Hi, everyone. Thanks so much for joining us today. I'm here with Tiffany To from Atlassian, Gillian Ostalovich from Goldman. We're really, really excited to have Tiffany here with us as SVP of Enterprise and Platform for Atlassian. Tiffany, you have been with Atlassian for almost five years now, working across the company's different solutions. Can you tell us more about the roles you have held and the evolution of Atlassian over this period?
Sure. Thanks so much for having me. So I joined Atlassian, like you said, about five years ago, to head up the product on the Agile and DevOps side. So I headed up Jira and Bitbucket core cloud products. But as I started meeting with customers, and asked them about what they wanted from our products, one of the really big recurring themes was that they wanted us to help them be better tech companies. So it wasn't just, "Hey, we buy your products, and they help our dev teams manage the software development process." It was, "How do we know how the work is flowing? How do we know that we're doing a good job? How do we know we can be a...
Like, how do we be a better tech company?" So a lot of that pointed me towards investing in more solutions around the platform, and so after a couple of years managing the products, I transitioned over to head up the platform team. And that kind of aligns with how Atlassian has also evolved their Enterprise strategy. So I think most folks are aware that we made a very strong strategic decision to move our customers to cloud. We announced, you know, the end of life of our Server products, which is where most of our customers were. And over the last five years, customers have been going through this journey of working with us to figure out what's the right timing for them to migrate to cloud.
And so building some of these new use cases that I talked to those customers with five years ago, those are now a big part of the business case for them moving to cloud. And then we'll get into it, but AI becomes, like, a whole another accelerant that is exciting to talk about.
Yeah, we will definitely be talking about Atlassian Intelligence and everything revolving around that. But even before we get into all that, collaboration has always been a really key component of the Atlassian platform, and across a variety of different end markets. How would you characterize that key differentiation that it allows you to do and approach that it allows, like, what can continue Atlassian's strong market position?
Yeah. I think what's interesting is, a lot of times when people think of Atlassian, they think of Jira, and they think of us as a dev tool. But if you look at who's using Jira, only half the users are developers. The other half are folks that are product managers, program managers, marketers, all of the other functions around building and developing software. And so when you talk about collaboration, I think one of the really interesting things when you think about technology and development is that, it's not just the developers, right? Like, if you wanna be an innovative tech company, you actually have to harness the value of the whole company, all of these other functions, and Atlassian has always embraced that. And that's why we...
You know, after Jira, we built Confluence, and you've seen us make a number of both new things we've built, but also things we've purchased, things like Loom, right? And that's because we truly believe that to be the best technology-driven company, you have to enable collaboration between the technology and the business teams. You actually have to connect those groups together. And so to differentiate, we want to both have the best tools for that range of different personas, but we also wanna invest in a platform that connects the data across those tools. And so one of the big investment areas that we built in platform is something called a Teamwork Graph. A graph is not a new concept. Don't worry, I won't go into, like, a whole engineering description, although that's my background.
But think of it as, there's been this huge era of, "Hey, you have tons of data, try to get value out of that data," right? The whole big data movement. And when you talk to customers and ask them, "Did you get value out of that big data movement?" Very few customers have. Why? Primarily because to take that data and actually organize it, clean it, enrich it, and make it usable is so expensive, that very few industries other than, I think, like, retail, manufacturing, there's a few industries that have gotten real value out of big data. Now, why do I talk about that? Because when it comes to collaboration, one of the hardest things to do is to provide context between people, right? Especially if you're on a different team or you're in a different function.
And so in Atlassian's platform, the Teamwork Graph is actually where we manage relationships between the data that comes from our products as well as third-party products. And we do that in a very opinionated way, and we anchor on four key concepts. So we believe for good teamwork in a tech-driven company, you have to really understand who's doing the work, the teams, right? The goals, so what are the business goals the company is aligned to? How do you map those teams to the goals? The work itself, so all the projects that tie to those goals. And then finally, knowledge, all the different ways that you may store data in your organization and how that maps back to the project. Why is that important now? You know, we couldn't have predicted the GenAI, you know, huge wave.
