Hey, good afternoon everyone, welcome to Atlassian's Investor Forum that we're holding here at Team 2026 in Anaheim. It's great to see so many familiar faces in the room, thank you for coming out. For those of us joining via webcast, thank you for tuning in. Because so many of you were coming out and making the effort to learn more about our platform, learn more about our solutions, and hear from our customers, we wanted to use this chance to help you better understand our strategic vision, our opportunities that we're attacking, and the momentum we're seeing across our business and our three strategic priorities. Today, we wanna talk to you about how we're serving enterprise customers, delivering that unique AI value, and what our system of work unlocks. Today, Mike, Brian, and James will share more about our longer term vision and strategy. We're coming off a strong quarter, but today we're talking to you about why we believe Atlassian is uniquely positioned in the AI era, and why the market is still misunderstanding or underestimating our runway and growth opportunities. You'll hear from Mike about Atlassian's evolution into a platform company, our system of work that we've built that serves all teams and powers hundreds of millions of workflows each and every month. He'll walk through our Teamwork Graph and the powerful context that delivers our AI strategy and the massive runway ahead across our 350,000 customer base. Brian will speak to you about our enterprise go-to-market evolution and how he's taken our platform and the increasing value it delivers, and how it translates into bigger, stickier, faster growing customers and relationships. You'll hear directly from two customers, Cisco and CANAL+, on what that looks like in practice. Finally, you'll get the chance to meet and hear from James, our new CFO, who will share his early perspectives. Please note that we won't be providing long-term financial targets today. Then we'll close with some Q&A. Before we dive in, the standard legal housekeeping around forward-looking statements, which you can see on this beautiful slide behind me, please take a moment to review. All right. With that, I'll hand it over to Mike. Thank you, Martin. Good morning, everyone. Good afternoon. It's morning where I'm from. That's my only excuse. Good afternoon. Thank you for being here. I hope you all had a good morning this morning. Did you all attend the keynote? Just so I know what I have to replicate. Okay. Well, this will be way more fun. Don't worry. Thank you. It's good to see so many familiar faces, I should say that. As Martin mentioned, we're coming off a very strong quarter. Total revenue $1.8 billion, 32% year-on-year, cloud at $1.1 billion, 29% year-on-year, RPO past $4 billion at 37% year-on-year. I'm sure you all know those numbers as well as I do. A really strong quarter, another chapter in our story. It is an example, I would say, at the highest level of our three strategic pillars, the enterprise, the AI, and the system work all coming together. I hope over the three or four presentations today, you see how those continues to thread together and lead to that strength and growth as we have shown continually. As Martin said, it's not about that quarter. We wanna spend time talking a bit more about the longer term story and what that means because underestimated, misunderstood, all these things that you said, I think it is totally true. There is a big disconnect, I believe, in how we are seen and what we are actually delivering. I thought we'd go through some of those doubts and give you a lot of facts and figures and other things to go through those. You've probably familiarly heard a bunch of the AI's gonna make devs redundant, we only serve devs, seat growth is gonna die, seats are gonna disappear, AI agents are gonna make everything less critical, people are gonna, I don't know, make their own SaaS by themselves, make their own operating system, then probably make everything. AI native startups are gonna just kill everybody, we don't have the right monetization model. I'm sure you've heard some version of all of these things. Let's go through some of them. Fundamental problem, I would say, is that's very much looking backwards, right? That might be looking at Atlassian 10 years ago and assuming we're a static company. We've never been a static company. We've probably always been underestimated and misunderstood. Awesome. Bring it on. The platform we built, transformations we're delivering, I hope we're showing you every quarter that we are delivering the numbers that we say we're gonna deliver, durable growth that you can see in those numbers. I do think it misunderstands our runway going forward, and we'll try to give you some indication on that. Let me tell you what Atlassian's about, granted in real numbers. I know a lot of you, despite being extremely smart, struggle to model Atlassian. You see a bunch of apps, and you usually talk a lot about Jira and Confluence, although I still don't know how many Confluence questions we've had in any earnings call. I think I've said this a couple of years in a row, it's still amazing to me, we'll get to that in a second. Jira and Confluence is not how Atlassian works. It's really not how we work, right? We are building a singular platform. As you now see, we have all five collections, plenty of companies claim to have a platform. Most of them, I would argue, as a technical person, do not have a platform, not like we do, right? We have a single platform that delivers a single system of work that continues to compound and multiply the more collections and apps that you have on top of it. It delivers a common way to do things through the flexibility for an organization, the value is in not the data, but the graph, the ontology. We will spend a little bit of time talking about that. That's why I'd argue we're becoming an operating system for work for a lot of the world's largest companies. Customers are increasingly committing on a platform level. Brian will go through that. We have more and more platform-level committed customers, I've talked to a bunch even this week, that are making even greater commitments to us, which feels excellent. It's a justification of all the things that we've invested in. As they add collections, they deepen their investment in us. It also makes our AI smarter. I hope you saw that. We'll have a lot of slides on AI. I'm sure there'll be at least a couple of questions on AI as we get there. One of the reasons that our growth is so durable is that it's incredibly diversified. We told you in our shareholder letter last week, the Service Collection has passed $1 billion ARR and is continuing to grow at 30%. That's ARR, not even revenue. Now, that's just the Service Collection. Confluence by itself has passed $1.5 billion in ARR. Jira has passed $2.5 billion in ARR. We've built multiple billion-dollar-plus businesses, all of which work on a single platform, which is really important for our customers, that serve every industry and every team, from finance to HR to IT to software teams to designers. That is an incredible set. People keep asking, "Well, how did Jira and Confluence keep chugging? They must be slowing down," right? It's not the case. Today, Jira and Confluence are accelerating, as we have said, in the cloud. It's because of the platform, right? We serve more and more workflows and business processes, which I think people greatly underappreciate, right? With the Teamwork Collection, people aren't buying point products anymore. They're buying a collection of things that work together that are part of a platform. That's a massive signal for us, as we've shared, of 1,000 customers, that was a quarter and a bit ago, I should say. That was in the previous quarter's results, more than 1 million seats in the first 6 months. Those are some really strong numbers, but the point is diversified business, multiple large businesses, all of which are growing very strongly. Again, the collections make it easier to expand. The changes we've made from a set of products three years ago to the apps and collections that we have today working on a singular cloud platform make it easier for customers to consume our software. We have less things for them to buy with far more value, and part of the reason we're seeing that runway ahead of us for durable growth and the growth we're seeing today. You can see all of this diversification playing out in our numbers, right? Customers aren't just buying in, they keep expanding. Let me give you an interesting chart I think it'll be interesting for you. Let's look at total cloud seats, excluding all migrations. No migrations involved. Despite the seat-based, it's gonna disappear. You can get out your rulers if you want. I know you do. You can see visually it's not slowing down. It's a pretty amazing curve. Again, this is excluding all migrations. Cloud seats. They continue to grow every quarter, every year. Durable growth as we talk about. Why? Because workflows continue to get more complex, more intertwined. Teams and companies are buying more into the Atlassian platform and getting exponential value as they increase their commitments. That's really important, and we think that only keeps accelerating from here. As teams start orchestrating their AI agents alongside their people, you heard me talk just a little bit this morning about the single Teamwork Graph, I think we have more ahead of us that we can continue to do because of our investments in that platform, right? You might be asking, okay, they're adding those seats, but seats for whom, right? This is where the old narrative, I think, breaks down. People pigeonhole Atlassian as a developer company. I might argue there's going to be more developers in the AI era. I think that's going to be true. Fine, you think we are the developer company or some people do. We love that heritage, I will say. Developers are awesome. Technology and business teams working together is the core of what we do. We think developers are incredibly important to the future of every single large business on this planet. Technology is the core strategic advantage of almost every single big company that you will talk to. If not, they have some sort of regulatory barrier, et cetera. The growth we are seeing has not been driven by developers for a long time. The system of work is for the entire company. It is for finance teams, it is for HR teams, it is for marketing teams, it is for operations teams and service teams. When we talk about assets and buildings and laptops and everything else, we're talking about far more than developers. We're powering hundreds of millions of workflows every month. You've heard us talk before about how half our users are not in technology teams, and we've got a half technology, half non-business. We've shared that before. How about this one instead? Break it down and let's look at developers versus everybody else, knowledge workers. In Confluence, seven out of 10 users for that one and a $500 million+ business that's growing well, very well in the cloud, seven out of 10 of our users are knowledge workers, non-developers. In Jira Service Management, it's over three-quarters. Even on Jira, it's roughly 2/3 of the users are non-developers. That's HR and finance and legal and marketing and operations staff and design. We spent two decades connecting these business teams with their technology teams, and we have a lot more to do. Again, a different way of showing that we are a well-diversified, durable growth business. Let's look at the customer segmentations. When you're embedded across that many teams inside a company, customers are expanding. How do we see that? Well, we talk about having 350,000 paying customers. We know that that's the bottom of this kind of pyramid illustration. How about at the top end? Our $1 million customer base, which I believe we said a quarter and a bit ago, had passed 600 customers spending more than $1 million a year. That has grown six-fold in the last four years. In the last year alone, it grew at 39% year -on -year, that category. These customers have more than a 99% retention year-on-year, they are almost all expanding. If we look at our $3 million cohort over the last four years, when we talk about the enterprise investments we made on the technology side, on Brian's side, that $3 million cohort has grown 10-fold in the last four years. 54% year-on-year in the very last year alone, we have quite a number now of those $10 million+ ARR customers. These are ARR numbers as well, not revenue numbers. Takeaway I want you to get is we're not a nice-to-have tool. We are part of how these organizations run. We are a strategic partner. That has been our goal, as we've said in every shareholder letter for the last four years. That is our enterprise goal. We've been working on the enterprise for a decade now, since Data Center launched a decade and a bit ago. I think that's reflected in the movement of our customer base. The top end of the pyramid is going very well. The important part is we have an awful lot of customers in that bottom end of the pyramid who are moving up there. The platform works, customers stay, they expand, they deepen their commitment to Atlassian. Natural question is, do you have all the businesses? What is the runway? We've updated all our SAM numbers. The way we've recalculated it now, updated the calculations, is that our SAM is about $140 billion. We have a lot of runway is the simple thing to take away from this. See it broken down by different collections and other bits and pieces there. There's a lot ahead of us. The question naturally is, how do you go after that? How does that actually happen? We've broken out these four growth levers, which are the ways that we grow typically, right. Expanding inside the customers we already have. Those $1 million customers have become $3 million customers, have become $10 million customers that started as $10 customers. That is expanding inside customers we already have. When we move to new groups inside those companies, we don't count them as a new customer. They're the same customer that we've always had. Most of the customers you'll hear from today, and I'll show you some examples in a second, have been with us for 20+ years. I routinely speak to customers who've been with us for more than two decades. None of them are spending less than they were two years ago, let alone less than they were 10 years ago, and their commitment to Atlassian keeps growing. We obviously cross-sell across the portfolio. Show you some stats about that in a second. We obviously have far more apps, I think you can see, across the Moonrise than we have ever had in collections. Upselling into new value tiers as we've added the premium and enterprise tiers in the cloud, of course, winning brand-new customers is still something that's critically important to us. When we look at that 350,000 customers across the globe, they're in literally every industry on the planet. I have spoken to customers in every single one of these industries in the last maybe quarter, at least year, every single one of these industries. For every single one of these industries, they're driven by technology. Their technology and business teams connecting together is how they're trying to win in the future, and that's exactly where we sit with our platform. It's a massive number, but we have barely scratched the surface of the opportunity in most of these accounts. How do we know that? Again, we talk about the Fortune 500 that are already Atlassian customers, 85% of them. Again, representing only 10% of our business today, and I think we only just passed 10% very recently. We have a huge amount of growth in that Fortune 500 cohort alone. The headroom inside all the other companies we serve is massive. We are in the European equivalent of the Fortune 500, the Australian equivalent of the Fortune 500, the Asian APAC equivalent of the Fortune 500. Across the global enterprise landscape, we have a huge amount of runway ahead of us. How do we know that in terms of those knowledge workers? If you look at the 1 billion knowledge workers on the planet, about 900 million of them are outside of technology, about 70 million technical knowledge workers, and about 30 million of them are in development. Call these order of magnitude rough numbers. There's various surveys. They all end up about this sort of proportionality. If you think about the fastest-growing segment of our customer base, which is that non-developer audience, we have an awful long way to go with our 10s of millions of users today to that $1 billion. A few different ways you can think about our potential. Again, when we land a new department, we don't add a new customer. Just two-three months ago, we landed a 200-person marketing organization that had never touched Jira in one of the 10 largest companies on the planet. What's