendors. So what have been the one or two things that have enabled you to secure big logos like UBS and get to a $1+ billion in reps? Yeah, I'd say one hallmark is definitely our unified platform approach. We have a single front end, a unified data back end, with an opinionated view of how software factories should be built. From planning through deployment, we provide our customers the best way to accelerate innovation, and that's proven in the, you know, payback period with GitLab Ultimate, six months. The ROI in three years is over 480%. And that's because of this well-integrated, built-from-scratch platform that unifies DevSecOps. As opposed to, you know, our competitor and other best of breed that provide kind of one use case or one part of the DevSecOps lifecycle, we provide it all in an opinionated fashion. The other thing that is a standout hallmark of GitLab, which customers love, is we meet them where they are. We're the only at-scale independent public company. We run on all of the hyperscalers. We support, in addition, self-managed deployments, so customers can take us and run them in their own infrastructure and manage them themselves, something that other software companies are moving away from increasingly. Including many of our customers are public sector, government, large financial services like UBS that want to continue to have control and sovereignty over their most important asset, which is their IP. So that's a hallmark advantage of GitLab as well. Okay, that's a good level set. So, Bill, let's jump into the AI phenomenon because I think that's what a lot of people in the audience want to hear you articulate a view on. So when I think about where AI is most innovative and applicable to real-world use cases, I would say actually coding and the creative realms are probably the most fascinating to watch, and the pace of innovation is remarkable. So I think that the issue we all have, though, is that we're trying to look out three years' time and figure out how AI will affect your space. And there's so many variables. Is it going to affect developer seat count? Is it going to force incumbents to alter their pricing models? Are the model providers going to step into your world and have a frenemy relationship? So maybe we'll go down a few paths, but Bill, maybe I could get you to look out over the next three years and articulate at least your view as to how AI, good or bad, will affect the developer tool market. Yeah, I clearly see that AI is going to expand our TAM. Okay. I believe the future of software engineering is inherently human-AI collaboration, and the AI coding tools that you mentioned as a highlight of AI so far are truly magical. I remember the first time I saw them in action. I was like, "Whoa, this is kind of mind-blowing that I can give a simple prompt and it can actually generate working code." What's interesting, as we've probably all seen over time, is that magic trick, if you will, becomes a cheap magic trick when you realize that the code being generated also comes with bugs and with security issues. Mm-hmm. That's by nature of the fact that LLMs are non-deterministic, and no matter how good they get, which we expect them to continue to get better and lower cost, they'll never be perfect, and they will require a check-and-balance system, just like humans, to ensure that the quality and the security and the compliance needs of the business are met. Mm-hmm. That's where GitLab comes in. That's what we do today for humans who are writing code. Mm-hmm. And we see agents. We see these AI coding tools actually creating more demand for our platform. Just a few days ago in our earnings cycle, I shared that we see, for example, you know, CI/CD deployments and releases in our platform have grown over 35% year- over- year. So we clearly see that increased engagement, the increased activity of developers. GitLab is a core backbone for software engineering, whether the code's written by humans or by engineers. Mm-hmm. But we also see when we talk to customers, and you've now seen this in multiple studies, while code generation has increased, software innovation has not accelerated. We call that the AI paradox. The reason for that is because LLMs are not perfect, just like human engineers, that code does have to go through the software lifecycle to be code reviewed, to be quality assessed, to be secured, to do all those checks and balances. And that part of the lifecycle has not been AI accelerated. And that's exactly what we've been building for the last 6+ months with Duo Agent Platform. We're really excited to bring it to market later this month because what it does is it allows engineers to solve any software lifecycle task with an agentic approach. They each, every software engineer can delegate work to one or multiple agents to accelerate moving that code, whether an agent or a human built it, all the way through deployment. Okay. I think I'm certainly in agreement that the AI enablement over the next two years is going to move well beyond the coding