The SaaSpocalypse that wasn’t, with Atlassian CEO Mike Cannon-Brookes

Today, I’m talking with Mike Cannon-Brookes, who is cofounder and CEO of Atlassian. Atlassian is one of those companies that every other company runs on — it makes important platform tools like Jira and Trello that allow people to organize and manage big teams, create shared databases of company information, and generally allow work to happen. As you’ll hear Mike say, all of Atlassian’s products are actually different expressions of a single core platform, which really shapes how Atlassian itself is structured and how those products are built. All of this means Atlassian is also right in the middle of the way AI is changing how all these companies work — AI tools might be able to look at all the different tools and systems you have and just read them for you, making a big migration to Atlassian’s platform less enticing. Or, if you buy the idea of the so-called SaaSpocalypse, AI might just build all of these tools for you, destroying this entire category of businesses. Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get your podcasts. Head here. Not a subscriber? You can sign up here. Obviously, Mike had a lot of thoughts pushing back on this. So we spent some real time talking about the value of design, human users, how AI is actually increasing the usage of Atlassian’s tools, and what this all looks like a few years from now. Of course, AI has also changed Atlassian. Like so many other tech companies, Atlassian did a round of layoffs earlier this year, with Mike saying he felt the company needed a different “mix of skills.” So I asked Mike what he thinks that mix of skills is and how AI is changing what it means to run a software company. But Mike was also refreshingly direct about what AI can’t do, and he was willing to push back on his own friends like Cloudflare CEO Matthew Prince, who was just on the show talking about AI eliminating what he called “measurement roles.” This was a fun one — and shoutout to Mike, who recorded this from Atlassian home base in Australia, which meant he had a deep conversation about org charts at 5AM. Okay: Atlassian CEO Mike Cannon-Brookes. Here we go. Mike Cannon-Brookes, you’re the co-founder and CEO of Atlassian. Welcome to Decoder. Thanks for having me, man. I am really excited to talk to you. I believe you’re in Australia? Yes. It’s tomorrow for you. What’s going to happen tomorrow? It’s tonight. It’s a great day here. It looks beautiful. It looks like it’s going to be an amazing day. At this point in the AI news cycle, I feel like I can just demand to know what’s going to happen tomorrow, and everyone understands the urgency behind that question. There’s a lot going on with Atlassian. There’s a lot going on with your products. There’s a lot going on in the very concept of SaaS businesses and business processes generally. Let’s start at the very start. I think people know Atlassian. They know Jira. I started my career as a Trello person. Tell people what you think Atlassian is today. Atlassian is a platform that enables businesses to collaborate and manage work across their teams. We connect their business teams and their technology teams to handle the most challenging work problems in a singular platform across any organization that is technologically driven. For any organization that has software and technology as its core competitive advantage, we make a broad platform that allows them to collaborate on content, manage projects, and unleash the knowledge of their teams and organizations across their business, their strategy, operations, all the way through to their service teams in all areas of their business. It’s a very large platform now that we provide. Just in terms of what work is today and what it might be in the future as we add more and more AI to these enterprises, maybe this is too reductive, but I have always thought of Atlassian as a company that makes tools to help teams figure out what they’re going to do tomorrow. Jira is a perfect example of this. You don’t do the software engineering in Jira, but Jira helps you organize large teams of software engineers and file tickets and prioritize problems and tasks. I was a Trello person a long time ago. My goal in life now is to never use any enterprise software. I feel like that’s a sign of true success if you’re just an iPad person in first class. I’m working on it. I’m not saying I’m there yet, but that’s one of my goals. But there was a time when I was the managing editor of The Verge and my job, straightforwardly, was to look at Trello every day and make sure everyone was doing the right thing at the right time. And I’ve always thought of Atlassian as that class of products. We’re going to organize the processes of the company. There’s something about AI that’s changing that. Has that conception of Atlassian changed for you? Is it changing faster because of AI? Understanding what work you have to do at an individual level like Trello, at a team level like Jira, or at an organizational level like our Strategy Collection for large-scale strategy and operations — that is definitely a big part of what we do. Understanding where processes are at — It’s less about work to do than processes. If you think about a business as a system of processes that are put together, everything in a business is some sort of system. It’s a process in the collection of all these, and how well we execute them is what your business is doing. The fundamentals of that haven’t changed. The way those processes run, the number of them running, and how to figure out what’s going on hasn’t changed. We think about Jira as a human reference to work. When we say that, it’s a really interesting term because, as you said, the work is not done in Jira. Developers don’t live in Jira. Marketers don’t live in Jira. Finance people don’t live in Jira. Jira is a workflow engine with highly collaborative parts that enables teams to understand what they, their colleagues, and their broader organization are doing. That’s why agents and AI and other things are going to increase the speed of those processes. In a lot of ways, they will increase the reliability, the quality, and the consistency of output of certain processes. They also put more emphasis on where the humans, the judgment, the intuition, the human bits that are unique, and the initiation come from. It’s our job to make sure that that’s all still understandable so someone can just look at any level of their business and know what the fuck’s going on. What are people doing? Are we successfully doing whatever it is that we’re trying to do, whether that’s service function in a finance sales deal, exception service desk to work out how many exceptions did we give out in sales this quarter, or it’s an engineering team who’s trying to work out, “There’s stuff happening all over the place. What did we build this month? Or what are we going to build next month?” All of those things are incredibly hard to do at scale and volume in a business. One of the more important features of the tools you’ve built is legibility. It’s user experience. You have a big database of exceptions given out by salespeople, and you need to look at a dashboard and see how the company’s doing. Or you have a whole bunch of tasks, and Jira will let you see at various different levels of abstraction how many tasks are being completed at any given time. That was something that was very important for human managers. A lot