important is those 10 largest companies, they said they had never used Jira. In fact, one of the people said, "I didn't know this was Jira. I thought this was someone else." I won't say which competitor. That was awesome, right. That was amazing. When they use it, they're really happy. Why? It connected to their technology team. They almost literally repeated our core mission back to me in a meeting, and it was a truly amazing moment. Massive opportunity ahead of us. We do have significant cross-sell opportunity just in the Jira base. How do I keep illustrating this in different ways? Here's a different way to look at it. If you look at the Jira base in the clouds, 150,000-ish customers, call this a sort of a round number. Again, as I said before, Jira is growing extremely fast in the cloud by itself. This number keeps going up. If you look at Service Collection as an equivalent, it's only 65,000 odd customers. There is a huge runway just if Service Collection did nothing other than sell to the Jira base, right? That's over, should have done math before my coffee. What is that? 85,000 Jira customers where Service Collection is not attached today. That is a huge number when you look at enterprises around the world. These are only significant customers, I would say. The reason it's 150,000, I've excluded a lot of the smaller ones and stuff like that. They're of size, let's say. The best part, those aren't cold conversations. When Brian's team go in and say, "Look, your Teamwork Collection is going really well. Let's talk about the Service Collection," and you've got the same data, the same platform, the same Teamwork Graph, that's not a cold conversation. That is an amazing conversation. Part of the reason why the Service Collection continues to take share and do really well, in a lot of those, increasingly in the enterprise and strategic segments. I talked about upgrading editions. This gives you some interesting statistics on where we were. If you look back five years, again, this is Q3 numbers, not quite the end of FY 2026 yet, but roughly a five-year period, call it four and a half to five years. You can see that our mix here has moved from the standard premium enterprise we had five years ago to where we are today. It's an example of our enterprise journey continuing. I drew this chart for you, so it was illustrative on the left to the right. The right-hand bar, obviously, in Quantum is far larger than the left-hand bar. We have far more customers than we had five years ago, but just as a proportionality, it shows that our customers are increasingly opting for premium and enterprise as we continue to solve scale, security, regulatory compliance, and other issues that they can opt into. At the same time, the standard continues to grow well because we get that broad base of millions of companies around the world. How big is that broad base? There are about six million companies roughly that we would estimate are in our target market, right, that aren't Atlassian customers today. We have a few hundred thousand free instances in businesses of any significant size. So again, we're not talking about a one-person instance, someone's created as a test, et cetera, excluding that. It sort of shows you where some large amount of opportunity when you look through those different things. We talked to the system of work, our growth, lots of opportunities. I thought it would be helpful if I broke it down into some actual customer examples. This is real-world customer data I've anonymized. Neither of these are two customers coming to talk to you today. They are two examples of thousands of customers that I could pull out literally that show a multi-year journey. I'm gonna start with a global auto manufacturer, 100,000+ employees, very big company. Let's look at their journey over 15+ years with Atlassian. It's a bit of an eye chart, let me walk you through it for a second. If you see the line at the bottom, the first line is their time on server for those who've been with us for a while. The Second line is their time on Data Center, and the third bit of the line is their time on cloud. They're on cloud for the last five years. They spent three or four years on Data Center and what is that? Six, seven years on server. They moved our deployment options over time as this example of a customer. They've been with us for 15, 16 years at this point, and you can see at the very bottom what applications they've bought. You're always asking, where does all the R&D go? Here is a good example of where they've built things that we didn't have and they've bought things that we didn't have over time. They're now sitting. I should say at the top, it's probably the most important part that I missed. This is obviously their ARR in millions of dollars at the top. You know, they were at $1 million-$2 million five years ago. They're now sitting, what is that? Sort of $8 million-$9 million, maybe $9 million and change. Sorry, my eyes aren't that good anymore. You can see as they've moved where those jumps in revenue relate to their movements. You can see when they moved to Data Center, it moved from what was actually an exponential chart for the first five years. It is actually exponential for the first five years. It's just, you know, the left-hand side, they were probably spending $5,000, $10,000, like near, you can't see the bars. Move to Data Center, they're getting to the $50,000-$100,000. They get to the $1 million in the Data Center range. As you see, as they move to cloud, they continue to ramp up. We talk a lot about why that is, it's fundamentally they have many more things they can buy. Their expansion opportunities or expansion speed in the cloud is a lot faster, they've moved to many more users. Back here, they're in the 5,000-10,000 user range. At the end now, they have 70,000 users running on cloud enterprise, the scale of what they're doing is absolutely wild, right? Millions and millions. In fact, more than 10 million automation rules running every quarter, hundreds of thousands of manual tasks disappearing, massive Rovo adoption across the organization, agents running AI. Rovo is their default for AI. They like it more than any of their other AI solutions, et cetera. You can see when they've started to add Strategy Collection and Jira Product Discovery, albeit those are small and still have some growth. One example of a customer, auto manufacturer. I got one more. Oh, no, I forgot something. Oh, no, I didn't. They're learning on Rovo. I already said that. It's all about the platform. When you talk to this customer, the platform is what has enabled them to keep going. A typical pattern that we'll see with the cloud 2021, 2022, 2023, they're actually adopting cloud, moving to cloud, moving users over. Once that two- or three-year period is done, you start to see that acceleration afterwards as they then take on JPD, Service Collection, and onwards to the Strategy Collection, which is now running their enterprise dashboard for this large organization. Here is a totally different customer. This is a major financial services firm. Different continent, different part of the world, different industry. Again, a second of many hundreds of customers I could show you that look exactly the same. They again have been with us for about 15, 16 years. I actually cut this one off. I think they actually have been with us since 2004 from memory, so actually 22 years as a customer, but the first few years are literally just blank from this scale. Very similar journey to show you this one. Again, I believe they're at 30, 000, 35,000 users, something in that realm, so about half the size of the Product Collection in users. However, very close in spend, and you see them in the last couple of years again, once they've moved to cloud, a year or two of adopting and moving themselves to cloud, moving their data across after a long journey with us, and then starting to adopt the Product Collection three years ago, Rovo two years ago. They again have tens of thousands of AI models they're running with Rovo. They really, really like it. They use it in automations, in everything. It's one of their default things. They built a bunch of agents to do critical work inside compliance, in HR, in lots of other places that run natively on the Atlassian platform. They're a big user of the Teamwork Graph CLI. They're in an alpha program for the Teamwork Graph CLI, so they're actually using the command line interface. They think it will unlock a whole lot more usage of the platform. They have an incredibly strong responsible AI framework. They spent six months putting us through their AI paces, and we were one of the first AI tools that they turned on, which we're really proud of. We love customers that have very strict guardrails and barriers, and then we, you know, we pass those parts. One of the biggest goals they have is what they call the connective spine of their organization. Rovo is part of their connective spine, automating reporting, cross-team overhead, thousands of engineers. Like it's a really core part of what they do. In the last 12 months, they've adopted DX and the Strategy Collection. You can see that nice jump as they've come on board with those types of things. It's not entirely due to that, but just like a general movement. It's an amazing example customer, and it works because of the platform. Two of many hundreds of customer examples, I hope they were illustrative to try to show you what it is that we deliver for our customers, and I think they show you the power of being an R&D-led company. We've always been an R&D-led company. We've made a deliberate choice to build a true large-scale platform, a single platform, not taking any shortcuts, even if that meant taking margins down temporarily as we invested in that platform, as I believe we've tried to explain every single time what it is that we do, right? We have certainly ramped R&D over the last few years in a very deliberate effort to build that multi-year period of time to build that platform, right? What have we done in that period of time? Many shifts simultaneously, taking our largest customers and moving them to the cloud, building that singular cloud platform, which we're seeing the results of today as we saw this morning, delivering all the enterprise reliability, governance, compliance, scale of those world's largest companies to 50,000-person-plus companies right there, 30,000, 40,000, 80,000 seats, whatever it was, 70,000 seats, and moving from those point products to those integrated collections, a huge amount of work to do all of those. What does that deliver for customers? Well, I thought I'd give you an example, one way of looking at what it is we deliver for customers today. All of this is what we deliver for customers today. When I say that, we look at our three transformations, right? We think about our three pillars. We've got the enterprise, the AI, the system of work. Tried to organize the things we do into those, put it into the same lens that we explain in our shareholder letter. All of this stuff on the left, Atlassian Isolated Cloud, not easy, giant customers really want it, Atlassian Government Cloud. We're in Google Cloud, FedRAMP moderate, multi-cloud is Google for now alongside AWS. All of the things on the left, Atlassian Guard Premium, security clients we talked about. In the middle, obviously, all the AI capabilities that we've talked about from Rovo Search and Rovo Chat, which are the first customer there, it's like their best AI tool. We give them the best answers in Rovo Chat of any tool that they use. The CLI, all the things you saw this morning, MCP, et cetera. We talk a lot about AI. I'm sure there'll be some questions. Obviously all powered by the Teamwork Graph worth pointing that out. That's very important. On the right, those collections, all the third-party apps, all the platform apps that we've built in terms of goals, et cetera, et cetera, et cetera. You see the icons, you get it. Our Forge development platform, I didn't know where to put that. It's not technically in any of the three, so I put it in the system of work. Now we can support our biggest customers in the cloud after all of that R&D. We've built the world's best context graph at a time when context graph are incredibly important, and it's running at absolutely massive scale. Like we're preparing for trillion object scale. We have to, right? 150 billion+ at the moment. It's non-trivial size and scale of anything. Even at a consumer internet company, that's a big scale. Delivered FedRAMP, all of the things that we've talked about there for banks, government, healthcare around the world. That's what unlocks all the enterprise expansion that I'm sure you'll hear a lot about from Brian. I put this down for one reason, because you're always asking, where does the R&D go? We look at that. Let's have a look at what this looked like two years ago. 2024, it looked like this. We had apps, we had no collections, most of the AI stuff wasn't there, very little of that enterprise stuff had been delivered. Everything on that previous slide, by the way, was GA, shipped out to customers being used today. 2026, 2024. That is a massive change in our delivery of product that those two customer examples hopefully are showing you how that is turning up. Hopefully, that was illustrative. Always struggle to explain where R&D goes. That platform investment, R&D investment, is not just going into product capability, all of those things you show. It's delivering leverage that I hope you can see showing up in our financials. What does that leverage look like? Well, you probably already know these numbers, for FY 2026, whole year's not finished yet, et cetera, expected non-GAAP gross margins of 88%, right? 3 points year-over-year by continued optimization and scale and a lot of R&D investment that goes into creating that scale and optimization of our cloud infrastructure, which now is running at massive scale. We are hosting more customers, we are hosting larger customers, we are running more workloads, we are powering far more usage through AI, we're doing an absolute boatload of AI traffic, and our margins are going up, not down when it comes to COGS in R&D. That is an incredible effort thanks to our R&D leaders. I don't know if we have any in the room at the moment. I think we have at least one. All of the R&D team that have done that over the last few years. That's two charts you would expect to go in opposite directions, and that's a leverage I would argue you get when you build a real platform, right? Now I'm going to front run some of the questions that you're going to ask. Know a few of you very well at this point. How are you going to moderate that R&D expenses? I get it. That all sounds wonderful. What does that mean? Well, quite simply, like we've done a lot of the heavy lifting. We keep trying to get our language correct here. The unified platform, all of the enterprise capabilities, the unique data graph, that has to be built upfront. That is an upfront spend to get all that. We can't move a single one of those two customer examples without all the things that we've built in the enterprise. That takes years, five, six, seven years to build properly and to do it at scale and for them to test you and trust you to get onto that. We believe we have done most of that work in the enterprise capability and in the system of work capability. A lot of the heavy lifting is there. We will keep investing in all of those areas, but in terms of proportionality to revenue, it will moderate. I'm trying to explain the reasons why it does. It means R&D doesn't need to grow at the same pace as revenue going forward. We're obviously going to keep investing in AI. AI will likely to continue to grow. Enterprise will moderate. We're balancing between those two, but moderate as an overall share of revenue, right? That's about the leverage we're getting from the R&D investments that we have made. Every new capability we build in the cloud, and as we migrate more customers to the cloud, sits on a singular foundation because of the investments we've made. One platform, not lots of different platforms. We don't have lots of different apps we've built in M&A. We re-platform everything. It's a long-term R&D story that I'm going to be here in a long time. It makes a huge amount of technical sense for us, and it gives us that customer advantage as well. It means every incremental R&D dollar we do now benefits the entire cloud platform. A huge credit to R&D team. I can't explain to you how different this is to the vast majority of other SaaS companies out there, especially anyone with our breadth of product and customer portfolios. We talked a lot about the platform R&D investment, so people are gonna ask about AI. Look, every SaaS company has an AI story right now. We are trying to work out how we explain why ours is different, and we truly believe it is differentiated and different, right? I can tell you, having talked to that customer a couple days ago, they probably have seven, eight apps that have a chatbot, chat sidebar, chat thing, chat app, chat something. Majority of them are just utter crap, right? They don't work very well. They don't give you what you need. Why are we winning in that organization? 