The SaaSpocalypse that wasn't, with Atlassian's CEO

My guest today is Mike Cannon-Brookes, who is co-founder 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. This means Atlassian is also right in the middle of the way AI is changing how all these companies work. 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. Obviously, Mike had a lot of thoughts pushing back on this narrative, so we spent time really digging in and talking through what AI is doing to enterprise software. Links: How Australia became the test bed for tech regulation | Decoder (2021) Building a $45B company far from Silicon Valley’s ‘froth and bubbles’ | Semafor Atlassian CEO Mike Cannon-Brookes on Atlassian and AI | Stratechery How Atlassian shook off the 'SaaSpocalypse' for a big rally | IBD Atlassian acquires The Browser Company, maker of the Arc browser | The Verge Atlassian Co-CEO resigns, leaving Cannon-Brookes as sole chief | Bloomberg Atlassian cuts 1,600 jobs amid AI push | Forbes Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder’s producers are Greg Ott, Kate Cox, and Nick Statt. This episode was edited by Ursa Wright. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinde Learn more about your ad choices. Visit podcastchoices.com/adchoices

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• 1:46Speaker 01

  Hello and welcome to Decoder. I'm Neelai Patel, editor-in-chief of The Verge, and Decoder is my show about big ideas and other problems. Today, I'm talking with Mike Cannon-Brooks, the co-founder 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 those products are built. All of this means Atlassian is also right in the middle of the way AI is changing how every company works. 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.

• 2:30Speaker 01

  Or if you buy the idea of the so-called SaaS apocalypse, AI might just build all of these tools for you, destroying this entire category of businesses. Obviously, Mike had a lot of thoughts pushing back on this, and 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 all this might look 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 that he felt the company needed a different mix of skills. So I asked him 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 willing to push back on his own friends, like CloudFlare CEO Matthew Prince, who was just on the show talking

• 3:14Speaker 01

  about AI eliminating what he called "measurement rules." This was a fun one. We got deep. And shout out to Mike, who recorded this from Atlassian home base in Australia, which means that he had a deep conversation about org charts at 5:00 AM. Before we get started, subscribe to Decoder on YouTube to watch new episodes every Monday and Thursday, and subscribe to The Verge to listen to this episode and every episode completely ad-free. Okay, Atlassian CEO Mike Cannon-Brooks, here we go.

• 3:50Speaker 01

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

• 3:53Speaker 02

  Thanks for having me, man.

• 3:54Speaker 01

  I am really excited to talk to you. I believe you're in Australia. It's tomorrow for you.

• 3:59Speaker 02

  It is. Well, it's today. It depends on...

• 4:02Speaker 01

  What's gonna happen tomorrow? At this point in the AI news cycle, I feel like I can just demand to know what's gonna 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.

• 4:28Speaker 02

  Atlassian is a platform that enables businesses to collaborate and manage work across their teams. So 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. So 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, 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

• 5:13Speaker 02

  business. So it's a very large platform now that we provide.

• 5:16Speaker 01

  Let me ask a question about that, 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 gonna do tomorrow. So like Jira is like 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 like 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.

• 5:58Speaker 01

  But there was a time, 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, right? We're gonna organize the processes of the company. There's something about AI that's changing that. Has that conception of Atlassian changed for you, and is it changing faster because of AI?

• 6:25Speaker 02

  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, right? Understanding where processes are at, it's less about work to do than processes, right? 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 some sort of process, and 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, how to figure out what's going on, hasn't changed, right? So we think about Jira as it's a human reference to work.

• 7:10Speaker 02

  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. What Jira is, 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, they're gonna increase the speed of those processes. In a lot of ways, they will increase the reliability, the quality, the consistency of output of certain processes. And they also put more emphasis on where the humans, where the judgment, the intuition, the human bits that are unique, the initiation, come from.

• 7:54Speaker 02

  And it's our job to make sure that that's all still understandable, right? So someone can just kind of 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? Whether it's an engineering team who's trying to work out, man, there's like 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.

• 8:29Speaker 01

  One of the more important features of the tools you've built is legibility. It's user experience, right? You have a big database of exceptions given out by salespeople, and you need to look at a dashboard and just 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. And that was something that's very important for human managers, right? And 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 higher scale. The turn that's coming is that maybe those databases aren't gonna be looked at by human beings anymore, or they're gonna be fed into more synthesized databases, or AI is gonna

• 9:13Speaker 01

  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 way. What's the path here? What does the end state look like?

• 9:25Speaker 02

  Look, there's no doubt AI is gonna help with a lot of those processes, right? There's no doubt it's gonna pick up some steps in a process. Most businesses at the moment, they have a process, and they're using AI to like automate 80% of this step, right? And it may not be 80% of the distance, it can be the web, right? So if you think about that sales deal exception process that you just mentioned again there, if AI can take 80% of the exceptions, say this customer wants 45 days, not 30 days, and we can write a relatively readable document, AI is pretty good at reading a document and saying, yep, this one's fine, right? But those are gonna be a customer that needs a lot more complex exceptions. They have, well, I wanna pay in 90 days in this way, and I want this thing and that thing, and that needs to go to a human for intuition and judgment.

• 10:10Speaker 02

  So 80% of those may be easier done with AI now, because it's very capable at processing our rules and, you know, in this particular part of our business, and that's great. It'll increase the speed of the process, the quality of it.

• 10:28Speaker 02

  It doesn't take away the need to know what's going on. So someone in the business will still need to know, okay, cool. How many exceptions did we give? And 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 about quality that is able to be measured, understood, that was never before, right? And the deal exception process is a good example because it's actually a very human

• 11:13Speaker 02

  process. It's not usually rule driven. The rule driven parts are easy. It's the non rule driven parts, right? That are more complicated and require judgment. Overall, 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 is, it gets more complicated as the flows, volume goes up a lot.

• 11:42Speaker 01

  I'm always asking these questions because I'm headed towards a series of questions about the supposed SaaS apocalypse. And I'm very curious where you think tool providers like Atlassian fit next to, okay, 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. And 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. And you're describing a somewhat different path, right? 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.

• 12:22Speaker 02

  I think if a frontier model is capable of coming and running your entire business for you, even assume four or five years worth of increase, you have a relatively simple business, right? If it's, if it's truly running the whole thing. Most businesses aren't simple. They are global conglomerations of rules, compliance, laws, staff in different places, human inconsistency, which is the same way as saying human creativity, by the way. They're putting it all together to try to deliver products and services for their customers in their industry, healthcare, university, finance, automotive, whatever the industry is. They're trying to compete with some other business.

• 13:04Speaker 02

  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, the, 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 get done for you. That is the history of technology, right? 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, right? You're like, ah, once Amazon arrives, we'll all just have, never have to go to the shops again.

