SPEAKER_00: Our biggest competitor back then was a product called Bugzilla, which was made by Apache, and it was an open-source product out there. And the word Bugzilla came from Godzilla, which was the sort of Japanese film. But it turns out that actually Godzilla was the anglicized Western name. Gojira is actually the Japanese name, Gojira. And so we dropped the Go, and Jira became the product. And back then, you could buy forwarded domain names just on your credit card without any problems.

SPEAKER_01: Maybe I should have not started a software company and just bought up forwarded domain names. It would be more profitable. For sure. But we bought Jira.com, and we started building the product.

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SPEAKER_04: Hey everybody, welcome to This Week in Startups. Some companies are just so influential.

SPEAKER_05: They define a category or a region.

SPEAKER_06: And Atlassian really became the anchor, the foundation of the Australian startup industry. A lot of the great startups are alumni of Atlassian. And if you're in the tech space, you know the firm. Today, we're joined by the co-CEO and co-founder, Scott Farquhar, on the program.

SPEAKER_08: How are you, sir? Great. What year is this for Atlassian? You're obviously in the second decade. I'm not sure what year it is, though.

SPEAKER_01: This is year 21 or 22, depending on where you count the starting points.

SPEAKER_13: So it's been a while now. We've been around the block a few times.

SPEAKER_05: Yeah, so technically entering your third decade. Well done. And the crazy thing about your startup was it was largely bootstrapped, right?

SPEAKER_06: Like just two small rounds of funding, if I remember correctly. And then they came in years 8, 9, or 10 or something.

SPEAKER_00: Yeah, we never took primary capital onto the balance sheet. So like we did some secondary rounds to allow Mike and I to take some money off the table and allow employees to take some money off the table. But we've never taken primary money. And then we IPO'd in 2015. And so we originally took cash in 2010 from Excel because we wanted to head towards going public. Yeah. And as soon as you can see stories, I can go into that. And then in 2014, we did that sort of pre-public round that sort of popularized a bit these days from a, uh, public market investor to help us get across to being public.

SPEAKER_08: Yeah. To your real price, right? I have here in my notes. So this is incredible to, to build a company from inception to IPO without outside capital.

SPEAKER_05: I mean, that's really what I'd love to talk to you about. So how did the company start? What was the first product? And how do you build a company with essentially no venture capital, no seed funding? People right now in the United States, uh, man, it's the entitlement level was really high for about five years there, uh, where people wouldn't even start working unless somebody gave them 3 million bucks. They say, how do I do it? You know? And, uh, so let's get into it. It's perfect topic for, you know, 2023 when let's face it, the, the, the seed funding is really dried up, uh, continued funding also dried up. It's pretty dark out there for startups.

SPEAKER_22: So how did you do it? What was the first product?

SPEAKER_01: We started in sort of 2001 each time.

SPEAKER_00: And back then it was really like the dot-com crash. Like, and we think, you know, 2008, 2009, and, you know, kind of the current downturn is bad for, for technology and it is, but nothing really compares to the dot-com crash where most companies lost 90% of their market capitalization. People laid off in, in huge, huge numbers. And, uh, back then we, you know, we thought it was the right time to start a company, um, probably because we were just graduating out of college. We had no other choices. It was either that or go work for a bank. And so, uh, we, we decided we didn't want to have to wear a suit and go to work. We knew the graduate salary to work at PwC was $48,500. And we figured as long as we could earn more than that and not like have to wear a suit to work, we would be good. And so we didn't really have huge, um, you know, venture capital style ambitions, uh, at the start of our, our company. And I think the advantage back then was that, um, you know, while we couldn't get any money, uh, none of our competitors or no one else in the industry could get money either.

SPEAKER_24: And so it was a level playing field there. Yeah.

