Mike Cannon-Brookes
Co-Founder
Sorry, Keith, I can -- good to hear from you. There's no doubt we've been through these technology transformations before, right? And when we go through them, you run through the hype cycle up and down, and there are certain words that mean something and then mean nothing and then end up meaning something. I think agents is probably squarely in that camp. We -- by that, the word is used everywhere suddenly for all sorts of things that I would argue aren't agents, but you can't control how the world uses a word. At Atlassian, we take a pretty pure approach to things and we tend to be pretty clear. We've been very declarative on what we feel is and isn't an agent and how we feel that we are building those agents, right? To me, they have to have goals, they have to be aiming at outcomes, they generally have some sort of personality and character, they have sets of knowledge that they can do and sets of actions that they can take, and some sort of control parameters in terms of commissioning and everything else, which ends up making them look extremely like a virtual teammate and represented in the software as such. Again, Atlassian agents are unique in that they can basically anywhere that a human being can be used in our software, an agent can do the same sorts of things. You can assign them issues, you can give them certain sets of knowledge, you can give them permission to certain actions and not other actions, et cetera. So that's pretty differentiated to other people who are building either some sort of a chatbot or fundamentally just something they're calling an agent. What differentiates us? We've been pretty clear on this, but it's really well worth reiterating. Firstly, we do have a significant R&D investment and an advantage in our ability to deploy that R&D. Why is that important in an agentic or AI world? Firstly, it's moving very quickly. So, our ability to build, deploy, get customer feedback and learn in a loop is really, really important in order to navigate these transitions. Anyone who tells you they know where this is going to be three years from now is a fool. What I can tell you is that we have to be able to learn really fast and move really fast and take the latest and greatest innovations and deploy them and get them to customers quickly. That is the best strategic path to gain that value over time. And we are obviously doing that and I think doing really well in the R&D team in how we do that. Second, any agent is going to be qualified by the quality of models for sure. So, what is underlying these agents is a series of different AI models. We have a very comprehensive multi-model strategy. So, we believe that models will continue to get faster and cheaper, and quicker to deploy and more capable. Therefore, our Atlassian Intelligence needs to be able to keep adapting modern models as fast as possible. Again, we're running more than 30 models from more than seven different vendors today. We continue to evaluate new models. Obviously, we've had a lot of movement in that space in the last week or two. Thirdly, it's all about the data you have, the data you have access to, the quality of that data, the ability to search across that data and the ability to connect it, that's where our investments in enterprise search, very big investment in the last few years and in a teamwork graph over a long computer time. Our graph has made major strides even in the last quarter about the speed of access, the density of the graph, the number of connections we can support, et cetera. That all is the fundamental knowledge layer that gives those agents capability to actually deliver something to a user in whatever form of outcome. And we feel we're very uniquely positioned on the data side at the moment and continue to invest there. And lastly, it's about the interfaces. So the surface level is really important here, both from a design perspective, but also from the ability to have access to those customers. That's where our more than 1 million Atlassian Intelligence now, we're obviously continuing to grow that number as fast as we can with great features that let us learn in the interface layers, right? Ultimately, customers and users don't use an AI model, they use a piece of software, they use some high-level technology to interact with an agent. How that interaction works, everything below that is up to us to do in terms of the data, the models and the R&D. But we feel really confident in our unique positioning and are going to continue investing behind that trend.