• 13:49Speaker 02

  Like, it doesn't happen, right? If you think about, I heard someone talking about bank branches as 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 just, you know, 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. And 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 the internet banking. They did use their mobile app. They don't go into the branch anymore with a passbook to say, I'd like to send a hundred dollars to Neilo, please. Like, you know, here's 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.

• 14:34Speaker 02

  The services they provide today are totally different to what they provided 25 years ago, due to the technology of the bank and the availability of things that, you know, they are much more about helping you with higher level processes and services than they ever have been. And that turns out to be presumably profitable for the banks, which is why they're opening new branches. So 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, I don't see that, that part changing.

• 15:09Speaker 01

  One of the reasons I'm asking all these kind of 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. And I agree with your general framing, right? 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. And it's obviously happening to your business as well, right? You're the CEO of Atlassian and you've made some changes around AI.

• 15:37Speaker 02

  Yep.

• 15:37Speaker 01

  So I want to ask you the decoder questions now. How many people is Atlassian today and how is it structured?

• 15:43Speaker 02

  We are, I think publicly 12, 13,000 odd around the world. We are structured globally, I would say. So we're team anywhere. So employees have the choice to come into an office or not. About 60% of people come in three days a week or more. But 25% 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 distribution. This is before Zoom. We used to have these giant Polycom systems in, in meeting rooms. Good, we don't have those anymore. Technological progress is nice. We have customers all around the world.

• 16:27Speaker 02

  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.

• 16:38Speaker 01

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

• 16:43Speaker 02

  So we have a CRO, we have a CFO, we have two CTOs at the moment. We have two, two large product groups, each of which has a CTO and a chief product officer, one on the enterprise and emerging side and one on the future of teamwork side. Our products are organized into collections. So we have collections of apps that are all built on a single platform. Well over half of our R and 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 single Atlassian platform, right? Customers hire us as a, as a platform across their business to get work done, not for a single application. That requires a matrix, a matrix internally, right?

• 17:28Speaker 02

  We don't have salespeople per product, if you want to think about it that way. We have to have people who, the sales, customer success, the FDEs, they're all customer related motions. So they're organized as per the customers and their geographies and their size and scale. And then we obviously have to have designers, product managers on particular products who care about the purpose of a product. So you end up instantly with a matrix between how the customers are organized and how the products are organized. And then we have a giant platform. So we have the technical platform that runs across all the products. So it's a very large platform team. We then have, you know, finance and talent and other things that are also broad processes. So naturally you end up with, you know, collaborative areas that you have to get together and we manage that through our operating processes.

• 18:13Speaker 01

  Do you use the Atlassian platform to run Atlassian?

• 18:16Speaker 02

  We do. We run entirely on the Atlassian platform. We're the, 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, where the people, the investments, the technical systems, how they all come together and what is going right and wrong across all of those. So we are a big believer in our strategy collection to operate a, a, a large scale business.

• 18:45Speaker 01

  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?

• 18:53Speaker 02

  An awful lot.

• 18:55Speaker 01

  What's your number one feature request for your teams?

• 18:58Speaker 02

  Look, our number one, my number one feature request is usually continual UI congruence. I guess that's, that's the category that people would put it in. I'm a bit of a stickler for design and consistency. We, we want to achieve eventual consistency in design, which we're, we've come a huge distance in the last five years and the last two years have 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. And as such, I'm moving around the platform and you're looking for ways where this thing over here happens this way. Hey, they do it better over there. And so we're trying to achieve that eventual consistency across a large product surface area. I use D R, our web browser is like, I think it's like 96, 97% of Atlassian now uses D R

• 19:43Speaker 02

  on a regular basis. I mean, it's not going to daily, daily basis. So I literally spend many, many, many hours of the day. We, we are building a web browser for ourselves because we've reached the point that we're like, man, this thing should just be better for knowledge workers. So we've built already, 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,

• 20:09Speaker 02

  I would say there's no 24 hour period because it goes by where I don't use one of my products. I'm not sure there's a, I doubt there's a six hour period that goes by where I don't use one of our products at the moment.

• 20:18Speaker 03

  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, and 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 in the platform. And again, maybe this is just productive, but it sounds like there is 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. Is that, is that how you think about it?

• 20:46Speaker 02

  Yes, absolutely. We have to build a singular R and 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

• 21:04Speaker 02

  content classification, whether that's how our home, our search engine work, there's many, many more technical capabilities that have to be shared. Then you have all of the next layer up, which is, 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. I don't have to, automation shouldn't be different per, per, per place in the, in the world. And 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

• 21:42Speaker 02

  and how operations, processes can be mixed across applications. So 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 want to leave Jira to open the, if I just want to read it, close it, keep going. So there's a lot of UI layer, sort of recompose ability, if you want to think about it that way. And then 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. And so that's where there is a difference in the interface layer, the interaction layer between those tools.

• 22:25Speaker 02

  And the, the combination of those is where a lot of our design challenges live. For example, Rovo is our chat layer is amazing, right? 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's a lot of reasons why we perform better in evaluations and testing as Rovo. It's not because we make a foundational LLM, I think, which is the, the floor of thinking. However, using Rovo inside a product, if you're going to Rovo for the sake of Rovo, 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, you know, the Service Collection,

• 23:07Speaker 02

  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 is, that's what we're striving for, to deliver to customers.

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• 26:45Speaker 03

  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, right? 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, right? It's 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?

• 27:15Speaker 02

  Look, we have a number of ways that we are different and we try to do that. First, I would say most important, 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. It's the job of, you have to put the platform first collectively. And then you go solve a bunch of problems. That does not mean genericism wins, but it does mean when you make trade-offs, you have to spend the extra effort and time to make it platform centric, to make it work. And that is a forever task, right? So it helps to have a CEO, if you think about the referee across all the functions that's platform centric. They know where I'm going to land and so we're going to end up there.

• 28:01Speaker 02

  Secondly, we have design as a very, very senior role. We have a massive investment in design. Our chief design officer sits, reports to me, sits on our executive team. We have three, four, five now chief design officers in the business from other very large businesses, some larger than us. We have a huge investment in design and experience, and I think in, especially in the AI era, that's getting ever more important actually.

• 28:27Speaker 02

  Much as Claude Design or something would tell you the opposite, I don't think so. I actually think design and the experience of software, if the, if the cost of building goes down, the quality differentiation is on the experience and the design, and that's not something that's easy to do. That requires a huge amount of taste and judgment. Lastly, I think we aren't afraid to put things together in unusual ways in the organization where we need to solve problems. So the latest example of that probably is our internal IT and engineering function

• 28:55Speaker 02

  now reports to our chief people officer and have combined those two roles, which is unusual. Like, why is HR running IT? That doesn't make any sense. It actually does, I would argue at the moment, because of the things we need to do to transform our business internally continually, which is that if I look at AI and becoming more AI native as a business, I ended up with two piles of projects. A pile of projects that relate to talent, how I need to change and grow the people we have, get them using these technologies, get them thinking in certain ways. I have a huge talent problem. Hiring, growing, training, changing people is very difficult to be competitive. And I have a huge system problem. I need to change our internal systems to have MCP servers. I need to make sure that everything is operable.