SPEAKER_00: Yeah, totally. Bootstrapping was a viable, uh, alternative. And, uh, and we also, I think there was some technology transitions going on at that time. And, uh, you know, we, we built our products on open source software, which meant we could catch up to many of the competitors that were, you know, had out there and been out there. We, uh, the browser was coming around. And so many of our competitors at the time had built client server products and, uh, they all built a browser, you know, add on as an extra thing, which meant they just had to support two different versions. And so we could catch up while they were building two versions of every feature, we could build it once. And so we bet on a new technology and also then, you know, the internet distribution had come around and it's a long, you know, way from there to now Stripe where you can just write a lot of code and take credit cards. But we were sort of very early days where you could, you know, conduct commerce online. And so instead of having to sell software for $50,000 or $100,000, which you sort of had to do when you were, you know, doing on a golf course and with credit cards and faxes and purchase orders, like we could sell software for $5,000. And so we have these huge advantages and a time that we can catch up with our competitors. And, uh, you know, being in Australia, I guess we didn't, uh, really know any different. I guess if we'd been in Silicon Valley, everyone would have told us that was impossible. Um, in fact, many Australian venture capitalists told us it was really impossible to build a business that way. Um, but it is a time and place that worked out for us.

SPEAKER_05: And you were builder founders, you were doing consulting gigs on the side, uh, high pet price consulting gigs, right? You can pay a couple of hundred bucks an hour. And then at night you're building Jira. Uh, and, and that is really the heart of bootstrapping almost every bootstrapping story. I hear starts with people doing some kind of consulting work. They got an ad agency, they got a dev shop, and then they see some opportunity to build a product and they go from building the product, you know, 20 hours a week and doing consulting 40 or 50 hours a week. And then the numbers just slowly switch to the point at which you just start telling customers, listen, I, I can't do any consulting for you anymore because we've got this other product that we built. Is that what happened over a couple of years?

SPEAKER_29: Yeah, it was, there was two bits of consulting. One is we started a support firm for a, uh, it was a company built out of Sweden called

SPEAKER_00: iron flare, and they had a product called Orion server, which is back in the application server days where there was like 50 different application servers, you know, vying for supremacy on the internet. And, uh, so we provide support for this small Swedish company who had most of their customers in America. And that was a terrible, terrible business. In fact, I'm glad it was so bad because many, I know many founders, you know, great founders get trapped in mediocre businesses. This was so bad. Uh, we had to get up at, you know, four in the morning or three in the morning when the phone rang to answer someone from the U S uh, you know, and, uh, and try and sound credible at three in the morning, trying to solve support calls. And so we did that for a while. Then we discovered writing software is actually our passion, not, you know, supporting someone else's software out there. Uh, and we started building that, but in order to bootstrap, we still needed money. So, uh, some of the people who had paid for consulting, uh, or pay for the support, chose to fly me across to the Netherlands, uh, to work and do some code review over there. And so I flew across for a couple of weeks and eventually a couple of months, and, uh, I would work during the day in, in the Netherlands on, uh, what was a billing system for the Dutch telecommunications company. And, uh, I do a good job over there and, uh, I'd read up textbooks at night on how to code.

SPEAKER_16: And, uh, then the rest of the time I'd be coding on JIRA, which was our, our first product.

SPEAKER_08: Yeah.

SPEAKER_05: I mean, that's bootstrapping at its best doing whatever it takes to keep the lights on, pay the bills and then diverting, uh, you know, the extra hours you have to building that product. And so how did you come up with the idea for, for JIRA? What's the origin story there?

SPEAKER_00: We found, uh, back then, um, in building our own software, like I couldn't doing the support work, we realized there was nothing to track all the tasks that we needed to get done. And we built something sort of really crappily internally, just because there was a need for it. And then we realized and went out to the market to sort of say, well, what else is there out there and there was nothing, there was either open source and the open source stuff was really terrible. And it would take you literally a week to set up, you know, the first stage was compile my SQL with these special flags. And, you know, that's not really easy for, for most people to do. And, uh, all you had very expensive stuff that started at a hundred thousand dollars, you know, going out from there and, you know, sold by IBM. And in many cases, the software was consulting where, you know, they'd come in and that was their introduction to your company rather than a product you would, you would buy. And so we really felt that there was something in the middle that you could put on your credit card and, uh, and do that. And, uh, our biggest competitor back then was a company called, uh, well, it was a product called Bugzilla, which was made by Apache and it was an open source product out there. And the word Bugzilla came from Godzilla, uh, which was the sort of Japanese, uh, film. And, but it turns out that actually Godzilla was the, uh, you know, anglicized, uh, Western name, uh, Gojira is actually the Japanese name, Gojira. And, uh, so we dropped the Go and a Jira became, you know, the product. And back then you could buy forwarded domain names, you know, just on your credit card without any problems.