'Cause our chat is awesome. 'Cause it's backed by the graph, it's backed by contextual, massive amount of work in that contextual intelligence, smarts, and understanding of what it is. We built it properly. We built it really well. We adopt modern models, a whole lot of other things. It is a big investment. I believe it will pay off in time, and it's very unique. That's all I need to say about that. Context, you probably heard a lot about it this morning. I'm not going to repeat any of that. I'm happy to answer any questions on that. I do think in a world of increasing agentic capability, agents flowing around, personal agents, team agents, et cetera, our context is gonna become really important. I have a little video coming up, which I think will be hopefully interesting. We do think that is something that is both durable and expanding to our TAM. If I had to simplify from an investment point of view, it's really tricky to work out how to do this. We have tons of AI advantages. I try to get down to three. Enterprise is really hard. One of the reasons is that platform we've built, Rovo, Teamwork Graph runs on top of that platform. For those customers, we can operationalize that at quite some scale. When we have tens of thousands of AI users in some of these companies, that's a non-trivial thing to do, and most other vendors actually can't deliver that today. We've got that. We continue to add more and more permissions and compliance and controls alongside our customers as they're learning about AI alongside us. We're really on the cutting edge of doing that, and it's very non-trivial and backed by the Teamwork Graph and the platform that we've built. Permissions and AI don't go super well together. It takes an incredible amount of really hard work. Obviously you got the Teamwork Graph. We believe we have a big differentiator in our context and ability to context, not just across Atlassian apps, but across all the apps and work that we do. For those companies that have moved from the cloud to Data Center, the two examples I showed you, 15- 20 years worth of workflow data, code data, understanding of their knowledge, which we can give them back in a graph instantly that is accessible to all of their AI tools, is a really unique differentiator that I don't think anybody else has in availability today. We're not stopping. We're gonna keep moving that advantage. Hopefully you saw a whole bunch of examples today of this whole like, oh, Jira's gonna disappear. Call bullshit on that. As a control plane, as a part of the agentic and human collaboration, we see more and more customers using it. We've given you a bunch of stats. I've got a few more coming for you in a second. The Teamwork Graph, as we talked about this morning, what can I say differently? Most SaaS companies see only a slice of data. If you look at any of the people who live in a vertical, they don't see all of the information, which means they can't give you great answers. We see more, we have more links, we have more connectivity because of our breadth of workflows than most other SaaS companies, the vast majority of other SaaS companies, and I think we've built a better engineering system underneath that and a better platform. We believe that's different, and we have a singular platform. If you've got a lot of different platforms and your data's all scattered around right now, man, I wouldn't work there for the next couple of years. It's gonna be miserable. As we try to show this morning that it compounds. The more usage we have from customers, the more our AI model grows, the more that compounds the data they have, and we create a wonderful data flywheel. We're seeing this already working. Models are continuing to improve. That's wonderful. We have great relationships with all of the foundation model vendors. It's not our job. Our job is to take these wonderful models that are built and deploy them as quickly as possible into use cases that customers want. We're down to sub 24, 48 hours on full model transitions where we have it running in our gateway. We often get early access to all foundational model vendors now. We get it running in 24 to 48 hours of public usage, and we can start running 1% of traffic through it to see how it performs really, really quickly. If it works well, we can move it. If it costs us more money, but the results are better, we make these trade-offs. It's an incredibly advanced orchestration system that we have, but it's really important at the scale we're doing. We think it's a moat. We talk a lot about AI, so I'll keep moving quicker here. We've made the Teamwork Graph a lot richer, as I hope you can see from this morning. Lots of new connectors, lots of new types of processes, lots of new categories of content. Code was a massive lift. It is a huge differentiator to us, the code intelligence. Internally, it is getting used everywhere because the understanding of code is so critical to business processes, not just technical processes, and it's not just about writing the code. We see it used in all sorts of different ways. We try to show that with the example in Service Collection today, where in IT ops scenario to fix an issue, understanding the code makes a huge difference to how quickly you can fix an issue. Again, a true differentiator in that Service Collection space. How it does reasoning over all the connections, et cetera. The graph is just amazing, and now we're opening it up with MCP, with CLI, and with Dia. Again, if you want the breadth of what we're trying to explain here, as someone pointed out this morning, we showed everything from a terminal to a browser. There are a few companies in the world that can actually show you that and actually deliver all the R&D in between and huge customer benefits at all points. A lot of excitement there. I'll stop myself before I go on too long on AI and the cool things that we're doing there. Instead, I wanted to get one of our engineers to tell you about this. This is about a four-minute video, and it's kind of nerdy. Let you not hear from me for a second. Trying to understand what is the ROI of the Teamwork Graph for our customers? What is the opportunity for us if we can get this out there and show customers how it works? Watch this video. I hope you follow along and it doesn't go too deep. One second. Hey, folks. It's me, Kun here, helping us explore a good way to demonstrate how the context from our Teamwork Graph helps agents do our work better. I'm demonstrating this with two Claude Code side by side. On the left, we have a freshly installed Claude Code. On the right, we have exactly the same Claude Code, but with TWG skills installed. I'll show you. If I type skills here, we'll see there are only three skills. These are built in from Claude Code. If we do the same thing on the right, we'll see there are a bunch of TWG skills in addition to those three. These TWG skills will teach Claude Code how to use our TWG CLI to fetch context from our Teamwork Graph. That is the only difference between these two versions. We're gonna run the same tasks, both in the same PI platform. This is our platform integration repo, and I will paste the prompt here. The same prompt. This prompt, this task is a real task that's about extending a StreamHub pipeline to support some new events while keeping compatibility with relevant services. It's a non-trivial feature to add. We're gonna ask the agents to just come up with a plan, and not the implementation, just the technical plan. We'll let them run now. It's gonna take a while, quite a while, and I know it's not gonna be easy to parse like these two screens from two scrolling terminals. I captured the full trajectories from those two agent runs and visualized them here to help us see the differences more easily. The prompt we just sent was really about improving a Jira admin's Slack digest to remove already approved access requests from the pending list. We're watching the agents working in real-time here, and we'll monitor how the cumulative token cost and time spent and the outcome is. Here we can start to see, with TWG available here, on these sides, these agents, the first couple of turns was really mostly about searching for context through TWG search. It's searching for context. It found some Confluence pages, and it learned some of the right vocabulary for what to search next. Here I can show quickly what the pages are. These two pages are the pages that got found, and the agents read these pages. These pages largely just explained how the Slack, Jira integration works, and what the access request notifications, really how they work, what they do, and the product behaviors here as well. Even humans, we will find this context very helpful. And then the agent used code search to identify some other related files. Here we can see, some of these results can't even be found through typical lexical search. It was the semantic search index that found these matches, because you can see it's not exactly matched the keywords. That is something that was quite useful as well. The raw Claude Code on the left without TWG is just like jumping directly into the local repo and starting to read the files. I'll speed through this, the important thing is really, through these search operations, we actually found there is another repo that is a dependency of what we're about to change here. In this other repo, there is some very important context that can anchor the implementation we need to do here. Yeah, let's speed through this. Here we can see with TWG, the agent was actually able to produce the correct plan sooner and with less cost while the raw Claude Code is still running. Eventually, the raw Claude Code will also finish. The problem is that it lacked context and missed the related repo in its plan. As a result, the plan was actually just wrong. It hallucinated the eve-event schema and would actually send a duplicate notification to the users, which will be really bad. On the other side, we have a correct plan, that's because it got informed by the information, the context that exists in this other repo, which is really hard to find unless we do the search and content retrieval upfront. Claude Code equipped with TWG successfully identifies this hidden context and made the correct plan with less cost and less time. That is the power of context. The agent with TWG spends the first couple of turns, mostly on context retrieval before going into the local repos to do the work. The upfront context, found through TWG was really the key to its success here. If you have any questions, please. I think, hopefully Kun's given you some idea. That might have gone too nerdy. If you wanna just zoom out. The exact same agentic harness, in this case, Claude Code, probably the most popular at the moment. $2.68 to run that task, a real-world, quite complicated engineering task. Without Teamwork Graph, $1.32 with Teamwork Graph. Don't have to be a Brian-level genius salesperson to go to a customer and explain why we can help them. Secondly, we actually finished in a minute and 10 seconds less, and we got a better result. The code needed less tweaking afterwards. It was more clear because it did a lot of searching of the context first. It understood business and technical data to get a better result. Exact same coding engine, exact same harness. The only difference is we added the TWG CLI, and we obviously have a lot of our own code indexed, et cetera, et cetera, et cetera. Hopefully, that is a different example of the graph in action. You can multiply that across all the business agents that are coming across all the other areas. This didn't use people data at all in this case, but we have great access to that, et cetera. When we say cheaper, better, and faster with the Teamwork Graph, it's a very simple message to customers, and it's a very true message backed up, and nobody else can do this right now. It's not theoretical. It's already showing up in the numbers. Let me show you what we are seeing with some AI stats, some you know, some that I think are new. As we said in our shareholder letter, Rovo customers' AI credit usage, their Rovo credit usage is growing at 20% month-over-month. That is a pretty good number. We're early in the curve, but we're already a very large player in terms of AI model and usage, and the density of usage is growing very fast. Secondly, when customers adopt Rovo, they grow their ARR at twice the growth rate, and our expansion rate, as you know, is quite good, our NRR. They're growing at twice the growth rate of customers that haven't turned on Rovo. Lastly, it is delivering value, right? They are stickier. They move more. Again, we've given all these stats. I don't know if the 75% of the Fortune 500 companies that have turned on Rovo is a new stat, but it's there, and you can see our agentic automations are growing really, really strongly. One way of using agents, again, is through automations, putting them into various rules that happen automatically and can access all of the Teamwork Graph. Some AI stats. When you look at the Teamwork Collection, which is our primary AI monetization vehicle right now, again, north of 1,000 customers, 1 million seats inside the first six months of upgrades of existing customers. Some new in there, but mainly upgrades. Choosing to upgrade, why? You get roughly 10x the AI or Rovo credits when you upgrade. We have a lot of other economic advantages, and I would argue main advantages for the customer. You get the same number of Confluence, Jira, and Loom seats, which increases your collaboration broadly, but again, far more AI credits. TWC customers use twice as many. You consume twice as many Rovo credits per paid user as non-Teamwork Collection customers, and they have twice as many active agents. They have more credits, so you'd argue, "Oh, well, they've got more credits." They've opted in. Awesome. Give people more credits. They use it more. As long as that keeps growing, it's a really good wicket to be on. I say this often enough because sometimes I don't think it gets differentiated. These aren't roadmaps. These are delivered in-market features being used by customers today. We deliver the Teamwork Graph CLI today. The Teamwork Graph is used by all our customers and available to all our customers. They can log in at teamworkgraph.com and see it today. Almost nothing we showed this morning is not available today. It's like one or two features that are coming in the next maybe two months, three months. Everything else delivered on the day, right? That is our amazing capability. Obviously, you're saying, "Okay, well, how do we capture the value in that model?" We're gonna get asked about AI pricing and monetization, I put this together. I hope it's useful. We have multiple pricing models. We're trying to be customer-led. We're trying to meet customers where they are. Most of our apps are priced per seat. I still think that's the way most customers want to purchase software. When I talk to customers, that is what they say they want. We have a very generous number of Rovo credits involved in those per seat accounts. We have the price per seat. I'm sure you're familiar with that part of our model. These are sort of illustrative down the bottom. There's other things we could put in. Secondly, we do have usage-based pricing, consumption-based pricing. We have a growing set of consumption-based offerings, whether that is Rovo credits, whether that's Customer Service Management resolutions, Bitbucket Pipelines. We have assets, which is increasingly growing with some customers. We have Forge and Forge Compute and Forge SQL and our extension framework. We have a lot of usage-based models that are growing, right, and established revenue streams there. We have our hybrid pricing, so that is things like the Teamwork Collection. Didn't quite know where to put that, where you can buy these apps individually, most of them. You can buy the usage-based pricing individually, and then when you buy something like the Teamwork Collection, you get a set of those usage meters together inside that collection pricing, right? It's a different way of thinking about it. We have a flex-based model that we are working on with customers at the moment that we're actually talking to a whole bunch of customers this week, which is more of the overall sort of commitment-based model, as I would say, is a way to think about it. As our bigger customers that get well north of $1 million say, "Here's what I wanna commit to your platform. I wanna be able to