• 29:38Speaker 02

  I need to make sure that we have all of these system changes so that AI rolls out. How are we managing our token spending? You know, there's a huge amount of system change. And so I end up refereeing a bunch of, is this a talent problem or a system problem? And I said, that doesn't make any sense. Usually the answer is this one's 60% talent, this one's 40% system, and this one's the opposite way around. So I've put them all together inside the business so that our system changes to apply AI internally and our talent changes to apply internally are, have, are in the same function right now. Which is a little odd, right? The people who deliver the laptops and the people who manage compensation work for the same group. But it actually makes logical sense based on what we need to change about our business at the moment, right?

• 30:23Speaker 02

  What is this sort of three year epic that needs to change?

• 30:28Speaker 02

  So I do think we organize around the problems we need to solve and the goals we have as an organization when we need to.

• 30:33Speaker 01

  This is a brilliant segue because I wanted to ask about this executive you have. I believe the formal title of your HR person is now Chief People and AI Enablement Officer.

• 30:43Speaker 02

  Yes.

• 30:44Speaker 01

  That's quite a title. And the point you're making about the the systems of the business needing to change, leading to some change in your talent mix is coming true, right? In March, you laid off about 10% of the company. I watched the video you made in Loom about that. And your point there was you're not necessarily replacing people with AI, but you had identified a change in the mix of skills that the company needed, and you were going to make these changes proactively. Walk me through this. What made you say, okay, AI is here sufficiently that the mix of skills is different? And what changes did you make to your systems to make losing 10% of your people effective or worthwhile?

• 31:24Speaker 02

  The environment we've lived in in technology for a while is continual hiring and growth.

• 31:31Speaker 02

  The markets have changed on their view on that, right? So you have to say that because one of the ways that we've managed changing businesses over time has been hiring people in different areas, right? If you have red dots and blue dots and you say, well, we need more green dots, you just say, well, we're going to hire all green dots for a while until we have a blend. And you kind of you manage it that way. That is no longer a feasible path, firstly. Secondly, we have certain areas of the business, right? Our AI.

• 31:57Speaker 01

  Wait, actually, can I ask one question about that? You're kind of describing the COVID era over hiring that every tech company are doing. And you're saying that's kind of over.

• 32:06Speaker 02

  I don't. Yeah, I think people hire at the rate of the best decisions they know at the given time and what they're encouraged to do by others. Hopefully, they don't look at everybody around them, but I know that a lot of CEOs do look at the people around them and be like, I should do that. I always think those are poor choices, but over hiring, I don't know. Pre-COVID, we were a few thousand people. You know what I mean? So we're four times, I don't know, three times the size we were pre-COVID, probably. Our businesses, you know, again, we're accelerating as a business, right? We grew 30 odd percent last quarter on a $7 billion run rate, which is the fastest we've grown in about two years. So customers are opting for more acceleration.

• 32:48Speaker 01

  I think I'm just trying to understand the you can't just hire a bunch of green dots comment a little more clearly because I've heard from many of your peers. Oh, yeah, during that period, we just hired everybody that we could. And it sounds like that's not specifically what you were experiencing, but it rhymes in some way.

• 33:06Speaker 02

  It does rhyme, but I think there are definitely periods where that is the way to go, right? That's not the current three, four year, you know, a period of time, right? So that's, that's the first thing I say because then you need to work out how do we change our skill mix? So we have a huge amount of internal programs to try to do that. We also have certain areas, our AI products and services specifically, and our enterprise sales areas are growing very, very fast. They're doing well, and we want to invest further in those areas, right? And so when you have certain areas you need to invest further in, you run into very difficult choices where you're like, okay, I need to invest further in these two areas. I can't grow the overall in a significant way.

• 33:49Speaker 02

  I have to manage how to transition the organization between that, right? Which leads to a lot of very difficult choices. We are still hiring really hard in those areas, right? In order to change the skill mix, but you also have a question of how fast we need to do that. It doesn't, I always say, take away from any internal

• 34:09Speaker 02

  training programs. I say that in sort of air quotes in terms of how AI is adopted and used. It's more around learn, play, share, you know, mutual learning. It's less like an L and D, I think, in terms of I'm going to sit down and watch a class on how to do this. But that doesn't take away from that. It's a combination of all these factors as we've massively changed the business to be, you know, truly world leading at AI product development in the last two years. There's no doubt that's been a rapid journey, and we're trying to move as fast as we can to to get there and to stay ahead.

• 34:42Speaker 01

  One of the things I've heard from a lot of CEOs in your position is, oh, the value of our senior people has increased, right? There are more senior software engineer job listings out in the market right now because that, as you've said, that judgment and that taste is very important, and maybe the tools can just build that stuff for you. I'm curious for your view on design, right? The idea that all of our designers will not be enabled to just ship code is very tempting to a lot of people. And then there's, you know, a third view that says product managers' roles do everything, and all these roles are going to come crashing into each other. So what mix of skills specifically did you identify? And how are you prioritizing in this sort of classic triumvirate as more and more people get the ability to do all the other jobs?

• 35:22Speaker 02

  I think it's very easy for people to have

• 35:26Speaker 02

  very binary takes on these things, right? I find it amusing that if you put an engineer, a designer, or a product manager in a room, they'd all sit there and they'd all say, oh, man, it sucks to be you. Your job's going to go away. And I'm like, ah, that that probably is your answer right there. Look, we have a lot more product managers and designers who are writing code from prototypes to actually shipping code than we ever have before. That is for sure. We have a lot more marketers and finance people and and HR people who are doing the same thing, by the way. The code that they are writing and shipping builds on two things. One, a platform that has the engineering robustness to be able to scale and deliver

• 36:08Speaker 02

  to customers a European compliant data resident solution that is necessary, the legal constraints of company, country X, et cetera. So you have to build a technical environment that that is able to get out to a customer with the required degree of customer safety. That is a non-trivial problem. That's not something you're just going to vibe code. If I'm vibe coding my own solution to something for my household, fine. It can just work well enough. I'll go fix it if it doesn't. If I'm doing that for a large organization, I need some other controls and rules around it. Secondly, I think the specialization of those areas all doesn't go away. The the human judgment required in different areas, it's like the edges of the roles are blending.