SPEAKER_01: And yeah, maybe I should have given, not, not, not started a software company and just bought up forwarded domain names, would have been more, more profitable. For sure. But we bought, yeah, bought Jira.com and, uh, you know, we started building the product.

SPEAKER_36: Uh, amazing. And, and it was open source to start, uh, you're doing bug tracking, project management,

SPEAKER_05: and all that simple stuff, but people had solutions for this in the market. It was just generally client server software, or that was what you were up against the

SPEAKER_06: proprietary IBM software, Microsoft software, et cetera.

SPEAKER_00: Yeah, so I think there's a couple of things here. One is, there's a company called rational and I think it still exists somewhere. I don't know if they've been sold to these days, but, uh, when we started rational, had about a thousand customers worldwide. And, you know, those customers probably on average took, you know, spent a million dollars with rational, um, you know, between software and services and so forth and keeping it up. And when you're spending a million dollars with, uh, on software that really reflects it down to a very small number of customers that can afford to do that. And I think a decade later when I stopped tracking it, rational still had about a thousand customers. Yeah. And, uh, so our original goal was to be very different. We had our big, our first big, hairy audacious goal was to get to 50,000 customers, uh, worldwide. And it took us about 12 years to do that. Uh, and we set that goal when we had 500. So our big, hairy audacious goal for the company was a hundred times our current size, but more importantly, it was, you know, sort of a vector that really made us differentiated from everyone else in the market, because we were really going to go after high volume, low cost at scale and sell globally. And so that really put the tenants, like, if we're going to sell globally, you have to basically sell through your website. If you sell through the website, it has to be in a credit card. If it's on a credit card, you know, it needs to be able to sell itself because, you know, um, and it needs to be good enough that you can sort of try it out and then buy it. So I set out this virtuous cycle that we probably now known as product led growth, um, was sort of the, didn't have a name back then, but we were probably the, one of the earliest pioneers

SPEAKER_16: of people being able to try and buy business software on the internet.

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SPEAKER_05: The other thing people don't realize is you created Slack before Slack existed. People were using IRC, I guess, to do, you know, like some general team chat. Really hard to set up an IRC server. It's meant for developers, you know, core infrastructure of the internet before the web IRC. But you created HipChat and that was just a side project. Talk a little bit about that. I mean, obviously, you wind up selling it, I think, ultimately to Slack.

SPEAKER_06: But talk about that side project and what you got right there and maybe what you missed in terms of the opportunity to build something really big.

SPEAKER_48: Totally.