move it around seats, move it around applications and collections, and I want more usage-based certainty," that is another model that we have. Again, we're here for the long term. This is us being customer-led as they ask. We have the ability to move around this. Again, I would say the early signals are strong. Customers using MCP grow their ARR at twice the rate of those that do not. The, "People who use AI will run away from Atlassian," I'm like, "Certainly not seeing that in the data." Seeing quite the opposite, I would say. Customers using our MCP server, that was before the CLI. We obviously don't have any stats on that. Early signals, MCP is a pretty advanced organization, so we need a lot more data to have that growing, but at the moment, twice the rate in ARR. As we said, our Rovo credit usage growing at 20% month-over-month, moves you between different pricing models if you're seeing value. I think I've covered all that. I didn't know where to put this stuff. AI isn't just adapting how we price, right? It's also creating new product categories. Here we have Focus and Talent and DX. The reason I put these up here, these are different applications to what we've traditionally sold. They're really only enterprise applications sold at large scale. If you're using DX to measure the productivity of an engineering organization, you probably have 500 or 1,000 engineers to start with, right? You're not buying this for 10 people. You don't need Talent for 10 people. You need to look around the room. As workforces adopt AI, we're seeing those customers, like the financial institution I showed earlier, they are using us in their, "How do I think about myself moving from AI novice to AI native? How do I look at my Talent, my skill mix? Who can help me see that?" DX is all about understanding how AI native my engineering force is and which teams, which services, which parts of my organization are faster and slower, which are using more AI and which are quicker and not quick. That is a phenomenal business. Wanted to make sure I put DX down there. It's ahead of our projections. We're feeling really good about that business. It's only a few months in, but again, all in that area, it's a not necessarily different pricing model, but a different type of application for us. Again, as we have these customers who've come in and opted into us as a platform, it's those customers that you saw earlier that are likely to open it up, and these are all used by the C-suite. As we continue our enterprise journey, I spend a lot more time with CEOs than I ever have, and CIOs. They're using these applications day-to-day. They don't probably sit in Jira so much, but they certainly sit in Talent. They certainly sit in DX. They certainly sit in Focus. They're very important to them. It helps continue our journey on that. There's a prerequisite for all of this. Martin's gonna kill me. We should probably talk about cloud migrations. A little bit of a topic. I haven't gotten there yet. I'm taking too long. Customers are moving to the cloud. We're doing really well. I think you know that, and you've seen it. It is the ultimate destination. It's the value of Atlassian. It's where customers get the most value. Can't get AI, can't get the Teamwork Graph, can't get anything. This, I think I should say, is illustrative, by the way. We've been very thoughtful and systematic, I hope you can see, about our multi-year, decade-long cloud transition, both in terms of the building of the future ahead and moving customers. I think we've executed extremely well across the hundreds of thousands of server customers. Now we're getting to the Data Center customers at some scale. The migration itself still has a ways to go in terms of the number of seats we have in the Data Center. That's a good sign. What does this look like? What is an illustrative example of customer pricing? It's always hard, I picked an example. 93% of our Data Center customers that are upgrading to the cloud are landing in Premium or Enterprise. I know this because in some of the models and some of the things we've seen, you can think, "Oh, well, the Data Center customer could go backwards moving to Cloud Standard." That doesn't happen for 93% of those Data Center customers. It can mathematically happen, I thought it was useful to say this. This is a, what did we put? 5,000. Oh, sorry, 5,000 user Data Center tier, that's 4,200. Again, in the cloud, you buy what you need. You don't buy sort of bigger tiers infrequently, we've talked about that in the past. The interesting part, this probably isn't news, the interesting part is what happens after they migrate. Now we have many years of history of moving large-scale customers. Let's look at multi-years. Let's take a three-year period. Let's take 1,000+ user customers, only the large customers have moved. 1,000+ users that have upgraded to the cloud. What happens in their three years after they move to the cloud? Well, they grow about 1.75x, 1.5x-2x growth in the three years after they migrate. Why? All those things I talked about before. Seat expansion, cross-sell. They can get Focus, they can get Talent, they can get DX, they can get the Product Collection, they can get the Service Collection with all the capabilities. You saw that in some of those customer examples earlier. It's saying that we're being successful at moving those customers, and when we move them, we have a good couple of years after they move. They continue to expand their footprint after they move 'cause of all the reasons we've talked about, and their ARR growth continues strongly after they migrate. We're not collecting all of the value at the point of upgrade. In fact, we're trying to trade that off over that three-year period. You've probably seen this chart before, but the cloud is not a flywheel, right? Sorry, it is a flywheel. What am I talking about? It's not a single project to upgrade. It is a flywheel that moves into the cloud, and they continue to grow. That's what we're trying to show over time. It allows us to continue to ship our AI faster, monetize all those new use cases, capture those workflows, right? Compounding our momentum with consistent 120%+ NRR growth at scale. In the cloud, that is what we're seeing. We had this rainbow chart when we went public. I love that we just keep adding years to the rainbow chart, and it keeps going. We have a huge opportunity. We're crushing it with customers, voting ever more for us as a platform. We feel incredibly strongly. Brian will come up. You will hear from him. Our cloud growth is extremely healthy. Our AI progress continues to be extremely strong, hopefully you can feel from me and everybody on stage, we're so bullish about what we're doing in that area. NRR, 120% strong. You might be asking, it can be difficult to see this in your financial statements, on the face of your financial statements with ASC 606 through this migration. What can we talk about that? Well, I wanna cut through a little bit of noise before I hand over to Brian. Again, is anyone familiar with this logo? Extra points for investors if you can tell me what it means. Open Company, No Bullshit. Open Company, No Bullshit. Love it. Yes. This logo means "Open Company, No Bullshit." It's one of our five company values, we wanna be direct, right? 2024, two years ago, we issued expectations on a three-year, 20%+ revenue CAGR through FY 2027. Since then, we've had a few major changes. In September of 2025, last year, yeah, that's right, calendar year, we announced Ascend, so the end of life of Data Center by March 2029. First thing I wanna stress, that is a great thing for our customers. It's a great thing for our R&D organization and our business. The challenge it's made for us, we were a year ahead of schedule. We delivered Ascend in September of 2025, not September of 2026, due to all the enterprise progress we had made and the R&D we invested in. That was ahead of our schedule. That's great for customers. That's great for our business. Enabled us to accelerate our customers' journey to the cloud. However, as a result, as you saw last quarter, that creates three interesting dynamics that affect the Data Center revenue line. First, with ASC 606, we moved from 20% upfront revenue to 50% upfront revenue. When you model that with the one-year acceleration, creates a challenge for us on the license line in Data Center subscriptions. Secondly, we moved our customers, which was not predicted three years ago, from multi-year deals to one-year deals. Couple of reasons why we did that. Firstly, when you have a three-year end of life, you can't sell someone a three-year deal a year later. It doesn't make any sense. Secondly, we wanted to have multiple opportunities to talk to that customer. We've moved the vast majority of our Data Center customers to one-year licenses. Model both of those together, you see what the effect is. Those one-year licenses give us three opportunities to talk to that customer over time. They often say, "I get it, but not right now. I've got busy things. There's this AI thing. Have you not heard about it?" We have a conversation. Yes, we're good at that, et cetera. Lastly, Data Center customer purchasing patterns have continued to emerge and accelerate as we move to cloud. Again, all these are good things. We saw that play out in a pretty big way last quarter, as I know a number of you've read about, with a lot of pull-forward activity into FY 2026 from FY 2027, which results in greater licensing revenue in a Data Center in 2026, far more than we had expected, which is a good thing. In general, timing dynamic creates a problem. We continue to see strong cloud growth rate, great for our customers, great for our business and Data Center retention. The greater term revenue in 2026 in Data Center, we now expect negative Data Center revenue growth in 2027. We've pulled all that forward, which is a great thing for us. I tried to explain this both Open Company, No Bullshit, and I'll give you some illustrative charts. I thought I'd say all that so you were listening and I saw you were writing before I showed you the charts. This is an illustrative revenue growth. Number one, we're expecting a trough in total revenue growth in FY 2027. Number two, we expect that to significantly re-accelerate in FY 2028 as we lap that Data Center effect going through. You can see why that one-year acceleration is a credit to the engineering team, creates a challenge for the finance team. Given these dynamics, the three-year 20% CAGR that we set two and a bit years ago is no longer a relevant target to anchor on. What is relevant and a much better measure of the strength of our business is ARR. Again, this is illustrative. Don't get out your rulers. Why is that? Well, ARR normalizes the effect of ASC 606, that revenue recognition, and helps everyone, I think, much better understand the overall health of our business. If you take ARR subscription business, so Data Center and cloud, put it together, do a lot of great mathematics that our finance team is able to do, you see a very different pattern. Here is our subscription ARR for the last seven quarters. What you can see in the last three quarters is a pretty good pattern of acceleration of ARR at the overall level of the business. One of many indicators, but I think a really strong one, showing how strongly we feel about how our business is operating and trying to explain the dynamics between all of these different things. I'm sure we'll have time for questions on that. Last one, I wanted to talk about one more thing before Brian comes on. What do we mean by the phrase durable profitable growth? Well, I hope we've shown that we have a durable growth story, both in our results and in the go-forward opportunities we have in AI, in the system of work, in the enterprise, and all the things we're doing in cloud, the customer stories, the customer scale, all the things we've done. The profitable word is also really important to us. We've been a capital-efficient business for 24 and a half years, and I think I will make sure that we are continuing to be so. We also expect, as a result of all the changes that we've made, that was not taken into account two and a bit years ago, to accelerate and grow our GAAP operating profit beginning in FY 2027. I'm sure we'll have more on that in the future. Wanted to put the profitable and the durable and the growth, all three words incredibly important to us. We've made a lot of the great investments, enterprise, AI, system of work. Hopefully, they add together to see why we have that durable profitable growth rate over time. You probably want to hear a lot more about our large customers. Let me bring up Brian, our fabulous hero, who has lapped one year and a little bit in the seat, so he has a lot more to tell you than he did a year and a bit ago. Here's Brian. Thank you. Thank you, Mike, and good afternoon, everybody. Great to be here with you. I, as Mike said, I've been here a little over a year, and I guess I'm still relatively new. At least I'm running with that. I'm regularly asked, you know, why did I join Atlassian? The answer for me is pretty simple. That is when you look at Atlassian, we are a very unique company. We obviously are known for the incredible PLG motion that we have, and we have scaled the business to be billions of dollars, as Mike has laid out, and we also have 350,000 customers. We did all of this without having a mature enterprise sales team, and many other enterprise organizations would say that they have somewhat similar ways of an acquiring customers, but in reality, they don't. For me, when the reason for me to join is because we have the opportunity to take that massive frictionless flywheel that we have, where customers really love the product. When I joined, Mike knows that I regularly said, "I'm surprised by how much our customers really love Atlassian and love the product," and they were expanding with us organically. Now the opportunity is to layer on top of that a world-class enterprise sales motion. Importantly is that at the same time, we're not moving away from our PLG heritage, and that motion is still running at the same time. Instead, what we're doing here is we're going to be spinning a new gear, and I'm hopefully going to show you exactly how we are aiming at doing that. For me, really this starts with the foundations, and you cannot build a great enterprise sales foundation if you don't have enterprise-grade products to ultimately back it up. If you look at the landscape today, and you see the slide behind me, Atlassian is recognized as a leader across all of our major product segments. We are putting the necessary sales muscle behind these products in order to capitalize on the opportunity ahead of us. The good news is, as you saw on the slide in terms of the ARR growth, we are already seeing the positive momentum. Over the last few years, we have been evolving the business itself, and that shift is still underway, and the transformation is an evolution. In the 16 months that I've been here, I've been very pleasantly surprised with the progress that we've made and the wins that we have under our belt. I wanna go in a little bit deeper in terms of some of the numbers that prove that the motion is working. In Q3, our volume of deals over $3 million surged by 79% year-over-year, which we're very proud of. It's not on this slide because we just decided to add it last minute, but over the past year, we saw a 54% increase in deals over $5 million. That obviously is something that is significant and has a strong contribution to our ARR and RPO. Now, not only are we closing more of these larger deals, but the ASP at the same time has also jumped, and that's jumped by 22%. The best part of all of this is that we're not feeding the larger deals at the price of the smaller transactions because what is happening is that our smaller deals are also growing at a clip of 32% as well. All of this is happening with our retention rates, like Mike said, at 99%. When you step back and you look at the business. You can say we're firing on all cylinders from the top of the enterprise into the middle of the pyramid, and then at the bottom of the pyramid as well. There's no piece that we are sacrificing. At the same time, it's not just about the size of the deals that we have, it's also about the durability of those relationships. Something that obviously is hugely important to us is the timeframe of our commitments, and our customers are now committing to us for longer timeframes. As we shared in Q3, our RPO grew to $4 billion, and that is an increase of 37% year-over-year. I know you regularly ask, you know, as these customers migrate to the cloud, what happens thereafter? The good news is that they're not sitting still with us, and neither is my team of sales people. They're driving customers to expand in the cloud and expand across the Atlassian