But when you think about how to provide context, initially, a lot of that investment was to give context to the analytics for our users, to be able to ask questions like, what I said at the very beginning, where customers were like: "Hey, how are my teams doing? Which teams are bottlenecked? Which teams need help?" That Teamwork Graph helps give the context to answer those questions. But now with AI, the Teamwork Graph ends up being a really key differentiator for how we evolve, those models, those AI models, because the AI models can layer on top and tap into that Teamwork Graph... and no one else in the industry has that. You know, Microsoft is well known for their graph, but it's a much more generalized graph, whereas ours is very focused on those teamwork objects. Yeah.
What does exactly the Teamwork Graph enable or unlock in terms of capabilities within Atlassian platform?
Yeah, the way that it shows up is, when a user logs in, it knows the context of who that person is, what team they're on, what projects they've been working on. So it's gonna proactively bring them suggestions on what work they should pick up, what's happening in other teams that they should be aware of because there's dependencies between their projects, right? It's gonna pick out of the sea of knowledge across Confluence or SharePoint or whatever tools that you're using, relevant knowledge that would make sense for that project. So think of it as like a way to have almost a helping hand that's very customized to each user. And that shows up in different ways across the different products.
But especially with the AI features, you really start to see that difference because it picks up on the specific ways that that company does their particular technology development. So I'll give you maybe a more concrete example. When you apply the AI features, the generalized models that people are using, obviously, it's gonna look at all data and make recommendations. But with the Teamwork Graph, we have an awareness of the way that that particular tech company does their work. So we know the way they write PRDs, right? Their product requirement docs. We know their release process. We know what security checks they wanna do before they can release software. All of that data then gets fed into the AI queries that we put into Atlassian Intelligence.
What that means is, when you build, for example, an AI agent, a Rovo agent in our portfolio, on top of the Teamwork Graph, it's gonna provide much more customized guidance that fits for that organization.
Yeah.
Yeah.
I definitely wanna touch on Rovo-
Yeah, yeah.
in just a second.
I'm jumping ahead.
Maybe a little bit, but it's, it's great context, and I think something that you said, I wanted to ask you a little bit about in terms of Atlassian Intelligence, and if you're seeing greater usage of that between applications within Atlassian ecosystem or even third party, or within applications in unlocking the functionality of, let's just say, a Jira or a Confluence. How does that look like today?
Yeah. I think we're seeing everything right now, which isn't surprising. Like, all the Enterprise customers I meet with, they're like: "Okay, we've gotta figure out our AI strategy." They're often designating a council that is in charge of determining how to evaluate and adopt all these different AI technologies from different vendors. I think the great thing for Atlassian is, we're usually on that top five list for them because we're the set of tools that is a system of record for some of their most valuable employees, their development teams, and all of those teams supporting those groups. And so the AI features that we've built, they're in kinda two arenas. One set of the GenAI features are kind of integrated across all of our products.
So think of it as any function that you're already doing in Jira and Confluence, we turbocharge those things, right? So it's like you could read the page, or you could read the summary much faster, right? You could write the page from scratch, or you could have it pre-populate based on other pages it's seen, your personal preferences, et cetera. You could fill out the Jira ticket, or you could have the agent fill out the Jira ticket. So a lot of those functions are happening, and we're making those available to customers that are on Premium and Enterprise editions of our products, and we're seeing really huge growth of that. So about a three X growth in now, quarter over quarter, we're seeing. We're feeding that growth, obviously, 'cause we're continuously releasing more features.
So I think we have a couple dozen features kind of in that arena of deeply integrated into the product. And then there's a second category, which is tied specifically to Rovo. And so there, that Rovo layer is both search, built on top of that Teamwork Graph that I talked about, but it's also a development platform. So part of what we're seeing with customers is that they want our help in building the right agent for their organization. So we have a lot of great data from, you know, our three hundred thousand customers and the research we do, so we're providing a lot of out-of-the-box agents. So think of it as your product manager teammate, your developer teammate, your program manager teammate. They're very persona-oriented. So we're using data from our customers generically to kinda develop those functions.
But then, since we're building it on top of our Forge developer platform, what becomes really exciting is customers or our partners can then take that agent and extend it to their organization, right? It's taking that rich context that I talked about, but then customers can start to make it work the way that they want in their organization. And that, that's part of, I think, where the real productivity is gonna get unlocked over the next year.