swim lane, and incumbents or disruptors are going to find ways to AI enable the entire software development lifecycle. That seems fairly clear, but I think the question that investors have is, is it going to be GitLab that does that, or is it going to be Anthropic, OpenAI, Cursor, and all those folks who realize that they can't just make a living off of the coding, that they too need to expand their footprint, so it seems ambiguous who there seems to be a battle in front of us, so, Bill, to the extent you can, how can you give us confidence that it'll be GitLab that'll be kind of standing in five years and not Anthropic and OpenAI and Cursor? Yeah, you know, if you'd roll back the clock five years, you might ask the same question, as Google and Amazon, both major hyperscalers with tons of capital and engineers, both entered this similar space. Yeah. And have since retreated. Room for several. Yes, well, they've actually exited their businesses, so you know, it still is a duopoly of sorts. You know, Microsoft and GitLab provide the only at-scale services for DevSecOps, and I think that speaks to the challenge of building a complete DevSecOps platform. Mm-hmm. I'll also say when it comes to agentic outcomes, there's, you know, four ingredients for that. Two of those pretty much everyone has access to. Those two are LLMs and prompts. You know, in order to create an agent, you need an LLM. We provide all the foundation LLMs from Anthropic, OpenAI, Google, everyone. Second, you need a prompt. Well, those prompts are pretty shallow IP. They're basically human instructions to tell the LLM what to do, and you know, we have some special customizations and things that we offer for customers that maybe generic agents don't provide, but largely those two are, I would think of as commodity. The real secret ingredients to high-quality agentic outcomes are things that are really strengths for GitLab. Those two things are context and capability. Because an agent, like a brain, first needs more than just the prompt for instructions in order to know what to do. And what other agents do is they'll hand the code as context, and the agent will look through that code and then, you know, generate code to either add to it or augment it or fix it. And what GitLab can do, which no one else can, is we index that code semantically, not just the one project at a time, but across all the repositories in your organization. And then we link that code to all the MRs associated to it, to all the security scans, to all the quality runs, to your quality test cases, to your issues and plans. Because we have the full lifecycle as part of our platform, we also have all of that unstructured data that can help the LLM make better decisions. In our early testing with our knowledge graph, which is our semantic graph database that we feed to agents, we see a 40% improvement in agentic outcomes, both in the quality of the outcome and a reduction of the cost as a result of that added context. Mm-hmm. So that's kind of secret ingredient number one. Secret ingredient number two is capability. Because agents, you know, our brains, they need hands and feet in order to take action. And what other agents have at their disposal are the generic operating system tools like reading and writing files. That's why they're able to generate code. But if you want to actually do things like security analysis, scanning, you want to do things like planning, you want to do things like packaging and integration and deployments, you need that capability. And that's what GitLab is today. We offer that to more than half of the Fortune 100. We have over, you know, 10,000 paying customers. We serve some of the largest organizations in the world. And that capability for humans is now being unlocked for agents across the software lifecycle. That's what Duo Agent Platform does and why we're so excited to bring it to market. Okay. That's a good answer to the question about how AI enablement across the whole software development lifecycle could play out. Another hot topic, Bill, obviously, is the effect that AI may have on developer seat counts over the next five years. I think you've stated pretty clearly that you're not really seeing any of that yet, but could you opine a little bit more? And then, James, maybe for you, could you unpack maybe GitLab's most recent 3 Q in terms of the seat contribution? So what did you see very specifically in the quarter around the seat contribution to the growth algorithm? Yeah, it's interesting. I hear this concern from investors all the time that because these coding agents are good and getting better, maybe developers will not be needed. Yeah. For any of us who build software, and this is consistent with what customers say, in fact, we did a survey last quarter, where more than 80% of our customers told us that they expect their headcount as a result of AI to either stay the same or increase in the coming years. Mm-hmm. Because when you're building software, you realize for every idea that's pursued, there's at