• 36:53Speaker 02

  They're able to do a little bit more of someone else's job, right? I have a lot of designers who are able to ship prototypes that are working code prototypes instead of a picture or a fake prototype in terms of a mockup. That's great. I still see them sitting in Figma a lot and doing that. I have a lot of engineers who are sitting in Cursor or Claude Code or whatever on a daily basis, writing features and building things, and they're able to do more design than they were before. That doesn't replace the need for the other job, and it increases the quality of the overall software. It increases the speed of collaboration between people, if you want to think about it. If they each understand each other's role, they can have a much more fulsome conversation more quickly.

• 37:37Speaker 02

  The specialized nature of what they do goes up. It becomes more spiky, I think, which is really, really important. The ability of building platforms is going to get overused here becomes more important. So we, just this week, for example, we shipped, one of our designers wrote an interesting blog post about, we now have an MCP and a CLI for our design system internally. We have a award winning design system, atlassian design. It's very public. We publish all of our design system. I've always said, the role of design, 50% of their job is to make our design system and to keep it being scalable, flexible, and buildable. 50% of their job is to solve the hardest 5% of problems in design.

• 38:23Speaker 02

  Because the half where they're building the platform, that what used to be templates and design documents that are now CLIs and MCPs to do design internally in the way that we want design to work so it's consistent and coherent, that is a really hard problem to build that. However, they're unleashing thousands, if not almost tens of thousands of engineers to build better designed things when they do that, right? Their leverage is a lot higher in building a design system than it is in solving, help me with this screen, help me with this screen. And it's the same in security. It's the same in customer, supported customer success, actually, right? If you think of bug fixing as the platform on which you reduce customer service,

• 39:02Speaker 02

  more and more of that role is required on building those scalable templates, platforms, ways that the other functions can build on top of. So they can do that thing, right? If a product manager is vibe coding a feature, as in they're just stabbing around some sort of code generating area, and it's an area where it's not infrastructural, it doesn't need to scale, it's, you know, fine. It should leverage our entire design system. Turns out, out of the box, that's not very workable. So we've just shipped MCPs and CLIs internally, which are like on V4, that are amazing at understanding our design system. So the designers can evolve that system, and the features that are being built will continue to match what customers expect in their congruence and consistency.

• 39:46Speaker 02

  That gets us huge leverage overall, but it's a non-trivial thing. It doesn't mean the designers are going to go away, the engineers are going to go away, the product managers are going to go away. I don't, I don't think any of those roles disappear.

• 39:57Speaker 01

  I'm always joking that Decoder is fundamentally a show about org charts, which means I think I know what the next five years of the show is going to be about because we're on the cusp of some of the weirdest org charts in history in AI.

• 40:08Speaker 02

  True.

• 40:09Speaker 01

  Matthew Prince from CloudFlare was just on the show. We talked a lot about his Wall Street Journal op ed where he said, I'm going to fire all the measurers at the company because I can replace them with AI. They can look at all of my systems and do all the auditing for me. And we're going to have fewer middle managers because what they're really doing is measuring and auditing things, and AI can do that. Mark Zuckerberg. There are reports that he wants managers to have teams of 50 empowered by AI somewhere inside of Meta. This strikes me as not a great idea, but we're gonna see how it goes. Where are you? Are you in classic org chart? Are you at wild ideas? How is this coming together for you?

• 40:44Speaker 02

  I'm certainly more measured than that. And I think the reality of how the world will be. I think it's easy to point to extremities. Is someone somewhere a manager with 50 people? Sure. Are they effective? Maybe. People always talk about Jensen. He's obviously very effective. He's a good dude. He runs things in a very weird way. Is that scalable and repeatable? I'm not sure it's scalable and repeatable. I'm not sure if you took an entire set of large companies and made them all work that way, they wouldn't have worse results as a collective. Part of business is scalability and consistency and able to be understood and managed. That doesn't require uniquely talented individuals to understand a very

• 41:24Speaker 02

  odd structure as they move around a business. I suspect you are going to get more role blending, people able to handle multiple types of skills. I suspect they're going to be more sort of generalists. The edges of the role will blur into the roles around it. A product manager is able to do a bit more marketing and a bit more engineering, right? And I think that applies almost all across the way, right? Finance people are probably able to do a bit more legal than they were before. They're able to understand the legal frameworks we have internally with agents. And that's great, right? I don't think that changes the roles themselves. I think it may make teams a bit broader. I do agree with Zuck's general direction that organizations will become a broader triangle,

• 42:08Speaker 02

  a fatter, wider triangle, right? The companies will get wider and hence less deep. I think broadly, that's a true direction. Do you go to 50 person teams? Then his span of control is like three people. Like, I mean, the organizational depth is like three or something. If you multiply by 50 at each level, you have two and a half thousand people with two levels of reports. I would question that. So that's probably not an average. I don't know about this term measurers. I don't know that anybody had sit around in a knowledge work job and say, my role, my purpose is to measure things, right? I just walk around with a ruler and I'm like, oh, that's a foot. I know there are a lot of

• 42:48Speaker 02

  jobs where that becomes, I know what Matthew's saying, that becomes the effective output of a role. We're measuring it for a purpose, I would believe. And we are going to work out how to make that more scalable. My probably way of looking at it is a little bit different. I think there are two types of jobs. If you want to simplify an organization, there are supply constrained and there are demand constrained jobs inside a business. So input bound and output bound. Well, what is the constraint on a job? So look at a marketing or a technology function, a creative function versus a legal or a customer service function.

• 43:30Speaker 02

  Legal and customer service are input bound. If I deploy it, I don't suddenly get a lot more contracts, right? Like the number of contracts coming in, if I'm looking at NDAs or leases or trying to understand a company's legal position in certain areas, I can process potentially that work faster with AI. And through systems, you know, I can be more efficient in how I do that. That is one set of roles that you can look at almost everything in a business process and say, that's input bound. I'm going to manage that differently than things that are output bound. If I think about marketing or engineering, unless I run out of roadmap items, which I've never heard any engineering team in my history of 25 years of doing this, where they're like, actually, we've reached the end of the roadmap

• 44:12Speaker 02

  and we'd like some more ideas of what to do next, please. Right? Said no one building software ever that has a large customer base, their output, their creativity is not, is bound by their own initiation and their ability to organize groups of people and processes and everything else, which is what the lasting platforms do. That is their limiting factor. It is not the human ability to create ideas. And so it may be that you have less input bound functions and areas as a proportion of your total employee base. And you have more creative output bound functions, you know, how much is this human ingenuity and

• 44:49Speaker 02

  creativity and imagination, right? A possibility. I think that's likely the way things shift and trend over time. I think that's going to take much longer than people think. We're big in technology. Next year, everything will be like this. And it takes 10 years to happen, but it will happen. I think I'm very fond of this term. I keep meaning to put up a rant online about it. I think we used to talk about information asymmetry, and I'm stealing another friend's quote here, but we used to talk about information asymmetry and how much certain people know things. And that is their source of power or advantage. I do think we're moving to, he said it, and it really hit me like a bolt. We're moving

• 45:31Speaker 02

  to imagination asymmetry. We're moving from information asymmetry to imagination asymmetry, where your ability to create and think is going to be far more important as a competitive advantage for your team, your job, your business, than your access to information, your control of information, your understanding of information. That part is going to be cheap. That's what LLMs are really good at. What they're not good at is imagining things, right? They didn't decide to start at LST. What business has been started by an LLM? Zero in the world, ever. Right? They got made of control.