Yeah, and it's actually really interesting. I think Atlassian was one of the first companies that we really look at and at scale in the industry that really talked about agents and through Rovo. What led you into that direction? And, you know, how fast have you worked to kinda get there to announce that at Atlassian '24? What are some initial proof points and applications of that beyond the typical Jira customer-
Yeah
... or Jira use cases?
Yeah, it's been a really fast learning loop. I think, like everyone else, it's been all hands on deck, right? To try and, like, capture this learning as fast as possible and experiment with our customers. I think initially our hypothesis was, customers would want these agents, like, pretty much out of the box, and they would use them. But as we first started experimenting, we realized that the true value was actually that last mile customization... because no one wants a generic developer or generic program manager. That's like hiring a brand-new employee that comes in, may have functional experience and background, but doesn't know anything about your company and the way you work, right?
And so what we realized was that last mile becomes quite pivotal, which is: how do you codify the way your company works, whether those are things that are, you know, rules and regulations or softer things, like cultural practices? So what we find is, you know, back to the beginning, when customers were asking me, "How do I be a really good, the best technology company I can be?" Some of that is in the tech and the tools, but some of that is in cultural practices. You know, are you running TechO ps practices, right? Do you have the right rituals? Are you doing retros, right? These are actually less about the tools and more about how the way the teams work. And so for some customers, they're hiring coaches, like humans, to come in and teach these things.
But you can imagine now, with the Rovo agent, you can actually start to take some of those practices that you want adopted and have that coaching happening through the agent as well. So I think this learning has been, to your question, quite recent, but it's been a lot of fun because, customers are giving us that fast feedback loop, and the Marketplace partners as well. As they're figuring out, you know, what is their role in this ecosystem, they're starting to do some pretty interesting customization, where they're taking the agents, and they're customizing them by vertical. So you can imagine, like, okay, there's a generalized developer or product manager, and then there's custom to that organization. But there's also really interesting things that are done by... You know, in an automotive organization versus financial services versus a hospital.
Some of these partners that work with quite a few customers in these verticals are also providing that additional domain context on top of the agents, so lots to come on this front.
Yeah, no, I'm sure we'll, we'll still be hearing a lot from you in that sense. But also, and when you think about how it's gonna look in the future, and you think about the workflows that are-
... existing right now, or the way that users engage with Atlassian, how do you see these agents kind of either complementing or automating some of this? And is it... Will you have a product for one and versus the other? Like, you know, I think we hear a lot about chatbots versus agents. And how does that- how do you see that evolving within Atlassian portfolio?
Yeah. No, that's a good question. I can't quite predict the future, but I will say that I think my view of it is that our customers are thinking much more holistically about their System of Work, right? And when I say the System of Work, it's how they think about the operating system that runs a technology-driven company, right? So they're thinking about: what are those key workflows, right? What are the key teams in these workflows? But also, who are the key strategic vendors that supply this System of Work, right? They don't want a hundred. They want a small set of strategic vendors that take ownership and integrate that System of Work together, because I don't think they're gonna have one vendor that does everything.
and to give you a sense of who's at that table, like, clearly, Microsoft, you know, has the horizontal collaboration tools. On the IT side, you know, ServiceNow is there as well. But when you look at the core development teams and the system of record for those dev teams, it's Atlassian, right? And so I think when you ask me, like, "What does that world start to look like?" I think it's these Enterprises having these multiple strategic vendors. It's them having a System of Work that organizes several of these core systems of record into that System of Work, and then they're gonna be writing their own AI agents that help with different parts of those workflows.
Mm-hmm.
And I think for an Atlassian, it's gonna be very much, the connecting of the technology and the business teams together. And so that's both a vertical up and down of, "Hey, what are the goals of the company," right? "Which projects are we betting on that ladder up to those goals?" and then, "What teams are working on those projects so we can track that work?" And then, you know, Microsoft tools are there horizontally, helping with, obviously, collaboration. We integrate really well with those Microsoft tools and bring that into our Teamwork Graph. And then, as you get into the delivery and then the servicing, then we integrate into, you know, a ServiceNow as well.
So I think it's gonna be a mix of multi-vendor and multi AI strategy. If, if that's what your question was?
