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

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Mike Cannon-Brookes on AI in the enterprise, Atlassian’s new org chart, and why chatbots aren’t the future of work.

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.

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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.

Mike Cannon-Brookes, you’re the co-founder and CEO of Atlassian. Welcome to Decoder.

I am really excited to talk to you. I believe you’re in Australia?

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 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 distributed company as we have done since the start. When you start in Australia and San Francisco, you kind of get used to the Pacific Ocean being a little bit of a distribution. This was before Zoom. We used to have these giant Polycom systems in meeting rooms. We don’t have those anymore.

Technological progress is nice.

We have customers all around the world. We have staff all around the world. We are structured functionally, I guess you would say, with a lot of matrices internally. I don’t know if that’s the answer you’re looking for.

No, that’s absolutely the answer I’m looking for. What do you mean by “functionally with a lot of matrices”?

We have a CRO. We have a CFO. We have two CTOs at the moment. We have two large product groups, each of which has a CTO and a chief product officer, one in the enterprise and emerging side and one in the future of teamwork side.

Our products are organized into collections. We have collections of apps that are all built on a single platform. Well over half of our R&D is on the platform. The apps are increasingly a smaller amount of the proportional total investment in building. More and more is on the singular Atlassian platform. Customers hire us as a platform across their business to get work done, not for a single application.

That requires a matrix internally. We don’t have salespeople per product, if you want to think about it that way. The sales, customer success, and the FDEs are all customer-related motions. They’re organized as per the customers and their geographies and their size and scale. Then we obviously have to have designers and product managers on particular products who care about the purpose of a product, so you end up instantly with the matrix between how the customers are organized and how the products are organized.

We have a giant platform. We have the technical platform that runs across all the products. It’s a very large platform team. We then have finance and talent and other things that are also broad processes. Naturally, you end up with collaborative areas that you have to get together, and we manage that through our operating processes.

We do. We run entirely on the Atlassian platform. I used to say we’re the number one user — we’re not anymore — of our strategy and operations products to understand what our business is focusing on, what our large-scale goals are, how the people, the investments, and the technical systems all come together, and what is going right and wrong across all of those.

We are a big believer in our Strategy Collection to operate a large-scale business.

One of my favorite questions to ask enterprise software CEOs is how much they personally use the enterprise software. How much do you personally use your products?

My number one feature request is usually continual UI congruence. I guess that’s the category that people would put it in. I’m a bit of a stickler for design and consistency. We want to achieve eventual consistency in design, in which we’ve come a huge distance in the last five years. In the last two years, we’ve been truly world-class at doing it.

That’s usually my biggest area where I use a lot of our products on a regular basis. As such, I’m moving around the platform, and I’m looking for ways where this thing over here happens this way. They do it better over there. We’re trying to achieve that eventual consistency across a large product surface area.

I use Dia, our web browser. I think 96 to 97 percent of Atlassian now uses Dia on a regular basis. I mean, that’s a daily basis, so I literally spend many, many, many hours of the day on it. We are building a web browser for ourselves because we’ve reached the point that we feel, “This thing should just be better for knowledge workers.” We’ve already built, I would argue, the best browser for knowledge workers in the world, and it’s getting much, much, much better.

Keep watching this space.

So, yes, I would say there’s no 24-hour period that goes by where I don’t use one of our products. I doubt there’s a six-hour period that goes by where I don’t use one of our products at the moment.

I want to talk about Dia in a second, because I’m very curious about that acquisition. Obviously, we covered The Browser Company very deeply at The Verge. That was a big acquisition for you guys.

Setting that aside for just one second, one of the things I’m particularly curious about here is the distinction between the platform and the products that run on the platform. Again, maybe this is just reductive, but it sounds like there’s a big layer of capability, and the products are expressions of those capabilities in different ways, but they’re all running on the same core platform.

Yes, absolutely. Yes. We have to build a singular R&D platform, whether that’s how we talk to AI gateways, whether that’s how chat works, whether that’s how automation and identity and logging and governance and compliance and content classification work, whether that’s how our home and our search engine work.

There are many, many more technical capabilities that have to be shared.

Then you have all of the next layer up, and customers want that to work the same. It doesn’t matter if I’m in Confluence or Jira or Loom or the Service Collection, automation shouldn’t be different per place in the world. That’s very expensive. It’s very hard. It takes a lot of time, but it delivers a huge amount of customer value and loyalty.

Most vendors don’t try to do that. They literally don’t try.

Then you have a layer up, which is important, which is the consistency of operation and how content can be mixed. Operations and processes can be mixed across applications. If I open a Confluence page inside of Jira, I want that to feel like a Confluence page, but I want it to be inside of Jira.

I don’t want to leave Jira to open it. I just want to read it, close it, keep going. There’s a lot of UI layer, a sort of recomposability, if you want to think about it that way.

Lastly, each application has to do its job. If you blend enterprise software together, you end up in a world of hell. People have tried this many times. You want a tool to do a job. You want to pick up a screwdriver or a hammer or saw and feel like that thing’s going to do the thing you hired it to do.

The interface is designed to help you do that task. That’s where there is a difference in the interface layer and the interaction layer, between those tools.

The combination of those is where a lot of our design challenges live. For example, our chat layer, Rovo, is amazing. I would argue it’s one of the best, if not very close to the best enterprise chat products in the world. Our customers continually say that. “How come you’re better than insert-famous-brand-here?” There are a lot of reasons why we perform better in evaluations and testing with Rovo.

It’s not because we make a foundational LLM, I think, which is the flaw of thinking.

However, using Rovo inside a product, if you’re going to Rovo for the sake of Rovo, is awesome. You have a question to ask, you want to search across everything, fine, you go to a particular interface. If you’re inside of Loom or Jira or the Service Collection and you just want to open up chat, ask a question, you want it to understand the context you’re in, but you want that operation to be consistent across the platform.

That’s what we’re striving to deliver to customers.

One of my constant tropes on the show is that if you describe to me your org chart, I can tell you 80% of your problems. The structure of the company leads to some kind of natural politics in some kind of way.

The tension between “we have products that are designed to do a job” and “we have a platform that contains the core capabilities” is pretty well known.

Maybe your product teams are going to desire platform capabilities that don’t exist yet or they will desire different platform capabilities from one another. How do you break those ties? How do you make those calls?

We have a number of ways that we are different and we try to do that. First, I would say most importantly, we have a platform-centric CEO and co-founder who thinks in terms of platforms. Thinking in Systems is my favorite book, man. I have a copy on every desk.

You have to put