least 10 that can't be pursued. Mm-hmm. For every bug that gets fixed, there's 10x more that never get fixed. We live with a lot of crappy software, let's be honest. Mm-hmm. Because engineering teams are constantly under pressure to both fix bugs and fix technical debt and innovate. And there's never been enough developer capacity in the world to do it all. So agents only accelerate the ability to build higher quality software and pursue more ideas. Mm-hmm. Software is what, you know, a large part of our global economy. It's how the global economy has grown, over the last decade. We've talked about digital transformation for a while now. Mm-hmm. Imagine AI-driven digital transformation. Okay. I think the prospects for developers only grow larger. James, how is this manifesting itself in the numbers? In the growth algorithm? Yeah, maybe I'll comment on a little bit on the growth algorithm first, and then I'll talk about seat contribution, right? So we have a sort of very classic land and expand model. It's a really healthy and powerful model. In Q3, we reported net dollar retention of 119%. And, you know, really almost at $1 billion of scale, that rate really speaks to the customer value that we're delivering and the fact that at scale, these large enterprises are continuing to expand their spend. We're seeing all cohorts since inception continue to expand at a fairly tight band. Our oldest cohort from 2016 has more than 100x'd their spend, since their inception. And so that land and expand model remains very healthy. What we also disclose is sort of the seat contribution as part of that expansion. And so in Q3, it's been consistent with prior quarters where seat contribution to that expansion was slightly over 80%. So we're continuing to see seat strength, seat expansions across enterprises, and we're really happy with that growth. Okay. Hypothetically, like, let's say we're wrong and GitLab in the industry did start to see some more modest seat growth. You do have one lever that you could utilize to combat that, as every software company that uses a seat-based model could. And that's alter the pricing model. Just start shifting it maybe towards more consumption, usage. Can you maybe perhaps for both of you talk about whether you're doing that to some extent and what that future could look like? Yeah, so as we introduce Duo Agent Platform, which we plan to do later this month, we're also introducing a hybrid pricing model, which is we'll continue to sell GitLab Premium and Ultimate with the seat-based subscription business that we have today. But Duo Agent Platform will be introduced as a consumption model or a usage-based billing model on top of that, where, because every engineer that uses GitLab can now spin up one or multiple agents, we need to be able to scale the price along with that value. Mm-hmm. Based on their usage, we will charge them what we are going to call GitLab credits. Those GitLab credits scale with usage. The organization that purchases GitLab will be able to buy those GitLab credits on demand if they choose to just let their, you know, engineers incur that expense on demand and get billed monthly, or they can choose to commit upfront and get the best pricing, because that gives us, you know, the ability to forecast and also have ratable revenue. We'll pass along some benefits with that and pre-commit to a monthly minimum that their entire organization can share. It will not be a seat-based model. It'll be a shared pool model that then within the organization they can slice up and use, which as I've tested and shared with customers leading up to our general availability has landed really well. Customers are excited about being able to have that pooled model for AI usage versus the fixed seat costs that some of the other alternatives provide. James, you haven't given guidance yet on next year, but on this dynamic. Yep. Pricing changes and how that might affect revenue growth, gross margins, is there anything that you could share with us about, you know, trends around this dynamic that Bill talked about that could impact the numbers next year without giving any guidance? Yeah, of course. Yeah, absolutely. I'll, I'll maybe comment on a few factors for 2027 to really help us all think through it, right? So the first thing, we said this in the earnings cycle as well, is the Premium price increase that we announced about three years ago will be going away as a discrete tailwind in FY 2027. So in FY 2027, we'll have lapped out three years since that announcement. The new price lift takes effect upon renewals. And so as that renewal base laps out, that tailwind will be going away. On Duo Agent Platform, we're really excited about that early customer momentum and engagement, but both because, you know, at, at our revenue scale and because about 70% of our customers are self-managed who take time to adopt this new technology, this will take some time to play out through the model. It won't be an immediate impact on the numbers. Maybe one last question before we turn