Yeah, yeah.
Right, definitely does-
Mm-hmm
... and it kind of leads a little bit into the next question in terms of thinking about a lot of... When you talk about ServiceNow, or you talk about Microsoft-
Mm-hmm
... you often think Enterprise, right? And I think that there's been a lot of changes in how Atlassian's going to market with the Enterprise, but particularly, a lot of the functionality that we're just talking about is only available in cloud, in particular SKUs that you mentioned earlier.
How are you balancing these investments, and the needs of these companies that are really, really eager to adopt AI, with also the desire to move more of them to the cloud?
Mm-hmm. Yeah, it's been interesting to see those conversations evolve over the last five years. When I joined Atlassian five years ago, we had just announced that, you know, "Hey, everyone needs to move to cloud. We're building the cloud platform for you," and I think customers at that time were like: "Okay, yep, we get it, and we'll get to it when it's a priority for us," and Atlassian, you've got to unblock all these other features, right? There were a lot of things they needed us to address, from a scale, performance, data residency, bring your own key. There's, like, a long list of reasons why customers often are more comfortable keeping their deployments behind the firewall.
But as they saw us continue to execute on that roadmap and unblock, and also increasingly add new value in the cloud on the platform, that conversation has shifted to, "Okay, we'd like to get to cloud. We wanna start. Help us build those business cases to get there," right? Because for a lot of our largest customers, who have hundreds of thousands of seats, like Bosch has six hundred thousand they need to move, it becomes a multi-year journey. And so I think the evolution for Atlassian is that it's not a, you know, one-time type of thing. It's actually having a much deeper long-term partnership with these customers, but that is opening up, a much richer set of conversation. Like what I was just explaining earlier about the System of Work, five years ago, we wouldn't be having that kind of conversation with these customers.
It was much more, "Yep, you guys are a vendor. You guys give us Jira and Confluence. That's great. The dev teams love it." Now it's, "Okay, we've got to figure out how to make our tech company, if we're a tech-driven company, more effective. We've got to figure out our AI strategy. We have, like, two hundred SaaS tools. We've got to rationalize those tools." They have a lot of these much more strategic initiatives that they wanna take on.
So that migration conversation has really transformed into, "Hey, how do we help you be a better tech company? How do we help build that multi-year business justification to move to cloud?" And it ends up being a combination of things. It ends up being, both near term, consolidate some of your apps. As they inventory, they look at, "Wait, I have five project management tools. I don't need that," right? That ends up helping make the business case for the initial migration, and then it becomes: How do I deliver new levels of productivity with the analytics and AI and the other use cases that you guys are building in cloud? So I think of it as us learning to be a better partner to our Enterprises. I think that's been the big shift the last few years.
Yeah, and when we think about that, right? I think you talked about multi-years, and you talked about a 600,000 deployment, right?
Yeah.
So that's, I'm sure, also across a variety of different applications.
Yeah.
Maybe mostly Jira, but maybe not only Jira, right?
Yeah.
Which applications are first moving to cloud, or which applications or maybe departments, I don't know how you might break it out or classify it, should we be thinking about maybe moving to cloud like, over time? Basically said otherwise, right? Like, in other words, how do we balance the complexity of some of the Jira and Confluence with the usage of those, and likely, like, the need for those to happen sooner rather than later?
Yeah. There isn't a one-size-fits-all. Like, I think in the first wave of customers that migrated to cloud, maybe two years ago, it was very much a lift and shift. So they would inventory their full footprint behind the firewall, lots of Jira and Confluence, oftentimes Jira Service Management, and it was lifting all of that and moving it to cloud. But a lot of those customers were smaller, like, you know, probably in the 10,000-seat and below. As we've shifted to the 50, 100, 500, like, the Bosch example, 600,000, then they have to take a much more strategic approach to it. And so there, it goes back to what I was saying earlier, where they kind of have to layer those business cases.
Oftentimes, they're looking at, "Okay, what are the most critical things that we would bring across first?" and then build a business justification to move the next set and the next set. and so oftentimes, what we're seeing is they'll bring the core app, you know, Jira, Confluence, but they're also looking at building business cases to expand into other use cases beyond that. so growing the ITSM side of their use case, bringing more of those business teams in through that consolidation play that I mentioned earlier, right? When they're de-duping, you know, the Monday.com and Asana and bringing that into Jira, that ends up being an expansion of the Jira and Confluence footprint for us.