portfolio. Our team is focused on uncovering new opportunities for our customers and driving product adoption. Also cross-selling into new collections and at the same time closing complex high product deals as well. Our customers, it's fair to say, have more options than ever before, and they are clearly voting with their wallets, and they are expanding seats across our core products and adopting our additional offerings. In terms of when we look at our collections, that certainly is being led by Teamwork Collection, and as Mike said, that is our primary motion for AI monetization, and then being led by Service Collection, which you saw the numbers there in terms of the size of that business. We're continuing to make progress there. If you look at the slide behind me, you can see the outcome of the strategy, these are just some of the logos that have placed their trust in Atlassian over the years. Many of these have been customers for 20+ years, their footprint has grown with Atlassian. One thing that I would stress is that these brands grew their footprint firstly by themselves without having an enterprise sales team in place, which speaks highly to the product, first of all, and then also speaks highly to the ecosystem that we have. I thought it would be interesting, similar to what Mike did earlier but with a little twist, to show you one of the brands and the evolution of that particular brand. The brand that you can see behind me is a semiconductor company, and they have been a customer of ours since 2015. They were a low-touch customer, so there was no account team associated with this customer. A story we've seen many times over. They were a Jira and Confluence on-premise customer, and they were experiencing hypergrowth. This particular customer had internal systems that were just not fit for purpose, their management made the decision that they needed to transform and that they needed to modernize. In 2023, you can see that we made the decision that we would assign an account team to this particular customer. We consciously made the decision that we would build relationships across the entire business. At the same time, as an enterprise sales team, we would also build relationships with the C-suite within this particular customer as well. We were not pitching a lift and shift to this particular customer. We were pitching a complete transformation and reimagination of their business, and we were doing that in conjunction with our partners as well, all obviously to fuel their hypergrowth that they were experiencing. Now, once an enterprise account team was in place with this particular customer, you can see what happened to the investment here. It multiplied because obviously they bought Strategy Collection, they bought Teamwork Collection, they bought Guard Premium, and they've invested in advisory services as well. Now, this customer is just one customer journey, and I could have shared many others with you. What's particularly promising to me is that we are hiring and are building out the organization, but there are many stories like this to come where we will have a similar journey and a similar investment projections, which are obviously going to change. We will see many similar stories like this as we move forward. Now, even with these wins across our enterprise base, it's fair to say that we've only scratched the surface. We have a $140 billion total addressable market, and we have an incredible runway in front of us with our 350,000 customers. We also have a massive opportunity to go out and attract net new logos as well. I walked you through the opportunity, but you know, internally we are obviously looking at how are we going to go after and capture this opportunity. We have a transformation, and there's a lot of work happening behind that transformation. Today I wanted to walk you through just two particular pillars, which is customer-centric selling and our partner ecosystem, and give you a little bit more detail around what we are doing in terms of those pillars. When it comes to customer-centric selling, we are evolving the go-to-market motion within the organization to become a trusted strategic partner to our customers. Obviously coming from a PLG motion, this is a complete transformation of the Sales team and the VAT team and the pre-sales team around it. We are now engaging, like I said in the example beforehand, with the C-suite to deeply understand their business challenges so that we can help them address those business challenges. We are now delivering business outcomes for our customers. In many respects, we are slowing down in some of our deal cycles so that we can actually grow the transactions, and then we can speed up, and then we have a better result at the end. This is translating into stronger customer wins, as we said, in terms of the logos, secondly, in terms of the value of the deals, and then in terms of the length of the commitments from our customers as well. Secondly, we've also realigned our sales incentives to reinforce our strategic priorities. We are now enabling our AEs to focus on the outcomes that matter most strategically to Atlassian. We are incentivizing them in a big way to uncover new value within our customers, obviously focusing on our collections and expanding our footprint within these accounts as well. We now have a specialized sales force for those collections, which are focusing on new demand within each one of those customers. As you can see from the numbers that we've put on the board, uncovering new value and new demand is also playing out in our favor currently. We are pointing the team directly at our biggest growth levers, and I touched on this already, which is customers are expanding across our collections, and our team is looking at ways to grow accounts, which is great. We are in a very fortunate position that we have a lot of white space around the world as well in terms of countries where we are not present and we have an ecosystem that is present. We are also operating in high-growth markets as well, where we are making investments, where our customers are present. That is in countries like the U.K., France, and India, and a few more. It's very clear from where we sit that the demand is there. We are expanding our growth horizon. We're prioritizing new markets and cross-sell opportunities through our collections in order to unlock that incremental revenue and opportunity at our customers. Now, to capture this opportunity and to sell to these enterprises, we're obviously making investments and to ensure that we have the right amount of resources, quota carriers. What you can see on the slide here is that four years ago, believe it or not, Atlassian had 117 quota carriers. The sales force was 117 people. Since I have arrived, we have grown that to 400. I constantly remind Mike and James of our productivity, which you can do the math, is best in class in the industry by far, and we are clearly punching above our weight. Obviously, as we moderate the spend in R&D and we look to make the investments in sales, we obviously have an opportunity to continue to make significant improvements here as well. We aren't just adding headcount blindly, I would say. We are tightening our coverage ratios when we look at where our customers are. We are increasing our quota carrying capacity relative to the overall sales headcount that we have, and we ultimately are building a very mature sales organization. What's exciting is we have the opportunity to learn from the mistakes of many organizations who have gone before us, which is an exciting spot to be in, and that gives us the opportunity to scale it very efficiently also. Now, even with the 400 sales reps that we have, we know that in order for us to capture the opportunity that we won't be able to do it by ourselves. That brings us to the second area that I said I'd mention, which is our ecosystem. For the first time at Atlassian, we are now partnering with the GSIs. I think that's particularly important because obviously, if the GSIs are involved, this speaks highly to the opportunity that they see. We are now partnering with Accenture, Deloitte, and PwC in a big way. They are giving us access to the C-suite at a scale that is unprecedented for Atlassian, which is great. Earlier this week, we had Mercedes on stage. Mercedes is a customer where we partnered heavily with Deloitte and would not be in the position that we are with this customer, if it wasn't for the partnership there. At the same time, our partners are building out dedicated solutions to drive collections and AI adoption. Earlier this year, I was with Infosys in India, and they have just launched a center of excellence in order to support their booming Atlassian practice as well. Now when we look at Accenture, where we have a very deep relationship, they are also driving significant pipeline for us personally. I would add that we're tracking all of our GSIs in terms of the incremental new pipeline that they are bringing to the table for Atlassian. We're continuing to see an evolution of our relationship with those GSIs. Now at Team 2026 this year, we have over 1,000 partner attendees, and I spent time with them on Monday, and I explained to them how we are committed to helping them evolve their business also. You all know that in the earlier days of Atlassian, we would reward those partners really on a transactional basis. We are obviously now changing that. We are now shifting our incentive structure really to be towards high-valued strategic services. We want to help them grow their services from a 1-to-1 to ideally a 1-to-3 or 1-to-5 ratio. We are making the necessary investments to help them grow that businesses as well. We are seeing a return already because we are seeing by incentivizing them in terms of the right behaviors, that that is leading to a higher adoption for us and better customer outcomes as well. This is obviously a big evolution for the ecosystem overall. Now, this is obviously a I've walked you through the combination of our product-led foundation that we have, our enterprise sales muscle that we are building and evolving, and the ecosystem, which is critically important to us. I could share with you a lot of numbers and a lot of slides around how we're very successful and how we're knocking everything out of the park. Instead of doing that, it's best if I could welcome onto the stage two customers who can actually share with you what it is we are doing. If you could please join me in welcoming Jason Andrews from Cisco and Stéphane Baumier from CANAL+ to the stage. Gentlemen. Thanks. Thanks. All right. Well, thanks for joining us, first of all. Appreciate it. Maybe we will get started with you guys quickly telling us about the company and then what you're responsible for. Jason, we'll let's start with you. I'm with Cisco Systems. I run the engineering operations function across our product development, specifically for the networking business. That results in a like kind of helping guide the how engineers work for around 25,000 users. I also have a couple other functions in program management process ownership, which is a real asset. On the back end, having our global app services, which is like a large Data Center environment. Thank you. My name is Stéphane Baumier. I'm the CTO of CANAL+ Group. Perhaps you know CANAL+, but in the U.S. it's not so famous. CANAL+, it's a media and pay TV company, a French company, which is based in Paris, headquarters in Paris. We broadcast pay TV in Europe and in Africa. It's a EUR 7 billion of turnover, to give you an idea of the size of the company. We have more than 40 million subscribers. After, I will give more information in the link. Thank you. Okay. Great. Jason, Cisco, obviously a company everybody in the room knows, has evolved over the years and has one of the most complex and operational footprints in the world. When you look across the organization, our relationship with Cisco has evolved. We initially had been, let's say, viewed as a tool that you were using, and I know from the conversations that we've had, we're now viewed as being a mission critical to Cisco. Maybe you can share with everybody how that has evolved over the time. Yeah, it's definitely evolved fast, and I think it's evolved in the way we work, right? A lot of ways, if you view it as a tool, you'll only have a tool. We look at it as a platform to deliver product. As we start to leverage things like the Teamwork Graph, again, bringing all this work we're doing across 25,000-30,000 engineers, making collaboration easier. At a large company, if you work in a large enterprise, collaboration is the hardest thing you're gonna do. Building a product in a single team, super easy. As you start to say, "I'm gonna blend, you know, security into the fabric of networking, I've got to get the security group, I've got to get the networking group on the same page," it's extremely hard because they have different models of working. As we started to align those groups, we've seen great results in terms of how fast we're able to deliver product to our customers. What's awesome about this is we've actually seen huge gains in productivity as we leveraged a teamwork concept or a system of work concept. We saw as much as for about between 18,000 and 20,000 engineers, an estimated 5% uplift in productivity just by adopting a system work. On our own side, we actually saw like a 40% reduction in our TCO of actually managing the platform as a whole. It's been a great journey. Awesome. Stéphane, anything you wanna add in terms of the journey that. Yeah. CANAL+ has had? We have the same idea. In fact, as CANAL+ is a 42 million subscriber, we would like to target to 100 million with organic growth, also with acquisition. Acquisition means M&A, at this moment convergence and synergies are key. Atlassian is really a part of the suite to be able to manage this convergence and to adopt all the same process and the standardization that we can have in the different countries in Europe, can be in Poland, in France, also in South Africa. Great. Stéphane, you had shared with me how you've moved to a unified system of work- Yeah. ...as well, and change your global decision-making and collaboration, system. What happens, you know, within CANAL+ if, let's say, that was to go away? That's a good question, especially in technology. I worked since more than 30 years now in technology, and I have different job in the world and not in Europe, in Africa and in Asia. I was a CEO and CTO, so I have to manage both side. I was appointed as a CTO to create a global technology department with 6,000 people. Standardization is a key to have the exactly the same. To answer to your question, if it's going away, we will continue to stream. We'll continue to broadcast some live sport to use a satellite and OTT tools. The key is to take some decision for the projects because we can have some project in Poland, in South Africa, in Senegal, in France or even in Myanmar where we broadcast. From this, if we don't have any more, the different system to do it, we will not be able, and we will have to do what? To have new Excel file spreadsheet, hours of meeting, discussion with finance, and to take this decision will be so complicated, which is not the case today. Awesome. We know the criticality of Atlassian within both companies, and we know that AI is top of mind for everybody, including both of your companies. Maybe Stéphane to you, can you share with everyone how And I know you're a Rovo customer as well, so you can share with everyone how Rovo is helping accelerate the decision-making within CANAL+ and how you're utilizing Rovo? Yeah. AI is a key. It's a revolution for everybody. There is a lot of promise in two years that we'll have 50%, 60%, 70% of productivity. When you have to manage a worldwide company and worldwide technology, you need to have a P&L also and to have some results. Each choice that we have to do with AI have to answer to different subject: cybersecurity, finance and usage. For cyber and for finance, we use Rovo because we know all and we validate all. After for the usage, it's not just a key for the tech department, it's a key to deploy in the different department. For example, if you have to manage project, the CFO of the group, it's EUR 7 billion of turnover for CANAL+, for example. When you have some question, what he did in the past, he asked me to say, "Okay, what is the cost of the program? Where is the program? What is the CapEx? What is the OpEx?" All we have to do some meetings, as I said before. Now with Rovo, he's able to ask directly for any project, any programs and to do this kind of validation. That's a very crazy situation for us and very useful. The dynamic can be that the CFO of France, of course, but of Poland or South Africa can ask the same question for his own project. Just one thing so it's clear for everyone, like