SPEAKER_00: So we, there's a company called HipChat that we were using internally. And, you know, we were early on the internet. I sort of feel like if we didn't build Jira, we would have built a dozen other products that we needed, you know, in terms of, you know, to build a software company on the internet. We built our own, you know, billing system and we built our own, you know, effectively version of HubSpot internally. So when you're, I guess, early in these trends, you get to see a lot of, you know, kind of the new ways of doing things. And one of the things we felt was we used IRC internally for a long time. We used a whole bunch of other, you know, tools out there. And then eventually we set it on HipChat, which is great because it was all in one and our developers loved it and so did everyone else in the organization. So it was sort of the first development tool where developers loved it and everyone else loved it. And we acquired them. When we acquired them, I think there were about six developers. And they had a quirky personality, you know, as a brand, as a company. And we, you know, doubled or tripled that team. And it was growing really fast. I think it was growing 300% to 400% year on year, which for most software companies, you would say is like, that's a home run. Like, you know, that's incredible. And but what eventually happened was Slack, you know, spun out of a games company that, you know, went south with Stuart, Stuart's second games company that went south. The first created Flickr, the second created Slack. And so they came out with a ready-made product. And, you know, Stuart was very good at branding and PR and so forth. And so they, you know, ended up growing 1,000% year on year or more. And so it showed there was this huge category there. And, you know, and eventually, you know, they, we felt that between when Microsoft Teams ended the market, there was, you know, two players, you know, between Slack and Microsoft. And we didn't think that it would support, you know, a third player in the market, even though we knew we had a better product, but I've used, you know, Slack since. And, you know, we used our product and I would still maintain we had a better product, but the market dynamics weren't going to allow three. And so my lesson for that particular thing, like, you know, when people ask me, what did you learn? What would you teach yourself or other entrepreneurs? A couple ones. One is if you're early to a market, you need to bet heavily on that market. And, you know, we bet, we, you know, doubled and tripled the team size, you know, in line with its growth, but we didn't bet heavily enough in that market. We should have, you know, taken our banner ads and we should have really pushed that. The second one for me is that in an engineering sense, when you have a small engineering team, you know, sub 10 people, the way that they operate as an engineering team is very, very efficient because you don't need to create documentation. Everyone knows where everything is. It's like a really small team. When you double that team to 20 or 25 people, you actually go backwards in productivity. You actually go, you know, and you really need to triple or quadruple the team to actually get forward momentum. And so though we doubled the team, we went backwards in productivity because you had to create all the documentation and the way the teams interacted and so forth. And so we should have really, you know, put a lot more effort behind that engineering team. And the last one is big markets can be way bigger than you think. And even if you've got the numbers at your back in terms of raw growth, you should always look at it in terms of like what does that compare to the market size and what does that compare to your competitors? And they were, you know, growing at stratospheric rates, you know,

SPEAKER_20: we could have grown faster if we push.

Chamath Palihapitiya: And this is the amazing lesson of entrepreneurship.

SPEAKER_53: Even if something's growing three or four times year over year,

SPEAKER_06: three or 400% growth, you really need to test to see if it should be 10x growth and not accept that it's three or four x and you have to be even more ambitious.

SPEAKER_05: But sometimes, you know, especially you guys were, you know, first time entrepreneurs now acquiring companies, you have to invest more. And then the paradox of investing, I love your second point, which is, hey, you had a bunch of people that actually creates all this overhead. It slows people down. And now it has to move from a 10 person little SWAT team, a little Navy SEAL team, a perfect Olympic team to now it's got to be an organization. And that's painful and requires infrastructure. And I suppose, you know, the other parts of the business, like JIRA are also growing incredibly well. So now you've got to pick which of these projects to focus on. And that also as first time founders doing this, you know,

SPEAKER_06: running a house of brands is hard. You need to have leadership in each one, huh?

SPEAKER_00: I agree. The trade-off between different, you know, capital investments is hard. And the interesting one for us is we were always profitable. So we actually had the cash ability to do that. It was constrained by the ability to find people and probably a little bit of risk tolerance. And that's interesting. As a bootstrap, there's a lot of advantages in that, you know, you're in control of your own destiny. But, you know, you have a history of measured, you know, kind of investment and seeing the return and putting more investment in over time. And I think that, you know, you've got to move to a VC model when you've got this huge opportunity that, you know, does that potential entrance and move a lot faster. I think we've learned that now when we looked at, you know, entering new products and new markets these days, we're much more aggressive with putting the investments behind these, the new markets we go into.

SPEAKER_57: So tell me now that you've got this new playbook and the go fast and really

SPEAKER_06: take the opportunity, what's the aggressive playbook? What's in that one as opposed to the bootstrapping playbook and how have you evolved that?

SPEAKER_27: Yeah. So if, you know, if the two original bootstrapping ones would probably say Giro and Confluence

SPEAKER_00: were our original bootstrapped products and both came from just listening to market needs where a customer had, you know, come to us and we looked and said, you know, we need this ourselves internally. And if we'll get more recent products, so Atlas and Compass, they still form that same playbook, which is we internally have needed something and we've gone out to the market and seen what's out there. And more and more, what we find is that we find products that companies like Facebook and Google, you know, have internal products to do these things, but there's no product out in the market. And so we feel like, well, we need to build it internally or we can build it for ourselves and customers. And that's what we've done really well over the years. And so now we, you know, build products internally for ourselves and we invest a lot more behind them. Like we'll put, you know, 50 to a hundred person teams on them, not to start with, because I think that's always a ramp period where you want a really small dozen people that build the core of any product. And I think that's the way to build any new go to market. But as soon as we start seeing traction in the market,

SPEAKER_20: we ramp up so that we can, you know, continue delivering features and make noise out there on these products.