You're seeing some of those displacements?
We are.
Okay.
We are, yeah. And they're happening not just. I mentioned the business case aspect, and so it may sound like it's only for cost savings, but as I meet with a lot of our Enterprise customers, they're also sharing that it's not always for budgetary reasons. So for customers like Amazon, LinkedIn, Adobe, it's not because they're trying to save money necessarily on the tools.
Yeah.
What they've realized is, in providing, like, full freedom for our end users to pick all of the tools, that that actually hasn't delivered higher productivity. It actually delivers more complexity and confusion, because people are having to copy and paste and move a lot of data back and forth between all of these tools in the same function, and so many of them now have these app rationalization processes, where they're trying to de-dupe those things in Enterprises, so we're helping them come up with not just a more, you know, cost-effective, but a much more kind of end user, better usable experience, I think, in terms of interfacing with all these SaaS tools to collaborate on digital work.
Interesting. So it's not like, how long would it take to move, like, the Jira or the Confluence, to your point?
Mm-hmm.
I'm just trying to think about if net new, sometimes we talk about net new workload-
Yeah
... or net new seats, kind of are joined on cloud, and there's, like, integration with the Data Center solution. Or should we be thinking about it as really, like, are they lifting and shifting? Are they rearchitecting? How long does that take, and what is the involvement of that migration-
Yeah
... of such complex and integrated applications?
I think for the ones that are in that hundred thousand seat or more, it's a three-year process. So they take, you know, anywhere from three to six months to kind of inventory what they have and build a plan with us and a partner. And then they're gonna take another three to six months to migrate probably a good chunk of the initial seats, right? From there, they're often figuring out how to get Marketplace apps and then plan the next set of use cases. So it ends up being kind of multiple phases over those three years. What I will share, though, is also for some of these customers that are in the more regulated industry, there's always gonna be this remaining maybe 10%-15% of seats that they wanna keep on-premise.
And so you may have heard we've started talking about our hybrid approach to this, and I think that's important because it is reflective of what you see in the market from other cloud vendors like Microsoft, where you end up having a private cloud option for that remaining 15%. So when I look at someone like a Bosch with 600,000 seats, at the end of 3 years, they probably won't have 600,000 seats in cloud. They'll probably have the majority, and then they'll have some set that they may keep in private cloud for some of these higher security use cases. So biggest customers, a couple of years to get across. Folks that are in that sub-10,000, they can usually do end-to-end that whole loop in about 6 months. Is that good context? It's-
Yeah.
It's hard 'cause we've got 300,000 customers, so it's a pretty wide range of deployment models.
Yeah, and, and if you have the mix, then we would love that.
Yeah.
But if not, we can also just kind of move to talk about the pricing of cloud. I think that oftentimes you really hear about the cloud Enterprise and Premium SKUs being relatively expensive, even compared to the Data Center. How are you thinking about elevate... How are you tackling this, first of all? And second of all, also, like, elevating the value proposition that they can really get from the cloud solutions versus Data Center?
Mm-hmm. Yeah, it's definitely a big focus for us on the Enterprise business. It really comes down to building that business case and educating customers on the fact that cloud is not the same product, right? Like, we've invested for the last five, six years on building a world-class cloud platform, and so what that means is it's not just offsetting the work of managing the instance, which is the infrastructure layer, but we've invested and made some acquisitions on the data side to build a really robust, intelligent data layer. That's where we've built things like the Teamwork Graph, as well as out-of-the-box analytics. And so when we work with customers, and we say: Look, what tools are you using behind the firewall to track all of the work and do the reporting on the work?
Oftentimes, they're paying for expensive Tableau instances, or if they have a developer productivity initiative, they might be buying third-party products like a Jellyfish. All of those things actually add up, and then when they realize that when they buy our Premium and Enterprise edition, that things like automation and data analytics, the Teamwork Graph, and AI, as we talked about, are built into those editions-
Yeah
... that helps them make that business case, to move to cloud.
Understood. Understood.
Yeah.