to some other facets of the GitLab story, maybe for you, Bill, is around the potential for AI to act as a catalyst for further consolidation in the developer tool market. And the examples I would give to you is the cybersecurity space, has some attributes that the developer tool market has, which is you've got a number of siloed players that are doing niche-y things in their swim lanes. And as my opening question had you respond this way, the GitLab story is very much about offering a totally integrated platform, but you're somewhat unique in that respect. There's a bunch of niche players. You're seeing the observability space, Palo Alto, Chronosphere most recently, begin to consolidate. You spent, you know, two minutes with Ali Ghodsi at Databricks, and he thinks the data management space has too many niche vendors and should consolidate. Do you think AI could spur on a desire for consolidation in your developer tool market? Yeah, I think that is the foundation of GitLab. That's the reason GitLab has been successful. I think the trend for best of breed versus platform plays out in multiple categories of software, as you've shared, and it will continue to play out, and one of the reasons for that is it's really easy, well, not easy, but it's possible to go after a specific niche and provide best of breed solution, and you referenced security, so I'll use that one, and there are certain, you know, security vendors out there that are constantly innovating to provide the latest differentiation and capability on security. What GitLab does with security is different, and it's harnessed the platform advantage because rather than provide customers with maybe always the very latest security scanning techniques, what we can offer to a CIO or a CTO is, "Hey, we will hook security scanning and vulnerability detection into your software pipeline so that every code change by every developer gets assessed." That's something if you're a niche and you're outside the platform, you can't do. Mm-hmm. That, from a compliance governance perspective, is a very powerful value proposition. Customers will be willing or often willing to either trade off the very latest security scanning technique for that leverage to get security across their code base, or they'll buy both. Mm-hmm. I think the same thing is going to be true for other capabilities, including AI code generation or AI coding, you know, tools or related tools. Over time, those capabilities will be subsumed and be higher leveraged in the platform. Mm-hmm. Because again, context and capability leverage is the secret sauce of great quality agentic outcomes. Okay. And that's what GitLab is so great at. Got it. Let's move to James for a moment. James, obviously, you guys printed earlier this week. I think you and Bill were clear on the call that there were a number of factors that were influencing your guidance for the Q4. There's still sort of a tail of SMB budget pressures that you need to account for. Yeah. You and Bill and the team have made a number of go-to-market changes, and you wanted the guidance to reflect some of that. Yep. You call that, potentially a little bit of softness in Fed. Can you run through those? Which ones of those are most significant that we should watch more closely? Which ones are transitory, such that they might only have sort of a quarter of duration and they're not really factors for next year versus ones that may persist a little longer? Yeah, absolutely, Carl. So we've called out three things, more broadly. Two from last quarter that we called out as we were setting last quarter's guidance around SMB softness and go-to-market disruption. You've heard Bill talk about some of the tweaking and innovation that we've been doing in rebuilding go-to-market. When we do that, we expect some ongoing level of disruption. The SMB weakness that we've called out for a few quarters now is really concentrated at the lower end of the market, right? These are spend-conscious customers, smaller customers with small amounts of spend. What we have is a really strong free tier. We also, a few years ago, took away our entry-level tier, and we've raised the prices on our premium tier from $19- $29. And so some of the behavior we've seen from these spend-conscious customers is scrutinizing their spend and sometimes down-tiering to free while staying on GitLab. And so from last quarter to this quarter, right, the prudence that we've called out in guidance on SMB and go-to-market were, frankly, pretty well-warranted. In addition, what we saw in Q3 was headwinds from the U.S. government shutdown. And so we've quantified this in talking about the U.S. public sector is about 12% of our business. Q3 is our biggest quarter. And so what we saw during the quarter is, you know, as the government shut down for 40-some-odd days, you know, there was simply no one to call on the other end. And so this impacted renewals, deals in the pipeline, both on new and expansion deals. And what we saw in Q4, the government came back online in the middle of