SPEAKER_08: Okay. So I want to get to two things. One, how you market them and scale them. But before that,

SPEAKER_05: how do you know you actually have product market fit? I got that piece in there that you slid in there about how you find products. If Facebook or Tesla or somebody, you know, a video game company like, like Stewart's old video game company, build some internal product to make everybody more efficient. Well, of course the long tail of companies, the quarter million companies that you serve as half million companies service, whatever it is now, they're going to need it. Right. And they're, they don't have the ability to put 10 developers on and build an internal thing. Some brilliant insight. How do you know you have product market fit? Once you do have product market fit, how do you scale? What,

SPEAKER_06: what are the things that actually work with product led growth and products for developers and business teams?

SPEAKER_27: I think product market growth hits you in the face when you have it.

SPEAKER_00: And if you're ever worried that you don't have it, it's probably true is my experience. And if I go back to Atlassian's revenue numbers, and I'll be off a bit on this, this is not SEC approved sort of numbers, but like from my memory, like our first year, first full year of, you know, selling JIRA was about $300,000 worth of revenue. The next year was 1.2 million. The year after that was four year after that was 12. We then had 21, 35, 42. And that was when the global financial crisis hit. We sort of only went up 20% that year. Then we went to 56, 75, and I think about 110. And so those, you know, when you're going from 4 million to 12 million in revenue, and you've got a dozen people working for you, life is pretty good. And you're really just trying to hold on. And I feel like that's when you've got product market fit. You really have that sort of near vertical growth. And I've advised a whole bunch of startup founders who think they have a great product, but they get trapped in these terrible businesses that grow at, you know, 15% year on year on a couple of million dollars worth of revenue. And they're never going to be a hit. And in fact, a good friend of mine runs a company called culture amp. And they do employee surveys and they're, you know, very, very big company these days, but he was also someone I advised. He had, they did a different product early on and it just wasn't going anywhere. And, you know, I advised him that product market fit really does feel, you know, when you've got it. So we, we did that with, you know, JIRA and Confluence and, you know, and so these days, I guess we've got a good playbook about what that, what that looks like. And we keep trying, you know, until we've got that. And then on the growth side of things, it's interesting. Many enterprise businesses have sales driven motion. If you look at many of our peers, it will be, what's my revenue going to be? Well, that's really just the number of salespeople I've got times the quota that we put in them times the attainment ratios times our rent period. Like that is the way that they predict, you know, revenue and look at scale for enterprises. That's a, that's a reasonable way to do it. But if you want to build a product led growth company, it's much more like a consumer model. It's basically how many trials do I get? How many people are using the product? At what stage in the funnel are they? And that's much more scalable at that stage. You know, you're not throwing salespeople at it to get every incremental dollar of revenue. And, you know, so, so we focus on, on metrics, like how many active instances are there of our product out there,

SPEAKER_20: whether they're paying us or not, just how many people are using it. We focus on consumer metrics, like monthly active users, which is a big metric we use internally.

SPEAKER_58: So we're sort of much more consumer focused in the metrics we use.

SPEAKER_05: Does that mean you still don't have famously a sales team? You're still not doing like the SAS model. Let's get a bunch of salespeople here. You're still committed to, Hey, the product led growth model, or did you ever add salespeople? I remember in the early days you didn't have salespeople.