Atlassian's footprint within CANAL+ and then how Rovo is being utilized, it's not solely within IT as well. Yeah, exactly. In fact, at the beginning, we use like a lot of company Confluence because we have all our documentation, after we start to use a different suite of Atlassian. Last year with Team 2025, when we discover Rovo, we said, "Okay, this is the key now to be sure that we can deploy all this suite for all the departments which are not technical. Great. Jason, anything you want to share in terms of Rovo? I think we're seeing a lot of value and really focusing a lot on the time to revenue aspect. A lot of times A lot of people are focused on engineering productivity 'cause it is obviously the huge win and kind of early focal point of AI. Really what we're trying to look is leveraging Rovo to actually run different business process for us, right? How do you actually standardize and automate the reporting? How do you make these things faster? How do you stop spending time pulling status together from, you know, different pages, meetings, everything, to actually focus on solving the risk and issues? We're seeing the team really lean in heavily to it. Our Rovo usage is going through the roof. It's great, right? I'm getting great feedback from the team and how it's making their jobs easier, how it's easier to collaborate across the organization, even ones that aren't on our system of work. Again, we're still getting everything together from the outside teams. As those teams need to bring features and data that are tracked in a slightly different way from this instance to this instance to this instance, it used to be that was a very manual spreadsheet-driven process. Now leveraging Rovo, we automatically pull that data in. It creates dashboards. It does all the things you need to do, so people can focus on managing risk and issues and not bring status reporting as their primary job. Maybe in terms of the transformation from a change management, and maybe both of you, if you wanna show the change management a difficult process? I think it's impossible. I think at the speed that AI is going and people keep saying that the change management, and I think we're spending a lot of time kind of trying to democratize AI, make it very easier for users to leveraging the Atlassian platform, pre-built agents, and things that people can get value by without having to understand system architecture, code design, all these kinda crazy things. I laugh when it talks about change management. What I thought we were gonna be doing with AI 60 days ago is different than today and definitely different than a year ago. It's a tough ask, I think. Yeah. That's tough. Change management, it's human, in fact, human relation to be sure that people can adapt what you would like to do. What we need to be able to change the way that we manage this is to go to create a clear strategy that we can adapt for each country. For this moment, as a human adapt the strategy, we will be able to know exactly where we go and where we would like to go. At this moment, they will be ready to change. It's not so easy for sure. Maybe Stéphane, do you wanna share with everyone your vision in terms of the future of exec reporting? Our dream is that, in fact, you use, for example, Loom. You just record a video because you have an idea. You can imagine you are in Johannesburg or in Dakar. You have an idea. You record your video. You have an automatic translation of this video to create the project in the system. Everybody, all the countries are aware of this new project and can start and to expand it. This is really our future, what we would like to target, especially when you are in different countries with different culture, to have one common product where it's easy to speak in your language because we have many languages. It will be easy to speak, to translate, and everybody have this information. At this moment, we can create all the process to create it with the Atlassian suite. This is really key for us for the future. It's where we go, and we hope Atlassian is going in the discussion that we have during the different conferences really is the path in fact of Atlassian, so it's been interesting for us. How do you see our relationship evolving in the future? With this very good, as I said before, we define a global strategy for the group to be able to manage M&A. When we define the strategy, we define a list of trusted partner where we have a good relationship. It means that we are confident with partner not only in term of legal, in term of finance, but also in term of product. It means what is important for us is to have some partner like Atlassian or Datadog, for example. We have 10 partners which we select, when we can exchange about the product and to give some advice, if we can say advice, or what we would like to do, what is our dream. For the moment, each time we have this kind of discussion, we saw that it's coming after a few months of two years. We have a call, say, "Okay, we have these features. You ask it for one year ago, and we have it." The relationship is really important, not only on the contract and the finance, but the relationship and the trust that we have and to create the future of this because the evolution is very big. AI is a revolution for everybody, including for you, so we have to be confident in cyber, finance, legal, and to be partner in fact more than to be just a customer and a reseller. Great. Then maybe Jason to you, as Cisco's business, you know, continues to evolve and change and grow, how do you see Cisco's relationship with Atlassian evolving and then the reliance that Cisco has with Atlassian as the business is gonna continue to change and evolve? I think it continues to be this massive partnership, right? There's a lot of, you know, 360 relationship. We go back and forth. Obviously Atlassian really steps in and leans in when we have problems, so I think the relationship couldn't be better from an enterprise server standpoint. I think when you look at the future and how it scales with us, it really is doing a great job. It's literally leveraged, I think, Mike Cannon-Brookes today in the thing said it was something that really is impactful to me is he said, "Acceleration is context times intelligence," right? I think that is really where we're heading as we start to develop AI native applications, things that are written 100% in this Vibe coding method. The system will work, and the framework is kind of required to do that, right? You're gonna need those, the product requirement doc, built with the feature linked, the dependencies tracked. In a program management space, we're leveraging Rovo to go out and look across our entire stack to help us identify dependencies we were not aware of, right? All of these programs and these motions are going at constant pace. We deliver around 15,000 features a year in networking alone. That's These are top-level epics. We have about six engineering epics to everything, so you're really talking about a platform around 80,000- 100,000 features. It's impossible for a human to track and connect how they work. Something like Rovo, it's really made our job in driving visibility into the work we're doing, is super impactful. Awesome. Great. Maybe and to close this out, maybe, and Stéphane we'll go to you, maybe you want to kind of wrap it up in a short answer in terms of like the ultimate business value that we drive to share with everybody, the ultimate business value that we drive for. Yeah. CANAL+ In fact, I think we have three business value. One is, let's say, more about compliance. We are a listed company in London Stock Exchange and very soon in Johannesburg, so we need to have some partners that we trust, and to be sure that the process will run for a daily basis and 24 hours per day, seven days per week. Which is really a key success for us in term of business. The second one is really operational. What I said before, Atlassian suite is more for technology department, but more and more for all the department of the company. This is the business value what we'll bring when we start to set up the application on the smartphone of the CFO to say, "Now you just have to check for the project and to have the cost of the CapEx and what we spend or what is the status of the project." The last one is more for the development. As I said, we would like to continue our development with M&A. We have some shares in Viaplay, for example, in Nordic Europe, with Viu in Southeast Asia, it's a company we have around 30%. Each time we do some M&A, each time we bring in our suitcase our partner to say, "Guys, now we know exactly how to manage the convergence and the synergy," which is a key for all the M&A. Atlassian suite is a part of it. If you do the addition of the business value for this operational, this compliance, and the organization, it's really key for us, and it will be the value at the end of the day for us. Awesome. Great. Jason? I think the ultimate business value if you break it down is it becomes a platform to deliver product, right. Our time to revenue improvements that we kind of or I mentioned earlier. I think the real power is it gives you the context in the system, and it also helps you orchestrate it, which again builds a platform of collaboration for teams to centralize that work on, and it really helps them stay in touch. It's incredibly hard in an organization. I can't reiterate that point enough, and they've really done a good job of kinda helping us lean into that and get this sorted. Great. Well, I want to thank you both firstly for the partnership and the trust. Appreciate you coming here and sharing your story with everybody. I have a great job because I get to spend time with awesome customers like this every day. If you could join me in giving these two gentlemen a round of applause. Thank you. All right. Thanks. Thanks for running through, Stéph. Thank you very much. All right. With that, I'm very happy to hand over the clicker to the new guy- Here we go. James. If you can give James a warm welcome. Good evening, everybody. You know, I consider myself really lucky to be able to kick off my Atlassian journey right here at Team. This is my first one, and it's been really inspiring to spend time with our customers, our partners, and so many practitioners and users that are super passionate about the Atlassian platform. Before we get to Q&A, I know a couple of you asked me last week during our call backs, you know, what drew me to Atlassian, so I thought I would just share a couple thoughts. First, I would say that, you know, I've long admired Atlassian, you know, this amazing culture of innovation and this very powerful mission of unleashing the potential of every team, right? It's such a powerful and enduring mission in many ways, sort of an infinite TAM. I've got my GC back there waving, saying, "You can't say infinite TAM." You know, we know there's a lot of noise right now in our market. If you punch through that noise, what I see is an incredibly well-positioned company, right? One that has a diversified and durable set of businesses building a platform that's serving over 350,000 customers and hundreds of millions of workflows. I've been in the role now for a little over a month, and that conviction has only grown. There's a couple of reasons for that. The first is that we are incredibly well-diversified, not just across tech teams, but non-tech teams, business teams. It's allowing us to play in these massive expansive TAMs with line of sight to $140 billion of opportunity. You saw some of that momentum play out in Q3 with the outperformance that we saw in TWC while also expanding our Jira seats on our standalone offerings. You saw Service Collection grow to over $1 billion in ARR, growing 30% year-over-year. That value, that ROI that we're delivering to our customers right now is positioning us really well across all of these segments. The second is how well Atlassian is positioned within that enterprise workflow stack, right? Serving not just developers, but HR teams, finance teams, legal teams to help them collaborate and manage an ever-increasing amount of workflows. That's only more amplified with AI now. It's early, but we're still seeing a lot of amazing traction. Mike talked about it a little bit earlier. AI credit usage growing 20% month-over-month. Customers that have unleashed Rovo, they're deploying 2x more agents. They're using 2x more credits. Rovo customers are growing their ARR at 2x the rate versus those who haven't yet, the keyword being yet. That's off to a great start. You heard from Brian just now the progress that we're making across our enterprise motion and with our partners, and a ton of headroom still with us being penetrated into 85% of the Fortune 500, but that only represents 10% of our revenue. A lot of headroom still ahead of us here. Maybe finally, you know, you heard Mike talk about it a little bit earlier. We talked about this in our shareholder letter, last week as well, which is alongside AI enterprise and system of work, we're elevating key strategic priority of driving durable, profitable growth, right? You heard me talk about it a little bit earlier. This culture of innovation, that's a big part of what drew me to Atlassian. It's what drove all this enterprise value over the last two decades. We're gonna continue to reinvest in areas that's gonna drive the pace of innovation and scale that's required to win in this era. We're also gonna do that while driving a culture of strong fiscal discipline while we accelerate our path to GAAP profitability. Just a ton of opportunity here. Really excited to be here. It's a privilege to partner with Mike and the entire Atlassian team to really steer this next stage of growth for us. You know, it's a wonderful time to be in our market right now, and it's an incredible time to be at Atlassian. Thank you all. All right, with that, why don't we go into Q&A? I'll ask Mike and Brian to join us. All right. We'll open up for Q&A. It's hard to see with the lights. I see Gregg in the front row, so we'll start with Gregg Moskowitz. Hold on for a mic. All right. Thanks very much. Gregg Moskowitz from Mizuho. Great presentation. Mike, you know, the fact that Atlassian customers will be able to use MCP and other external tools to query the Teamwork Graph, add to it as well, super interesting. What does this mean, though, not only for your relevance over the long term, but also your ability to continue to grow at a healthy rate? Why is this going to be a winning move for Atlassian? Why is it gonna be good news for Atlassian? Let me give you three reasons. There's probably many. First, again, we're seeing the current We've had our MCP server in market for six months or so, something like that. Quite a lot of adoption already, growing very, very fast. The customers using it, and we're quite a medium to high level of adoption. It's hard to know. There aren't a lot of MCP stats around there, but we believe we're certainly in the top handful of used MCP servers at scale anywhere in the world. Customers using it, as I mentioned, are growing significantly faster than customers that aren't using it. If they're the AI native organizations or the most forward-thinking, the early signals we have is that that really helps accelerate because they can do a lot more on the platform. Those customers are in the cloud, they're using Rovo, they're using the MCP server. That generally will result in more workflows. The data we have so far, it's very early, is very good. Secondly, it allows them to do many more workflows, right? They can use other apps. The example we showed on stage, Figma, a lot of customers, Figma, Atlassian overlap, good partner of ours. We use a lot of Figma things. They use a lot of Atlassian things. The customers that use both of those is a large subset. It enables both platforms to play with each other in terms of data exchange and usage. It makes Figma make better to be able to access the Teamwork Graph. It also will result in write backs to the Teamwork Graph. It grows our graph, which then makes the next operation. Maybe you then move to Claude Code to code after designing or something like this. That's gonna help us from a network effect point of view, if you think about sort of the data network effect of the Teamwork Graph, right. People that are reading and writing from it, the more access there is, the overall the graph size grows. It also keeps it fresher and newer because it's the active workflows that are really important, right. The latent graph is not. It's how it's used over time and continues to evolve and grow. Lastly, there is a good angle for us in terms of being more actively used by customers. If we are more actively used by customers in a generalized sense, I always believe that is better for us. We don't have a lot of data on this yet, but if you look at the very, very small