of the capability unlock of businesses as they added software like the software Atlassian makes is to just be able to see and coordinate more things at a higher scale. The turn that’s coming is that maybe those databases aren’t going to be looked at by human beings anymore, or they’re going to be fed into more synthesized databases, or AI is going to make some other kind of information at different levels of abstraction. I know you’ve got a product called Rovo which feels like the new face of Atlassian in some ways. What’s the path here? What does the end state look like? There’s no doubt AI is going to help with a lot of those processes. There’s no doubt it’s going to pick up some steps in a process. Most businesses at the moment have a process, and they’re using AI to automate 80% of this step. It may not be 80% of the distance. It can be the width. If you think about that sales deal exception process that you just mentioned again there, if AI can take 80% of the exception — say this customer wants 45 days, not 30 days — and we can write a relatively readable document, AI is pretty good at reading the document and saying, “Yep, this one’s fine.” But there’s going to be a customer that needs a lot more complex exceptions. They say, “I want to pay in 90 days in this way, and I want this thing and that thing.” That needs to go to a human for intuition and judgment. So 80% of those may be easier done with AI now because it’s very capable at processing our rules in this particular part of our business, and that’s great. It’ll increase the speed of the process, the quality of it. It doesn’t take away the need to know what’s going on. Someone in the business will still need to know, “How many exceptions did we give?” What happens in most of these areas is businesses find way more ways to make themselves scale and efficient, and they find way more ways to make higher-quality products and services with AI. I see this all the time where they are utilizing AI in ways that people don’t expect. It’s not all about mechanistic efficiency. There’s a huge amount of quality that is able to be measured and understood that was never before. The deal exception process is a good example because it’s actually a very human process. It’s not usually rule-driven. The rule-driven parts are easy. It’s the non-rule-driven parts that are more complicated and require judgment. The business still needs to know, for that process, “Do we need to add more people to this process? Do we need to change it? How much is going through it?” You still have a lot of work to understand the flow of work around an enterprise, which gets more complicated as the flow’s volume goes up a lot. I’m asking because I’m headed towards a series of questions about the supposed SaaSpocalypse, and I’m very curious where you think tool providers like Atlassian fit next to the frontier models are just going to eat more and more capability. Eventually, Claude will just do this for you. You’ll say to Claude, “Run my business for me.” In the backend, Claude will burn a bunch of tokens, and it’ll just do it all for you, which is a promise that many, many people seem to believe in. You’re describing a somewhat different path where the tools get smarter or more capable because of AI, and you’re still adding a lot of human judgment, but at no point is a frontier model just coming and running your entire business for you. If a frontier model is capable of coming and running the entire business for you, if it’s truly running the whole thing, even assuming four or five years worth of increase, you have a relatively simple business. Most businesses aren’t simple. They are global conglomerations of rules, compliance, laws, staff in different places, human inconsistency — which is the same as saying human creativity — that they’re putting it all together to try to deliver products and services for their customers in their industry: healthcare, university, finance, automotive, or whatever the industry is. They’re trying to compete with some other business. They are still going to have a huge number of humans, I would argue more knowledge workers, more developers, in five to 10 years time than today because the ability to do tasks to compete will go up. The bar for competition will go up in almost all these industries. You will still have a huge amount of things to go do. Most of the things that we think are simple will get done for you. That is the history of technology. I’m a big fan of saying AI is just technology. What we can do with spreadsheets, what we can do with the internet, what we can do with ordering goods online… You think, “Once Amazon arrives, we’ll all just never have to go to the shops again.” It doesn’t happen. I heard someone talking about bank branches as an analogy, which I thought was a really good one. Around 2000 when mobile banking came along, everyone thought bank branches were dead. Bank branches started closing down. Everyone wasn’t going to go to their branch anymore. It was a pretty negative place. At least it was in Australia. I’m pretty sure it was in America as well. If you look over the last 10 years, bank branches are increasing. People are like, “Huh, this is a narrative violation. Why is this?” And the answer is bank branches did close down. People did go to internet banking. They did use their mobile app. They don’t go into the branch anymore with a passport to say, “I’d like to send $100 to Nilay, please. Here are his details,” and write them all down. But bank branches have adapted. The reason they’re growing is there is a huge customer service element to a bank branch. The services they provide today are totally different than what they provided 25 years ago due to the technology of the bank and the availability of things. They are much more about helping you with higher-level processes and services than they ever have been. That turns out to be, presumably, profitable for the banks, which is why they’re opening new branches. Bank branches are going up. The things those branches are doing are totally different to what they were 25 years ago. I think you’ll see the same thing with knowledge workers and everything else, that it will still be incredibly important. I don’t see that part changing. I am working my way up to getting Jamie Dimon on the show to find out what happens in all the Chase Bank branches in New York, because I don’t actually know, but we’ll set that aside. Jamie will come on the show. We’ll ask, and we’ll figure it out. One of the reasons I’m asking all these foundational existential questions is to understand how you feel about Atlassian’s relationship to businesses and how businesses might change as we add new technology. I agree with your general framing that automation technology arriving to a business is a pretty familiar phenomenon, but there’s something else going on with AI that is either making that faster or more dramatic. It’s obviously happening to your business as well. You’re the CEO of Atlassian, and you’ve made some changes around AI. I want to ask you the Decoder questions now. How many people is Atlassian today? And how is it structured? We are, I think publicly, 12,000-13,000-odd people around the world. We are structured globally, I would say. We are “Team Anywhere.” Employees have the choice to come into an office or not. About 60 percent of people come in three days a week or more. About 25 percent of people don’t come in a single day per week. We run as a globally di