• 46:03Speaker 01

  Hey, I think has run a failed vending machine for several years now. Come on.

• 46:08Speaker 02

  But it requires a human to say, you know what we're gonna do? Let's fail at running a vending machine today. Right? They were probably sitting in front of a vending machine, cursing the thing when it didn't drop their candy bar. And they said, I'm gonna, I'm gonna do this better with AI, which is probably the way that most of those companies think about every single problem, right? As they're staring at vending machine. It required a human being to say, let's go do this. And it required them to write a bunch of stuff to go create the vending machine operation code and try it. And, you know, we all learned a lot as a result of this scientific experimentation.

• 46:45Speaker 04

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• 47:42Speaker 03

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• 50:18Speaker 01

  Let me ask you the other decoder question, then I want to apply all of this to what is broadly happening to enterprise software in SaaS. The other decoder question I ask everybody, how do you make decisions? What's your framework for doing that?

• 50:28Speaker 02

  I would say I make decisions by talking a lot. That's what people internally would truly say. I find the need to discuss things from different angles very important. I like to let other people talk. I like to get all the information together. I do believe there's obviously a time where we need to say we need to stop and just move in a certain direction. I think the more important part for me than how I make decisions is I really like to explain decisions to people. You know, at Atlassian, we have a value, we open company, no bullshit. And I tell people all the time, that does not mean transparency. We don't owe you as an employee, all of the details behind

• 51:11Speaker 02

  every decision. We don't want to, all the sausage making is not useful. It's overwhelming to people. It doesn't help us move fast. We do owe employees clarity on why we are making a decision and an explanation of said decision. And I think that's one of the most important things managers can do for training, for helping their talent grow is not, we're going left, but hey, we thought about it, we looked at the different options, we considered straight, right, left, here is the pros and cons, we're going left, this is the reason why we're going left. Often, people don't do that because people don't like the decision. Right? And I say that all the time, when you talked about our, you know, talent mix changes in March, we have to make a lot of hard decisions

• 51:55Speaker 02

  to run this business. I want to make sure that we are always explaining those decisions to people in the clearest and simplest way we can, why we've made a decision, and what the decision is, without any dressing. And I really don't like these corporate emails where I read the whole thing. I'm like, so what are you saying exactly? Like, you've got a lot of words here. I'm like, here's what we're doing. We need to change our skill mix. Here's why. You should have the right amount of empathy to explain decisions of, you know, especially hard ones. But you also should not expect people to necessarily like it. Like, we make a lot of hard decisions where I'm sure 60% of the company, 70% of the company thinks it's a great decision, 40% think it's a terrible decision. We build trust as leaders by explaining our decisions and being clear about why we've

• 52:40Speaker 02

  made it and how we've made it. And hopefully, we improve decision making across, right? I would say decisions get to my desk when they're presidential decisions. I think it was Obama that called it that, where it's 51-49. That's why I've made it to my desk. If it was 90% certain what we should do, we should not have made it to my desk in the first place. I only get hard decisions. That's, that's, that's a well-operating company. I think any leader should be in that situation. If it's an obvious decision, why did it make it to you? So that then requires more thought and more explanation about those decisions. I think that's probably the most important part than any sort of framework we use to make them.

• 53:18Speaker 01

  So let me put all of this under some pressure. You've described Atlassian as a platform, a lot of an organization's decision-making and data and capabilities in that platform. What are we going to do next? How are we going to do it? Is it working? The entire point of the SaaS apocalypse was, well, we don't need your beautiful user interface. We don't need your design surfaces or congruence of design across products. All we need is your data. And if I unleash Codex upon your data store, it won't even matter that it's the same platform. You can have 15 different vendors, and the AI will create itself some middleware and read and synthesize all the data, and that'll be great. And like, actually, your business can leap ahead

• 54:03Speaker 01

  in meaningful ways. I think my favorite example of this from a previous era was, I always had Daniel Dines from UiPath on the show. And instead of modernizing your healthcare billing system, he would just build robots that would use Windows 3.1 for you. Right? And this is like a very early version of what I think every AI company is selling right now, which is, instead of modernizing your backend and spending all that money on a migration, our robots will just use your horrible old databases and present to you a new user interface. That's one version of SaaS apocalypse. I see it coming for a lot of businesses. How do you expect to change all of Atlassian against that? Because a lot of what Atlassian sells is upgrade, right? Upgrade the

• 54:45Speaker 01

  whole platform. Use one product and use all the products. Use the whole platform. Modernize your entire business. And the other answer is, well, it's like $200 a month, and you can just token max your way into the future.

• 54:56Speaker 02

  You're talking about the headless sort of world, I guess. I, I say that headless is brainless. It is literally the same thing. It is submission in slow motion, if you're a software vendor, to do such thing. And I say that very carefully, because again, it's one of these answers that requires nuance. We have one of the most used MCP servers in the world. We've just shipped a giant upgrade to it. We've written it from scratch. It is massively used on a daily basis by millions of people, and it's amazing. MCP servers, we've shipped three or four CLIs that are also used incredibly heavily. The ability to have interoperation of tasks is

• 55:39Speaker 02

  very, very important for customers to get jobs done, and I totally agree with that. However, and people who use our MCP server and our CLI, they actually grow faster. They create more issues in Jira, they grow their seats faster. We say this publicly on earnings calls, I think it's like, at least 5% faster. They grow their ARR at twice the rate of customers who don't use our CLI and MCP servers. So the customers using these things are growing their Atlassian spend faster than they have before. So that world, I totally believe in. When I hear the word headless, though, I think that is the only world that we're going to exist in. Like, we just sell an MCP server. That is the brainless part about it. Because then your software really

• 56:20Speaker 02

  has no value. If you truly just have a database, fine. If your interface sucks, and I think a lot of enterprise software has horrible, horrible, horrible interfaces.

• 56:31Speaker 01

  This is why I ask all the enterprise CEOs if they use their own products. It's really just, how bad does your interface suck? Yeah.