amount of data, that seems to be true in like MAU and all sorts of other signals as well. I think there's a lot of reasons why I would generify MCP to like app and agentic usage of our AI stack, if you like. There's a huge amount of AI that goes into making the Teamwork Graph. We obviously have a Rovo credit story. Again, too early to see how that one pans out, but we feel very confident about it. Overall, both the CLI, the MCP, and other usages I think are very, very positive for our overall story. I guess I'll go Peter Weed in the front. Gotta keep the mic up here close. Peter Weed from Bernstein. You know, maybe I continue the conversation around AI, obviously both a hot topic for your users and adding a lot of value. You know, investors have really been kind of wondering, you know, how can we see the upside beyond kind of like the strengthening of the platform, like directly in revenue? I think there's kind of two sides to this question. One is you're showing kind of the amazing use cases of plugging the MCP in, delivering a tremendous amount of value. It's not as clear to me, you know, how you might get directly paid or monetize that. You know, I think the other piece that's been really kind of a, an investment, maybe you'd talk about it, which is, you know, on the, on the credits that you provide, you're not really enforcing, you know, people having to pay for those. I think that's like, "Hey, we wanna get people, like, to a certain level. We want the flywheel to get working before we wanna crank that down." As you think about those two things, you're clearly adding value. You know, what's the line of sight for you to participate in some of that, you know, financially, I guess? Look, we obviously struggle to answer this question despite continuing to answer it, so I'll try another attempt at doing it. Teamwork Collection strength is due to AI. Like, it's a huge driver of that, right? It's a very obvious customer path to upgrade to Teamwork Collection to get far more AI Rovo credits. It's not the only reason you'd upgrade to the Teamwork Collection, but we're trying to make sure for customers that they see it as a simplified package. There is some amount of that cloud growth that we are seeing and increased revenue from Teamwork Collection in the AI story. How much? It's hard to parse out 'cause there's a number of reasons why we've moved to Teamwork Collection, but it's always in the top handful of reasons why. Also, as we've talked about many times, the upgrades to the cloud, increasingly AI is listed as one of the top two reasons that customers will move, right? The economics of customers moving to cloud for us is extremely good over that multi-year period. Both of those are actually leading to a positive economic outcome that's a result of our AI investments. We obviously have an AI Rovo credit story in the longer term. That requires that usage. That requires that flywheel to be moving. We're seeing it moving, which is great. We wanna be very careful to grow it, very patient looking at that long-term story and making sure that it comes through. There is a story there for sure, but we're trying to make sure that that is the case. Again, we'd rather have customers consuming and using and seeing the value of the platform. We will learn about the platform and really early in that journey as an industry, I think everywhere. Lastly, I would say there's a sort of interesting competitive dynamic, right? The things that we're investing in and building and the amount we're investing in R&D in AI, the platform we've built is very, very hard for others to replicate. There will not be 20, 30 SaaS vendors that can do this. There just won't. It's too hard. It's too expensive. It's too difficult. We're determined to be one of those handful of SaaS vendors that can do that, and I believe that's long term a very good position for us to be in to be able to do that. The stuff we're doing in the Teamwork Graph, this is non-trivial, massive consumer scale stuff that very other few other vendors can do. Again, the video I showed of Kun is one of many examples of where the Teamwork Graph can accelerate the customers. We have to continue to tell that story, get that out there, and grow it and scale it, but we feel really good about where we sit at the moment. Mike touched on this a little bit earlier, but just maybe to put a finer point on it, you know, TWC is the best AI monetization vehicle right now. A big part of that is because of the credits that we're giving, 10x credits relative to the standalone SKUs. I think what we hear from customers is twofold. One is they want the access. Two, they also have within their enterprises, and I'm sure you guys see this within your organizations as well, there's lumpy usage, right? You've got some hyper users, others that are provisioned but not using it. They're able to load balance those credits across their organization as they're getting better and better at driving value from that. It's giving them that access, it's giving them that predictability from an invoicing perspective. Mike shared a little bit earlier all the different commercial models that we will adapt to as our customers are evolving as well. I think we're seeing that. One of the things I don't want to get lost here is, you know, when we showed the video a little bit earlier there, I'm not sure if we ended up showing the stat, but in the keynote, we showed a stat that talked about how, you know, we were getting 44% of better quality in terms of output, and 48% cheaper rate, right? You're using 48% fewer tokens to get to that same or better outcome. That's a conversation with your CIO. That's a conversation with your CFO that's going to resonate. I think both things are true. We're seeing that show up today in our monetization, and we're still building the platform and the flywheel to continue to compound on that. Maybe one thing to add from a go-to-market perspective, obviously, our approach is quite different from others in the market in the sense that we've given our customers access to Rovo, and as both of them have said, get more access via TWC in terms of credits. That approach removes friction that might exist if we were positioning this in terms of how much it costs. It's a way easier way to position it to our customers, first of all. Secondly, this is, as Mike had said, a more patient approach that we're taking. However, this is an approach that is historically this is something that Atlassian has done before. However, the one difference compared to previously is we now are making considerable investments into our customer success organization in terms of helping those customers adopt even more so. Not only into our own customer success organization, but also into the partners as well to help them stand up similar adoption organizations. A combination of all of those is where we are now seeing an increase in terms of our monthly active users. Let's go to Jason in the front. Thanks. That's actually a good segue to my question. The side by side of the Claude example, and James, your comment about utilizing tokens more efficiently or cheaper. I think a lot of companies right now are still pretty early in maybe their token utilization. You see these memes online of, you know, people making fun of how many tokens they're trying to deploy, right? If the value prop for players like Atlassian is to utilize tokens more efficiently, but the user is not quite asking that question yet, what needs to happen to get there, or how long might it take for the tech community to rationalize their token usage more? Yeah. I'm not sure most CFOs really like the token maxing meme, to be honest. I think they are starting to see and pay bills that this magical revenue pile is not coming from nowhere. I do think that story resonates. I can give you multiple customer quotes already today that have been sent around some of the internal rooms and groups I'm on where customers are loving it, they're talking about it. They're already saying, "Hey, I'm installing Teamwork Graph!" We already got someone at work that did it, like, in this morning. These are large scale, big customers. I think that is a relevant story on the cost side and token usage. I would not dismiss the other two, right? We've done a ton of work making sure that it is both higher quality and faster. The example we showed finished a minute and change earlier. That's one thing. Imagine that when you're running suddenly more and more parallel agents, you're doing more and more things, and your workloads get more and more complex. The more complex this gets, the more saving you get. For these smaller trivial examples, the maths is way less good, actually. That's a good thing for us. If we believe the trend is towards more complexity, more complexity of agent use and agent work, we're heading into a better and better world as that happens. I believe that's absolutely the world that we're gonna head into. Even if we just sit down with a customer and explain, we can make every AI agent you use have a better quality answer due to the work we've done in your Teamwork Graph, the search that runs across it. Again, those answers come out of a search engine, kind of a search, a search and graph combination like answer. It goes to reason that the better answers we can give, the better information we give to any AI application, whether that's Figma or Claude Code, it doesn't matter, anything in between. The more you put into the Teamwork Graph, the better quality answer you will get. Even if you take out the cost story altogether, that's a really compelling story to customers, especially if they already have a huge amount of data in their Teamwork Graph. They're going to connect that's going to write back, that's going to grow. The quality in itself, let alone the speed, people still want this stuff to finish faster. It's a really compelling pitch to customers. I expect that it lands very well. If they're not having a token cost problem today, three months from now, six months from now, 12 months from now, they will probably have that in some point. Ultimately, Jason, you know, we're not in the business of selling tokens, we're in the business of selling value, right? That customer journey that we walked you all through a little bit earlier in those slides where customers start with a couple of SKUs, they realize the value, they go to collections, then they go to multiple collections and ultimately buy into the platform, and that reads and writes right back to that Teamwork Graph. There's that compounding value ultimately. If you're a customer and you're getting 40% better outcomes at 40% cheaper prices, you've got a competitive edge. I think that's partly what we're seeing right now in terms of, you know, the consolidation and the conversations that we're seeing with some of our customers. Maybe Jason, just to round it out, I would only add that, like it's top of mind for, from the customers that I speak with every day in terms of the usage, not only the usage, but the return on investment. When we look at DX, which obviously is operating in this space, 75% of the transactions that they are doing are associated with AI and the return on investment in terms of AI or agents specifically. It clearly is top of mind for our customers. Why don't we go to one online that I thought was good, from Thomas Blakey. It might be good for Brian. Customer examples given were excellent in terms of continued growth focused on cloud and the power of one platform. Noting the consistent growth in millions of dollars, sometimes $5 million or more in a year or so time is meaningful. Could management talk to penetration rate of these accounts at these spending levels, and maybe cite where this spending is coming from, i.e., is it consolidating from other vendors or other IT spending pools? Brian, I know you and I talked about this the other day. Obviously we have considerable customers still that we need to move from DC to cloud. We're continuing to make progress there. We have also established a considerable specialized sales organization now. That specialized sales organization allows us to focus more in terms of selling into specific buyers into our customers. We historically have landed in IT, so tech, and from tech, we will expand into new buyers. When we now look to sell to new buyers within the organization, we have to position ourselves differently to those particular personas. Therefore, we are selling into, if it's marketing, if it's into HR, et cetera, we have persona-based selling that we have in place. We are seeing making progress there. We're from a collection perspective, obviously, Service Collection is where we are making considerable progress. We have, as you saw in our Q3 results, we have made considerable progress in Service Collection. Also we have seen a pickup in terms of our win rate against ServiceNow specifically, and also some replacements as well in terms of our competitors, which is what we like to see. We're hopefully expecting that that's gonna continue in that vein. Why don't we do Rob Oliver right here? Great. Thanks. Rob Oliver with Baird. Thanks, guys. Mike, I was struck in the two charts you put up, the financial services company and the auto manufacturer. Jira Product Discovery was kinda right at the crux of the hockey stick there. Obviously that's a very important part of the Teamwork Collection. Would love to hear how you guys think about that as a driver. When I think about some of the most durable companies in software, they're those that are, you know, around system of record, system of truth, design. You know, thinking about that JPD opportunity for you guys as a component of the Teamwork Collection, how important is that as a land factor? There's no doubt the newly grown Product Collection, so we have the Feedback app that got launched today. We have Jira Product Discovery and that Product Collection. It is a few things. Firstly, it's an excellent cross-sell opportunity to a Teamwork Collection customer or a classical Jira or Confluence customer because it is a very different way of looking at the data that you have and a very logical part of the workflow. There's no doubt it is a good cross-sell opportunity. I would say that's more of a classical Atlassian business, right? It's still quite small. It's growing quite fast. We're making sure that the product is just freaking awesome before we start scaling it. I think we've only just added a premium edition three, six months ago. Yeah. Not long. We don't yet have an enterprise edition of Jira Product Discovery. Again, wanna make sure that it has that momentum, the seat growth, people are loving it first, and then we can start working out what we need in the premium enterprise that makes sense as the value grows. Classical cross-sell opportunity for us. Great team, doing really well. Feedback is a really interesting addition, I think, because it moves us into some other spaces we have not classically been in beforehand. At the same time, it leverages our strengths in AI because I do think the volume of feedback is gonna go up. The product manager's job to take all of that feedback and distill it down and turn it into ideas that become the pipeline for engineering, if you wanna think about it that way. You've gotta first start with a set of insights and sort of scraps of text and other things from customers. You distill that into a set of ideas. Those ideas become roadmap items, and roadmap items get built by engineering. Engineering is, as Sherif said on stage, I think ceasing to be the bottleneck in that process. That creates other economic opportunities when you go outside of that. Now, a product manager's job isn't gonna be as classical. It's gonna have a lot of AI and automation and other things associated with it, which is exactly what we're trying to do in the Feedback app, is show some of this at a large scale in a category where we don't have much footprint. I think it's all upside for us, which is going really well. I think it is also a completion point because more and more marketers, other roles in a business are gonna start looking at that feedback and working it out, and it somewhat completes a cycle. You saw Customer Service Management as one of the ingestion points for feedback. Think about customer service as the thing you do at the very end of a chain. You've built the thing, you've marketed it, you've sold it to someone's used it, and then they have some challenge or feedback that comes from customer service. Inevitably, it's a problem that they also add some feedback into, and it kind of runs around a cycle. It's us continuing to show that we have a system that can take those customer requests with a really deep AI and Teamwork Graph core. That's a really interesting point for us, as well as, a new point of data connectivity to some of those other systems we've shown, whether it's Pendo or parts of