SPEAKER_00: Yeah, we, for a long time, we had the sort of no sales mentality. It'd be like Salesforce is no software mentality. It's a great tagline. You know, what a journalist want to write about it. And I would say, you know, of, of the 250 plus, 260,000 plus customers we have today, you know, if 260,000, 250,000 don't have any person that touches them in terms of sales. So we're still largely product led growth for everything that we do. What we found though, is as you get successful inside large companies, they then want to standardize on you, particularly in the last year or so, when people are trying to save costs, they want to standardize on you. And so they want to call someone up to have that conversation. And we found that having a more traditional sort of, you know, sales motion in those customers makes a lot of sense. And what we did with those people is we have incredibly high quotas because these salespeople are not out there prospecting for customers, trying to call people up, you know, looking at LinkedIn, trying to find a new prospect. It is really an existing customer that wants to talk to someone about how to use more of our products. And so I think that's the way of sales of the future is that, you know, if you're trying to get a new customer by calling them up on the phone, I think that's a really difficult motion, very expensive. You're ending up in head to head motions. And whereas if you start bottoms up, start with a team and a team's successful and they need it to another team, the enterprise process at the end to do a consolidation or get them to use a second or third product is a way different conversation that you're having. And particularly at our price points, we're subbing out a lot of competitors, you know, there are much higher price points, but we have the credibility because we're already in there. And I think that's the, that's eventually the model that, you know, I think most enterprise software companies should do. Unless, unless you're, you know, work day and you sell one copy inside, inside your entire system, if you're any sort of collaboration product, whether it's us or Slack or anything like that bottoms up with a motion at the top to help people consolidate is the way that it's going to go. Now, I do see some people make mistakes here and there are many companies that started like that. And what they discover is that when we add salespeople, we get great results. So we keep adding salespeople at every stage of the funnel. And eventually you get to the stage where every person who gets touched by a salesperson and it's death by a thousand cuts. And it makes sense on an ROI basis at every stage, but then eventually your website, you know, has contact us for a price and talk to a salesperson and you don't invest in the onboarding experience. And over time, I think that ends up being an issue. So we are very clear about who gets touched by a salesperson and who doesn't.

SPEAKER_22: Yeah. I mean, the total number of customers across all the products approximately, I had read somewhere you broke a quarter million. Yeah.

SPEAKER_27: We have 260,000 customers around the world. I think that's like pretty much every country and territory we can,

SPEAKER_00: we can sell to.

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SPEAKER_05: I just had Dharmesh from HubSpot on, and they committed to the midsize, the small enterprise, and they had to have the same discipline, which is the product had to be exceptional, and the product had to sell itself. And sure, yeah, if you're big enough, we could have a consultative sale later. But there's something about having to please a two-person or a 20-person organization that just makes you really efficient and sharp on products,

SPEAKER_20: I think so. Dharmesh is a great friend of mine and an incredible technologist, and also hats off to him

SPEAKER_00: for wanting to be the sort of technical person and not be the CEO. I think it's very difficult for people often to make that, but he realizes exactly what he's great at, which is building products and he's deep rolling his arms up in the AI side of things as well. And I think HubSpot, one of our employees is a board member over there, and they've learned a lot from our product-led growth model. And they're very similar, which is, yes, we can have a great product that sells itself. If you need to talk to us eventually at scale, we're here, but we win because a great product that sells itself. And I think that's really hard to disrupt, whereas there are many enterprise companies that are there because they've got a great sales team. But you can sell, I presume Salesforce is HubSpot's large competitor. There can be pockets of HubSpot in a Salesforce deployment. It's unlikely to be the reverse because of the way that the sales motion happens.

SPEAKER_05: That's fascinating. Yeah. I mean, it's just like hand-to-hand combat, like a much more guerrilla style. In a way,

SPEAKER_06: the product-led growth teams, like the ones at HubSpot, the ones at Atlassian, they're doing this like street level,

SPEAKER_05: winning over the actual customer who uses the product every day. And then you look at like the Oracles or Salesforce, you know, they might be doing like the, you know, going to the Warriors game or taking people out to dinner and using the sales and the CTO top-down sales. And it's going to result in something very different, as you're saying. Darmesh is obsessed with AI. Are you obsessed with it now too? And what impact is it having in the organization here as we move into this year one of ChatGPT language models and, you know, an actual platform starting to emerge that can be used by, you know, any business user can just use any number of these language models themselves and you get hugging face,

SPEAKER_81: throwing up new changes every day. It's got to be in your consciousness, huh?