What else, from an investment standpoint, do you think are still needed within Atlassian platform, and maybe how are you prioritizing them internally?
Yeah, I'm biased 'cause I head the platform team, so I'm always like, "There's so many things we could add more of." I think we're just getting started on the data layer. Like, I think the uptake on analytics has been immense for customers, and they're asking for more and more features there. The great thing is that we've built it in a very platformized way, and so at this point, we're enabling Marketplace partners to build on top of that. But I think there's a lot of exciting things when it comes to... When you think about AI in the platform and then orchestrating these workflows, I think build or buy, there's some new opportunities around low code that will be really interesting for us to add to the platform.
'Cause if you think about it, it's like we've got a data layer that now gives you all the insights, right? We've got an AI layer that helps you create agents to take action, but then the final piece that is kind of missing there is, yes, the agents could write code, but really what you want are pre-built pieces that you know work in your organization the way you want your app. And so I think having more of those available to teams outside the core development team means that with the addition of AI, you could have the entire company, like, driving that innovation loop, right?
'Cause I think the traditional model is like, "Let's get the insight quickly to the dev team so they can build the thing and get it out the door." And then we have this influx of, okay, there's low-code things that non-devs could do, but there was quite a lot of limitations in terms of, like, how powerful those apps could be. But now married with AI, I feel like we could really, like, complete that loop and get much faster innovation for these companies. So that would be on my wish list.
Yeah, no, that's. I think that that's one way—like, that is probably driving some of a vision that you and the broader Atlassian team have on your strategic and competitive positioning, right?
Mm-hmm.
When you think about your TAM, and specifically across the three different markets that Atlassian plays in, how do you see that evolving, and maybe if any specific areas you see it particularly driving Atlassian in?
Yeah. I think the stat that stuns me all the time, is the fact that we have $14 billion in opportunity in our existing Enterprise customers, and that's just with our current products, right? And so that's not even, like, as the portfolio grows. And that just shows how broadly we've spread the seeds of Jira and Confluence and Jira Service Management. And so when I think about the potential, I see that in our core market of, development, there's still a huge opportunity to grow. Like, we're a standard, but there's lots of teams that have other tools, as we talked about, so I think consolidation will help with that growth. And then I think, the other two really big opportunities are the ITSM space, right? Where as companies use Jira-...
And then they ship a lot of these great products and services, and then have to manage them. There's a very natural workflow that goes into the service management side. So JSM has been growing so rapidly for us, and I think that continues to be a huge growth sector. But the one that I'm the most excited about, I think, is the broader, bringing the business teams and the technology teams together. So I think it's making people aware that Jira is not just for developers, that it's a place marketing can be in, and HR can be in. I think as we ride this wave of consolidation, and then architect this larger System of Work for customers, that that's a huge untapped opportunity for us.
Yeah, and how does that affect the way you're thinking about go-to-market then, right? Atlassian has always been really oriented around individual products and elevating their... those specific capabilities. How do you expect that to evolve over time as you think more about the System of Work that you've outlined with us today?
Yeah, I think it means go-to-market has to evolve with us, right? It means that we're selling... I think you hear it in the narrative that I'm sharing. It's much more of a solution story, right? It's not a transactional, like, "How many more seats of Jira do you want?" It's the, "Hey, what are the business problems that you need solved? Which bottlenecks in your development process can we help you with?" And so there's investment in bringing the right talent in to do that, which we've been doing the last few years. And we've been doing it thoughtfully. I think the biggest investment has to be the R&D side, 'cause I think being Enterprise-ready takes these big resourcing and R&D commitments. And Atlassian's been in a good position to do that because we focus very much on R&D.
So the last five years is getting the platform ready, and then now, as we were saying, with the GenAI trigger, it actually becomes this massive accelerant. So now if we invest in those go-to-market motions that can really bring fruit fast, I think. So we are bringing in the right folks to do the solution sales model, and from my experience, that training can happen very, very quickly, and I think with GenAI as, like, the door opener, we're seeing a lot of great traction in these System of Work conversations. Yeah.
I think it's a great place to end it, and that's all the time we have today.
Yeah.
But thank you so much for coming and joining us.
Yeah.
Hopefully we'll see you here again.
Yeah, that was fun. Thank you, Julie.
Thank you.