• 56:36Speaker 02

  Oh, I'm a big fan of recording the Loom and being like, guys, this doesn't make any sense. And I believe if you do that, that yak shaving over and over again, you end up with amazing interfaces. And that's why tens of millions of people wake up to our software. The investment in design and experience that I talked about is the antithesis of that. I actually think the world is very different than those views. We'll see a few these times who's right. The way the Atlassian platform works is not to be a single platform. I am probably the only CEO that goes into customers, massive, large-scale customers, and says, do not centralize everything on my platform. I do not believe that is a viable strategy for a CIO. I don't think it is. Our platform is highly connected. It always has been. One of the things that Jira, Confluence, Trello, the service collection do, is they interact with many, many, many, many other

• 57:19Speaker 02

  applications. You look at any work item in Jira that's been going for a while, it is full of links. Links to Workday, and Salesforce, and ServiceNow, and Figma, links to Source Code, links to Google Drive, and Teams. Links are what build our context graph, right? The reason we have the best context graph in the world is because we have a lot of links to start with, and we have had a 10-year history of having to understand how to be collaborative with other applications. Right? Our applications are by nature highly connected to the rest of your IT world, the rest of your technology world. We don't want to be a control tower. I think it's a stupid analogy. I think every CIO has been told, just trust us, we'll deal with all the problems. It's never worked. I don't think it ever will. The reality of technology is

• 58:04Speaker 01

  Well, once you add AI to the mix, maybe it'll work this time. I mean, this is the, this is the thing that is being sold, right? Is you have now a powerful, intelligent orchestration layer that will finally realize the stream.

• 58:16Speaker 02

  Three parts snake oil, two parts bullshit. I think the reality is, it will help all the applications, if built well, to work better with each other. There's no doubt, like, look at Figma and Atlassian, we have a deep partnership, we use each other's MCP servers a lot, and we can build better solutions for marketing teams, and designers, and technology teams between the two platforms than we ever have been able to before, because we can understand each other's data in ways that we never have been able to before, and we can solve workflows on different ends. If you're sitting in a deep design, you're sitting in Figma. It's a visual experience. If you need that to be tied to work, and then understand how to find that, that moves back

• 59:00Speaker 02

  into our world, and we want to make those journeys as seamless as possible. We want to be not a control tower. We want to be a subway station that is highly connected. We want to be Union Square. We want to be Town Square. We want to have a lot of lines going through us, and we want to make that experience for our customers the best that they can. So I think it's 98% was our stat on the earnings call, more than 98% of people using our MCP server also use the user interface. And that is not changing. Right? The ability to do work faster doesn't mean I just stop using it. If you invest and have a good interface and experience, and you're solving high-level problems. If you look at the features we're shipping around,

• 59:41Speaker 02

  agentic uses, right? So how do these harnesses, Claude, Codex, and everything else, work inside the Atlassian world, and vice versa? Now, one world is, I open up Claude, I say, hey, go work on this work item. It uses our MCP server to go and get the work item. It uses our teamwork graph to go and get all the context around the work item that is necessary and related, and that gives it the best chance of doing that job the cheapest possible. That is certainly a way that people are going to work. And Claude's going to move the work item along to the next stage. Awesome. There are a lot of other people who start in Jira, and will say, hey, send this work item to Claude. And then on the board, it tells them the work item's running and going, they're in an interface that is built for the task, back to the saw and hammer and sort of

• 1:00:26Speaker 02

  screwdriver analogy. It's built for the task they're doing. It needs to understand, hey, Claude needs your attention. Inside of Jira, you can open Claude, say you need to, send it off. Most people don't use Claude. Most people don't use Codex. Every company, customer I go to has a whole bunch of harnesses running. They're going to have internal ones they've built. They're going to have, you know, two, three, four vendors. Most people aren't making a choice. They're all amazing. They're all over, leaping over each other in progress. Our job is to bring all that together into a coordinated surface, to understand your agentic sessions, your human sessions, your work, to connect all of your enterprise applications into a giant graph, and to give you phenomenal answers across the whole thing. That requires a lot of interface investment. That is hard.

• 1:01:11Speaker 02

  That takes time. That takes great design and experienced folk. That takes taste oriented product managers and engineers. That is a non trivial challenge. And I do think a lot of people are avoiding that challenge. And I don't think it'll end well for them. I don't think the world is going to live in a CLI as an end tool. I think.

• 1:01:31Speaker 01

  You don't think the chatbot is the final, final user interface?

• 1:01:34Speaker 02

  I don't think chatbot is the final answer, no. I think we learned this in 1970 with the CLI. We don't know, we're all learning what the future interface is. It doesn't mean that chats aren't going to be a part of it. It's just, where does this sort of world work? You know, you talked about DIA. DIA is a good example where we're trying to build a AI driven experience for knowledge workers that is based in the world they understand and still magical and different, not based in a taking them out of the world they understand to a chat based interface.

• 1:02:10Speaker 01

  So DIA is the browser. You acquired a company called The Browser Company, I think for a little over 600 million. That was a year ago. We spent a lot of time with The Browser Company when they were working on their products. And, you know, at first they were building a consumer product. And then the notion that what they were building was more like an operating system came into focus as we covered DIA and their, and their product strategy. And most of those conversations and most of that coverage, most of which was done by my colleague, David Pearce, was happening simultaneously with Google search traffic dropping, right? And the very notion of the browser as an information document viewer was changing in big ways. If you think the homepage of Chrome opens to Google and that's going to take you to

• 1:02:53Speaker 01

  a bunch of webpages, well, actually, Google has a lot of ideas in between there that is changing traffic on the web. And yet, at the same time, the web is an application environment, is a thing that can make AI agents vastly more capable, because the applications all live somewhere that they can go address them. It was, it was just obviously explosive at that time. You and I are talking, it's like a week or two into Meta launching Muse. And the power of Muse is that Mark Zuckerberg has given everybody eight gigs of ramen, eight gigs of storage in the cloud with the web browser. And now you have an agent that can just go use a web browser for you. And this is like very powerful and Amazon is furious about it and has blocked this web browser. Do you have DIA because you need to control the application layer? Or is it something bigger than that?

• 1:03:38Speaker 02

  I think two, two things are important to understand. When you get technological disruption, one thing that happens is we all move up the interface stack a level, right? Not a lot of people competing about DOS or operating systems anymore. In the modern internet world, one way to move up the interface stack is to move towards the browser. Features that were inside of applications moved to being inside of the browser as we increasingly learn and operate that way. I think second, the biggest thing that's changed, and you know, usually people's habits change is what happens. Knowledge workers, yourself, myself, everybody, we spend 80% of our lives in a browser. But we're not reading articles all the time.