Salesforce, other sources of Zendesk, whoever of access or partners of ours to say, "Look, if you've got the connector to vendor X installed, now look what the Feedback app can give you. Look what the Product Collection can give you on top of the existing connector that you already have installed in your Teamwork Graph," right? You don't need more data. You don't need more connectors. You have that already. It creates a higher multiple, multiplicative AI, a sort of ROI opportunity for that customer, and again, makes our graph more central to that customer. Super bullish on that area of the business. I hope in multiple years' time, we're talking about the Product Collection heading in the same direction as the Service Collection has. How about DJ right here in the front? Hey, thank you, guys. DJ Hynes from Canaccord. Two quick questions. I'll ask them concurrently. I think they're straightforward. Mike, you talked about we're now at the point where you can start to moderate R&D spend, and sounds like Brian's team will be a beneficiary of that. What does that look like in practical terms and kind of over what timeframe are you talking about? The second question, some really interesting data and context connections to the Teamwork Graph today, right? Code, assets, which is apparently your favorite, skills. Are there any other major areas of data that still need to be connected to the Graph that will kinda improve AI outcomes? Two very different questions there. Look, the moderation of R&D spending is gonna continue to happen over time. You've seen some of it already, and it will continue to happen over time. I think it's probably the best answer that we can give. I think what we're trying to explain is the why behind it, right? I really like people to understand things from first principles. We need to build this enterprise platform. We need to build the AI infrastructure. We think those are all strategic long-term pieces for us. There are only so many enterprise controls and compliance. There is a limited number of those eventually that you get to, and we've built them into our platform. Again, our FedRAMP, our Isolated Cloud, commercial cloud all run on the same code base, which is quite unusual. We don't want any engineer to be slowed down, and we continue to keep rolling those things out. Same as our multi-cloud offering, our data residency. There is an upfront cost to pay for all of those things. It needs to be maintained and continue to build and evolve and all those things. That is a different price over time than the price we've paid to get here, I guess, in terms of the smart teams. It also frees up engineering resources to be able to put towards some of those other things like the Teamwork Graph. You'll see that coming through over time. Secondly, on the graph, I don't know there's any major categories that we're looking at. Code has been a long-term investment. It's technically very challenging both to index large volumes of code. Again, we, as we said, we're north of 1.5 billion lines, 11 million files. It's a non-trivial sized code index when you're looking at it semantically and breaking it all down into all the component parts, all different languages, everything else. That is a huge piece, but also because code underlies a lot of the other things that we wanna do. Secondly, the people aspect was a big investment, right? The assets in the graph we've had for a long time, that's really taken the asset graph we already have, continuing to scale it and connecting it into the Teamwork Graph, right? It's really connecting two graphs and the same graph language running across both of them and all sorts of other things like that at the moment. That's been a sort of longer term thing. People has been a new investment, right, as we continue to grow really strongly in the HR function broadly. We have the Talent app now. HRSD continues to be a big aspect. People, Chief People Officers increasingly responsible for culture, so things like Loom and other things become a big part of how they're communicating. Hubs and Confluence are big for HR usages. Again, we partner with all the major HRIS vendors, and we have a very symbiotic relationship with them, which is really helpful. I think that's a big category, right? If we look at what we need to answer questions fulsomely and well, like better than anybody else in the world can answer said questions, it's about the people, the code, and the physical objects connected to the sort of knowledge or the classical knowledge objects that I guess you have. We feel pretty comfortable where we sit actually at the moment in terms of the major categories of things. Adam Tindle right here. Okay. Thank you. Adam Tindle from Raymond James. Really appreciate the presentation today. James, just wanted to ask, for you, Mike mentioned in a helpful comment on expecting Data Center to decline next year. Wonder if you might put any parameters on the magnitude of that decline and the potential knock-on impact to be mindful of on margin and cash flow, given the upfront rev rec. The flip side of that question would be, you know, as we've talked to partners here today, customers are not looking to churn. There's no real viable alternative to Atlassian's products here. You know, if Data Center is going to be in decline, I wonder what that might mean for cloud growth into next year. Yeah, I really think about this as sort of timing, right? Taking a step back, you know, Mike shared a little bit earlier, cloud remains really healthy for us. We're seeing retention rates as high as we ever had, in fact, actually outperforming expectations in Q3. So I think you hit on all the points there. You know, as it relates to cloud or sorry, data center growth being negative next year, again, this is more in that spirit of clarity. I think a lot of folks were sort of asking for that. We're obviously not giving out FY 2027 guidance quite yet. We'll be more clear about that in August earnings, but obviously need to still see Q4 play out as well. Again, like the dynamics that Mike described a little bit earlier I think was worth reinforcing, right? What we're seeing in terms of strength in cloud, strength in retention on the data center side, and then some of that customer behavior, right? As end of life is nearing, they're making decisions about what that more complex migration is going to look like, being able to pull up some of those commitments. Again, these are good things. These are customers that are committing to Atlassian, whether it's through data center or through cloud. We'll see that play out over time. We'll have a little bit more guidance, I think, out in the August timeframe for that. Koji. Koji Ikeda from Bank of America. Thanks for doing this, guys. Mike, during your presentation, I thought you had a pretty cool slide on your AI advantage, with enterprise as hard, Teamwork Graph, and Jira as the orchestration layer as the three advantages. If we fast-forward three years from now, what do you think will be, out of those three, the most important advantage for Atlassian? You know, I ask the question because I think that inherently implies that might be the hardest to defend. I mean, I suspect all three of those are important advantages. I think it's always important to remember the world is an incredibly dynamic place. Right now, our advantage is in AI. We wanna make sure to magnify those advantages with customers in terms of getting that adoption. The flip side maybe of the question asked earlier around we'd much rather get that AI adoption right now while we have an enterprise advantage because it makes it harder for other people to invest in building it, and we know it's very hard and very difficult at the moment, right? It's a dynamic world. You might argue some of those advantages will atrophy over time, and we will find new ones. It's about us continuing to evolve. I don't know that I could say that any of them are more or less important. We love our Jira franchise. It's an amazing franchise. It continues to grow really strongly, and we've invested a lot to make sure that it is the case. At the same time, in an agentic world, what has been done, who is doing what to which piece of any workflow needs to be tracked, managed, and understood. I think if you wanna think about it generically, I believe you'll have way more actors doing that, right? The idea that a hundred-person company might have thousands of agents running around, that creates a lot more management overhead and understanding overhead, which I think is really good for orchestration platforms the like of Jira that already have workflow and automation and all sorts of other capabilities to handle all manner of business workflows and processes. I talked on a podcast and someone sort of, I think one of the hosts explained to me backwards, or I forget which way it went, but sort of talking all about system of record and system of record, and that always sounds to me like a very static database-driven type of thing when you're a system of record. We were sort of maybe not even accused or pointed to being, I forget how it happened, a system of process. I'm like, that's a great description of what it is that we actually do, right? These dynamic business processes you heard from both Cisco, CANAL+, you heard from customers today. We talked about Mercedes-Benz yesterday on stage. We showed another handful, two, three customer examples between Brian and I that aren't those other three customers. They're all running processes through Atlassian, right? Those processes that they have 10 years of data center and server history that move to the cloud, they only grow the number of processes they run through us. Agents are gonna yield many more processes and much more of that difficulty. I think Jira is gonna continue to have a really strong place, especially if we can give all those tools to allow people to manage and understand that, which we keep trying to do. There's no doubt that Teamwork Graph has amazing potential, right? As customers use it, as it grows. We're seeing it grow very rapidly, create some fascinating and interesting engineering challenges for our team to grow it at the scale that it's growing. Again, things that are hard to do and hard to scale and hard to deliver on are great because it is very hard for other people to do that. We have a distinct customer and data advantage already. Keith Bachman. Hi, good afternoon. Thanks for doing this. I'll ask two concurrent questions in the interest of time. Mike, just to pick up on that thread, when I walk the show floor, it just seems like Teamwork Graph is one of the key- Competitive advantages that Atlassian could have over multiple years. The inverse of that, though, what is the risk you see from a competitive dynamics? In other words, if somebody, one of your Atlassian customers, is not deploying Teamwork Graph, what else might they be using? Might they just be using a standalone Claude or something along those lines, which you've shown and demonstrated is not as efficient. Just curious on the competitive dynamics that you see on Teamwork Graph. In other words, what somebody might choose to use instead. Just to ask a second question, Brian, you indicated you had 600, or excuse me, 400 sales reps or quota-carrying reps. I'm not sure how you refer to them. It's still very sub-subscale, right, on almost every respects, and your 10% of your revenues are Fortune 500, so and you're moving to collections and these higher value add sales. How should we think about the ramp of sales as we look at 2027 when you're trying to, I think, get more revenue, greater revenue from existing customers? I guess I'll take the first one. The Teamwork Graph competitive question is an interesting one, actually. I think, look, firstly, customers don't have to buy the Teamwork Graph, they get the Teamwork Graph. We've made it a core part of the platform. There's a reason that we don't sort of separately charge for it or sell it or any of this sort of stuff, which always makes it harder from an investor point of view to communicate that. You'd love to see a separate line item that's going up into the ride, and it's looking really, really great. From a long-term strategic point of view, I don't think that's the right thing for us to do. What we want is anybody using Jira, anybody using Confluence, anybody using Loom, anybody using Bitbucket to have the Teamwork Graph. The more of those things they're using, the better their graph gets. The compounding exponential effects, right? Metcalfe's Law of context graphs. I'm not sure if they can kind of take two different eras of technology and put them together there. That is a really powerful thing because it means that the next collection they get, the next app they add, their graph gets more powerful. The next connector they add, it gets more powerful. We have a lot of connectors already because we've had various graphs. The reason we built the graph eight years ago was nothing to do with AI. It didn't really exist. It was machine learning. It was a very different world. It's to do with us connecting to other customers' applications and them wanting to share data and us continually managing the connectivity of that data. In such, it doesn't really have a competitor in and of itself, nor do you need to buy it as a customer. What we're trying to make sure that customers understand is the more Atlassian products they use, the more connectivity, the more their data grows, the more processes and workflows they run, that graph is just gonna keep growing in value. Now, you don't need to connect only the graph to Claude Code in that example. You can connect the graph and other something else. Great. It's up to Claude Code to determine where it's gonna get the better answer. In the long term, it's a really interesting question whether the agents themselves will learn that we are a great place to get great answers. I suspect they will, and that's a great thing for us. We're just gonna make sure that that is the best graph that you can get of the type of data that we want to serve. We have a lot of partners that do different types of data, and that's great. If you go look at a Databricks or a Snowflake or someone doing sort of relational numerical data at massive scale, that's not what we're trying to do in the Teamwork Graph. You're gonna have multiple of these types of knowledge graphs, data graphs, whatever you call them. Most of your agents are gonna have a number of places they can go and get information to help them. We wanna make sure that we're building the best for our use cases, I guess, is our competitive vector and make sure the customers understand, and that we can bring all of that past history into the graph. Today, you can, I've had two customers do it already, download the CLI and be like, "Holy crap, look at all this stuff I have." I'm like, "That's the exact reaction that I want them to have." Then I'm saying, "Great, just go plug that into Claude Code and watch it get better." That will, I suspect, lead to their graph continuing to grow and them getting more and more value from us and them seeing us as a more valuable partner to them, which is a, an amazing position for us to be in over the next few years. We can continue to invest in the R&D to make that both scale and the smarts. As you said, we have 400 quota-carrying reps, and we certainly punch above our weight when you look at the revenue. Over the course of this year, we have increased our reps, and the way we look at it is we prioritize both from a geographical perspective, and also from a account to a sales rep perspective to look at where will be the highest return on our investment. As we look at FY 2027, as Mike had said, there will be additional investments made into my team, and we will continue that approach of ensuring where we will make those investments from a return on investment to ensure that we're gonna maximize the return that we will be getting for the company. That includes from a geographical perspective, entering into new markets where we do not have people. Just earlier this year, we put our first reps on the ground in India, where we did not have any reps before. In addition to that, we're also going to be leveraging the ecosystem. There will be certain parts of the world where we identify that we have an opportunity, but we won't be going in there yet. We've already leaned on our partners to ask them to come into those markets with us where they are doing that, and they will serve as an extension of our sales force, and we will continue to make investments and look at it prudently as we move forward. That's actually all the time that we have today for questions. Really appreciate everyone for coming out, learning more from us, talking to our customers, learning about our announcements. For those that tuned in via webcast, thank you for joining. Thank you all. Thank you.