November. You know, these agencies are coming back online, but these things don't happen overnight, right? There's 40 days of backlog. Teams are coming back from furlough, figuring out budgets and priorities and resetting again. And what I would say is there's a high level of urgency both from customers and from our side to re-engage and to accelerate what was pushed, but these things do take time. We're sitting now in the beginning of December. We're expecting a big push now and especially in January to catch up. Got it. The other thing I would say about the public sector too is, you know, we have a fairly ratable business model, and every day of a delay is a day of lost revenue. And so we will see that impact in Q4. James, how are you and Bill thinking about the growth margin trade-off into next year? Yeah. Bill, we've talked a lot on this fireside about AI change, and that must create a big need to keep your foot on the R&D pedal as best you can. But on the other hand, you're now an at-scale software company with, call it loosely, mid-teens non-GAAP EBIT margins. And. Yep. In fairness, I think there's probably upside there. So you've got, you know, competing goals. So I can start with you, James. How are you thinking about that? Absolutely. Yeah. We are starting from an absolute position of strength, Carl, right? We have 89% non-GAAP gross margins in the quarter. We have created over 1,500 basis points of our operating margin expansion in just two years. That kind of fiscal discipline is very much in our DNA as we think about scaling the business. What we are also doing is investing in the business and investing in growth, right? Specifically right now, what we are investing in is augmenting the go-to-market capacity and building out that function and in product innovation, right? We are about to announce the GA of Duo Agent Platform, and we are continuing to invest in making sure that we are innovative and shipping value to our customers. Ultimately, on the gross margin point, the way we think about it is what we are optimizing for here is long-term growth in gross profit dollars, and we think that best delivers both customer value and shareholder value. Bill, is there any way to put brackets around the magnitude of any sales capacity build-out at GitLab that you would like to see over the course of the next year or two? Yeah. One of the things, to, maybe augment what James just shared in terms of investing for growth, even within the existing envelopes, for example, in Q3, we reprioritized existing, dollars and headcount to create more capacity in our field. Mm-hmm. More quota-carrying reps. Mm-hmm. We believe in this expanding TAM. We want more capacity to go after that in FY 2027, both in the form of the new logo, the new business team that I've talked about we're spinning up, as well as expanded capacity to go after expansion. Mm-hmm. So we're being as efficient as we can and responsible as we can within the existing envelope. And then, as James shared with FY 2027, continuing to invest both R&D and sales and marketing, to grow. Okay. Hopefully, we have time for one question if anybody in the audience would like to ask one. Yeah, upfront, you can just shout it out. You often leave structure. Here today, perhaps you want better in terms of taking share and, you know, moving existing lines and developing something that the other parts can't offer. Yeah. And for those of you listening, then the question was, to Bill, what can GitLab do to be a little bit more aggressive around taking share in this dynamic market? Yeah, it's fascinating to me, so many questions about AI and emerging AI tools. The conversation around the real competition, as I see it, almost doesn't get any airtime. I would say I feel great about our position relative to GitHub, versus one year ago when I started. I think we've continued to build out the core platform and our Duo Agent Platform AI strategy. I feel and I hear from customers we're in a better position in, just structurally and from a competitive position, capability perspective. I do, we are looking at a number of ways to take advantage of that, including, you know, James mentioned this jump from $0- $29 as a first order, is a large jump for customers, and many of them went down to free. As we bring Duo Agent Platform to market, we're excited to bring that, potentially to our free base. We have a huge community base out there. To GitHub customers that want to move to GitLab, it could be a lower-cost and more capable option as a first order, meaning the free tier plus our AI capability. Our win rates have been very consistent. Our gross retention rates have been very consistent. Throughout all of the AI wave and everything, we continue to stand our ground and compete very successfully against all competitors. Okay. To answer your question. Yeah. Let's end it there. Bill and James, thanks for coming and making this conference as good as it's been. I've learned a ton. And thank you, everybody. Hope you had a great week. Thanks, Carl. Thanks so much.