• 1:04:23Speaker 02

  We are sometimes. We're not reading webpages. We're using applications. We're using Gmail and Google Calendar where we have Slack open. We're using the Atlassian platform, all of our applications and Salesforce and, you know, our, we're watching videos like, like Loom and we're interacting with those videos back and forth. That set of tabs is no longer a set of webpages. It is a set of documents and applications that have massive power underneath them. We're trying to rebuild the web browser in a totally new form for knowledge workers who live in applications, who have their browser open 80, 90% of the day as their

• 1:05:05Speaker 02

  front surface area and want a better way of managing those applications and getting work done across those applications. The browser has some incredible power to be able to do that. It requires us to understand SaaS apps very deeply, which we do. It requires us to understand enterprise security very deeply, which we do. It requires us to not chase the consumer audience. Chrome, Safari are built the way they are because they have to cater from five year olds to 100 year olds who are doing less work related knowledge tasks and are doing more browsing and entertainment and other tasks. That doesn't mean that someone who's a knowledge worker in a corporate job isn't looking at YouTube or Facebook sometimes, but it's not the purpose of their job.

• 1:05:50Speaker 02

  So we believe we can build a better browsing experience, a better work experience, right? One of the pitches we had for the product is we're not building a browser. We're building a doer, right? It's a totally different thing. We're helping you do things. We're not helping you browse passively. And hence why tabs and split screens and pinned tabs and groups and AI and dynamic tab groups, live tab groups as we have of the documents you have is a great example, right? Our documents live tab group in DIA shows you the documents. It will automatically open and close tabs, if you want to think about it that way, for you across any content application. Google Drive, Confluence, SharePoint, any application you use that has documents.

• 1:06:35Speaker 02

  If someone comments or shares a document with you, the tab automatically gets opened by your web browser. And if you're done with it somewhere else, it automatically gets closed by your web browser, because that is a set of documents I'm currently working on. Same for pull requests or anything like this. Then we add AI over the top. AI lets us change how we use these knowledge applications in insane ways. The browser has your entire history of what you've done. It has skills. It has an ability to run AI. Like you can use DIA to make Minesweeper. And you can use DIA to make Minesweeper out of the tasks that you did in the last week. And it'll go, start a computer underneath the browser. It'll run a bunch of code generation.

• 1:07:18Speaker 02

  It'll create an application for you that plays Minesweeper based on the tasks you have completed in the last week. Now, I don't think that's a very useful application, but the fact that it can do it is amazing. When you apply that to what you can do, so the most popular feature of DIA is the morning brief. People are blown away and often suspicious about how we can understand what you need to do today with a fidelity and a design quality and an experience that makes it a joyful experience when it pops up every morning. Mine opened about 45 minutes ago. That is a design challenge. It is an amazing team of designers that are thinking about our most used application surface area and reimagining it for knowledge workers and for the AI era simultaneously

• 1:07:59Speaker 02

  with access to every SaaS application that you have open on your computer in a way that corporate security is going to say, this is a good idea and I trust it. And that is the mission we embarked on a year ago, Browser Company embarked on three years ago, and it's usable today. It's coming out on Windows any day now. It's in beta on Windows, GA is very, very soon. And it's used on the Mac by a huge number of people on a daily basis and only increasingly.

• 1:08:28Speaker 01

  Let me just push you a little bit on moving up the stack to the next level of user interface. You could argue that already happened with web browsers, right? Windows was disrupted by the very presence of the web browser. The iMac was only successful because the, the most interesting thing you could do with a computer at that time was go on the web. And so the presence of the web browser on the Mac allowed a bunch of applications to move away from Windows binaries to being web apps and then cloud apps and now productivity apps in the cloud. The web as an application environment is probably more vital and important than ever before, right? It is, it is the thing you're describing. It's where all the applications live and a custom web browser designed to do work is very important. At the same time, I, I would just say like, didn't that already happen?

• 1:09:13Speaker 01

  Are you actually moving up the stack? Are you just building a more custom web browser? Or is AI changing that in some other way?

• 1:09:20Speaker 02

  AI is changing that. AI is giving us the ability to help you understand what work you have to do, not just your browsing history, right? One of the most powerful things about AI that I think people don't broadly understand is an LLM's ability to generate content is kind of well known. I can say, tell me a dad joke and it spits one out, right? It, it streams out tokens. What is more important, I think, for application vendors like us?

• 1:09:47Speaker 02

  People who are trying to make tools and products and solutions for customers is the ability to read text, not write it, but read it. Because we can understand meaning for the first time ever. We can understand what a page or a comment or a piece of text is about. Then we can make application level choices, which we never could do beforehand. Word didn't know what document you were writing. When it said, it looks like you're writing a letter. It was like really shit house and it was a terrible experience. Now it can actually tell with super high fidelity. Are you writing a letter? A PhD? Is it a high school essay or a university essay? And it can adapt and change its interface. The ability of Dear and AI is to understand what it is that you are browsing, what it

• 1:10:32Speaker 02

  is that you are doing, to be able to reach into applications to get content and to pull it back to give you tools to manage your day. So the morning brief looks across your calendar and your messaging tools and your document tools to tell you what it is you have today in a very intelligent manner, the way it would be if you gave me all your content and said, spend the days. Now it reads millions of words in order to generate that. And it has a lot of smarts to give you a very simple experience of the most important things you need to do today that are totally different from anybody else on the planet. That requires a lot of AI to do and it requires connections to all of your SaaS apps.

• 1:11:16Speaker 02

  The browser is logged into all those apps, so it can do that, right? And it happens locally. It happens in on, it doesn't happen in the cloud. It happens on your machine. That is something that we could never do before to understand, hey, of these 10 documents you looked at yesterday, here's the one you need to do today, because I know in your calendar, you got to do this tomorrow. You got to do these things, right? This is the most important thing for us to do today. And let me help you get started on that task. Let me draft some notes for you. Let me help you with that document. Let me help you do things. That is something that was never, ever possible beforehand. Lastly, it understands the people you interact with. People are left out of so many of these conversations and equations. You can think of Dear as having a mini CRM that is constantly updated based on your browsing habits.

• 1:12:00Speaker 02

  It's a weird analogy, but it's effectively what it's doing. One of the things, many things it's doing inside the browser, which is why its answers are so good. It knows that you and I don't know each other very well. It knows I know my head of engineering extremely well. So if that person asked me for something, because it's maintaining a constant context graph of people relationships across every single one of your SaaS applications into duplicating and normalizing and using AI. All of that helps to understand what tasks are actually important to me, right? It can look at LinkedIn and see who you are and say, man, that interview prep you got to do today, you should put that up your stack. Dylan is an important person. It, it, it does all of that for you.

• 1:12:43Speaker 01

  Can you put that in the DS system prompts so people know when they come to talk to me? Just hard code that in there.

• 1:12:48Speaker 02

  We'll see if we know some people. It's hard and the experience, none of that should need to be known by somebody using Dear. The experience should just be a beautiful, joyful way to start your day. We want to leave you with more sense of calm, control, comfort about your day, not stress about AI, right? Leave that to us to do really well and we just give you the answers that you need from your tools and applications. It also does not mean you use less of those tools and applications, right? I don't use Dear and stop using Slack. I don't use Dear and stop using Confluence. It's helping me understand which thing do I need to do next by understanding what's inside those things, right?

• 1:13:32Speaker 02

  By cross referencing with my LinkedIn and my Salesforce and my Microsoft Teams conversations and meeting transcripts, but it's doing that all for me in the morning and during the day to be able to say, here's what you have to do next. Here's the most important thing and providing an interface to allow me to organize and group those tasks in ways that hopefully bordering on joyful. And I say that they're beautiful and simple experiences, right? And there's so many lovely touches in Dear that just make it a joy to use every day. So we're, we're pushing that mission really hard.

• 1:14:07Speaker 01

  It seems very obvious to me that you have a very clear view of how AI should work in the enterprise and how work should get done using your tools, your tools enhanced by AI, your tools expressed in your browser. There's focus there and I appreciate that. On the other side of the house, on the consumer side, my argument has been, well, the reason people hate AI and they're mad about it is a little bit because, you know, the doomers have said there's a 10% chance we're all going to die and all of our jobs are going away. But there's also no great products, right? There's not as much coherence and focus as I'm hearing from you in the enterprise context. Do you think that there's some great consumer AI product in the offing that has the kind of focus that you have in enterprise?

• 1:14:51Speaker 01

  Because that seems like the, the missing piece for me.

• 1:14:53Speaker 02

  Yes. If you look at the history of technological disruptions, the products that came through the disruption often aren't linearly related to the disruption. If you think about the smartphone era and we all pick up our smartphones 100 times a day, don't tell me you don't. When the iPhone came out, we were all excited by little bits and pieces. We did not think, man, that camera thing is going to lead to this Instagram phenomenon. We did not think the GPS is going to lead to Uber and so I can take transportation, right? The products that came as a result of the technology shift, the iPhone is an amazing business, don't get me wrong, but the, the services and changes to life didn't come from the iPhone. They came from the apps that it enabled, like Uber and Instagram and whatever else

• 1:15:38Speaker 02

  you like on the mobile phone. It can be a game, it can be anything. Those take a while for people to play with the form factor, to understand the bits, right? Uber didn't come along until the iPhone six, because it all needed to kind of get better, right? And, and like, then someone's like, wait, we can take a car with a phone and it'll just show up and yeah, we can show you where the car is and we can build enough trust and we can build a whole service layer. So I suspect one part of it is in AI, we need to keep playing and Muse, I know the Muse team pretty well, that's an amazing example of an application. There are many, many more of these things. There's a company that one of my kids loves called Talon, I think, which makes these sort

• 1:16:19Speaker 02

  of Hollywood AI agent chatbot things with personality that someone from technology is just like, ah, that's just open claw with some skin on it. And kids are like, this is a character that I can interact with, right? Like it's an amazing psychology Hollywood game character. These sort of applications, we're just starting to see. It's going to be an incredibly exciting five years of those sets of applications, right? And I suspect it takes way longer than we think to understand, get to GPT six, get to understanding of memory and harnesses and putting all these things together. And it probably won't be open claw. It'll be some version of how an agent surfaces in a certain area of life. So yes, the products are still coming in the consumer space.

• 1:17:01Speaker 02

  Secondly, I think the no part of the answer is that AI is not a product. It's a technology. It's a piece of technology. If it just makes everything about your life a bit better, you won't even notice you're using AI. And actually that's the beauty of it. You can use Dear all day long and not realize how much AI it's doing. You're just like, oh yeah, the morning brief thing, it's really good. I look at it every morning. It's one of the most highly engaged features we've ever built. And it just tells you, here are the three things I think you need to do today. Here's what your day looks like. You want me to help you prep for this thing? And you're like, yeah, help me prep for that thing. You don't need to know it's AI. We don't tell you it's AI. We're purposefully not trying to hide it. We're not secret, but we're also, you need to have a great experience.

• 1:17:45Speaker 02

  You don't care there's LLM and tokens and gateways and massive amount of technology going on behind the scenes. You just want to know what are the three things I have to do this morning? And if you build trust in it, that's great. The hard part, when you mentioned the data centers and stuff is people want those experiences and they're going to be very joyful and very contented and more calm and happy about the experiences they're getting. They're just not going to be using AI, right? I, I tell this to, to people here all the time. Every time you take a photo on the iPhone, there is an insane amount of AI processing going on to make that photo look good. Insane amount. And photos look amazing on my phone compared to what they did 10 years ago and 20 years ago. Do I need to know that? Nope.

• 1:18:28Speaker 02

  I want to point at my kid, snap a photo and I want it to look good. That's great technology. When it disappears, that, that's what it should be in the enterprise or for consumers. There's no reason people in the enterprise should put up with shitty technology. I think that's consistent, but it's not going to be necessarily knowable that I'm using AI. It's just going to be an amazing product experience that says, DS says, hey, here are the three things you got to do today.

• 1:18:54Speaker 01

  Even beginning to describe the conversations I've had with the Apple camera team about the use of AI on those photos is a full other hour of this show that we do not have time for. Mike, this was a great conversation. What's next for Atlassian? What should people be looking for?

• 1:19:07Speaker 02

  We have a massive set of announcements in, I'm scared to say a bit over a week, 10 days. We have a biannual conference, our Team 26 EU in Amsterdam in 10 days' time. Announcements in every collection. You will no doubt see lots of AI features that are magical and disappear. You don't need to know that you're using them. Dear launches, Timo collection launches, a lot of fantastic Loom features. We haven't talked about Loom, massive in the AI era. So we have so much on Loom's agentic use, some of which has been online. Kudos to the partnership with the Cursor team who built some amazing Cursor and Loom features. So really exciting stuff coming up in the next, in 10 days' time.

• 1:19:51Speaker 01

  Well, we will have to have you back very soon to talk about what happens with enterprise software in just one year's time, because I'm confident it's going to change. Thank you so much for being on Decoder.

• 1:20:00Speaker 02

  Thank you for having me. Thanks, man.

• 1:20:02Speaker 01

  I'd like to thank Mike for joining me and thank you for listening to Decoder. To get new episodes every Monday and Thursday, subscribe to our YouTube channel at DecoderPod and find us on TikTok and Instagram under at DecoderPod for more fun stuff we put out almost every day. You enjoyed this episode? Please send a link to it to someone you think you might like it. It really helps us grow the show. You can also subscribe wherever you get your podcasts. Decoder is Praxion Verge and part of the Vox Media Podcast Network. The show's producers are Greg Ott, Kate Cox, and Nick Statt. This episode was edited by Ursa Wright. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinder.

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