SPEAKER_27: Yeah. And to anchor AI in the way I think about it, in technology,

SPEAKER_00: because it's so much of a winner-takes-all market, it usually takes some sort of technology shift to shuffle the playing board. And in those technology shifts, you find some companies that endure, you know, across multiple of them and some that stumble. And if you look back historically, you know, back to at least my lifetime, you had this sort of move to desktop software, which obviously, you know, Microsoft and Windows and Office were, you know, kind of the big beneficiaries of that. And then you had, you know, the sort of turn of 2000, you know, 1999, 2000, where you had the internet came along and you'd say, you know, Netscape, Netscape was, you know, the big winner there and Microsoft played catch-up, but it birthed, you know, companies like Google that wouldn't have existed previously. And then you sort of roll through to mobile and, you know, that birthed Apple really as a company. And, you know, in Google, you know, sort of with Android did a good job there, but Microsoft wasn't anywhere really to be seen. Then cloud came along, which is not so much a consumer product, but Microsoft, you know, caught up heavily with cloud and suddenly Amazon's, you know, in the race as well. And so you see these technology shifts where a couple of the big players maybe make the shift and a couple of the players don't make the shift. And I think AI is the next big technology shift that's going to shuffle the playing board of technology. And when I look at, you know, I've gone deep with all the different large language models and how they all work. In some ways, the industry has been saved by large language models because if you weren't deep in AI, you can basically rent a large language model from someone, which is very different, I think, to how most people thought this world would play out. And so there are a lot of companies who are really just playing, you know, catch up effectively by bringing these large language models who didn't have investment. So it really is different than most pundits would play it, thought it would. I think the real value is going to come from putting data together with these models because the large language models at the moment, I view them a bit like a Swiss army knife. They're expensive, they're not particularly good at any individual thing, but they do a lot of different things for you. And that's great, everyone's going to use them because they're the first thing available and I can pick up one of them and use it for lots of different use cases. I think over time there's going to be specialized models. You know, if you just want to do language transformation, which we do, we convert text to a query language. We don't need a multi-trillion parameter model to do that and we can have much faster and cheaper and even cheaper and faster are pretty much the same here and so we can actually have better user experience and save ourselves money. So over time, I think you can see specialization of particular niches or niches I think as it said in the US. Yeah, either of those

SPEAKER_85: are acceptable. We'll accept both of those as answers for niche or niche. You're allowed

SPEAKER_05: to say both,

SPEAKER_86: yeah. But that's, I think that's

SPEAKER_05: the correct answer is, you know, right now, the Swiss Army knife, I love the way you put that. I can go in there and ask it about travel or to write me a blog post or throw in some code and clean it up. Great, great Swiss Army knife. But if somebody makes a verticalized thing like, you know, the, you know, GitHub's copilot or Stack Overflow is working on one or somebody works on something just for finance or just for travel, of course, it's going to have a lot of features wrapped around it and a lot of verticalization and then reinforcement learning and it's going to blow away the general model. That's, that should be pretty obvious. I think it's pretty intuitive to think that's going to happen and those are going to start showing up in the next year probably, especially with all the open source projects. So you're in open source, a lot of your success is based on open source. So do you think the proprietary models like closed AI, previously known as open AI, is pursuing, what do you think is going to win? The open AI model where it's closed or the actual open source models? You know, I guess Facebook's Lambda is open source and other ones that are coming out. Which one's going to, which one's going to win the day?

SPEAKER_32: I don't think that for us where we sit in the ecosystem, it really matters

SPEAKER_00: if one or other people win the day because they're so interchangeable. You know, for me, it's an API call to use a large language model. And so, unlike saying, well, you know, how hard a choice was it to choose between Amazon or Azure or Google to host in the cloud? If I'm going to switch between one of those things and I've invested millions of dollars, you know, right into their APIs and working that way, the switching costs are very high. The switching costs, you know, for large language models are very low. And we've, at the moment, partnered with OpenAI because they're the best and we, you know, we've worked with them even on their contracts and how they store data and making sure they're much more, you know, B2B friendly. We think that we'll be probably using lots of models over time and the real value is going to come from putting data together and having those, you know, data use cases. And this is where I think the landscape is going to change a lot because if you're a very small point player at the moment, you do one very, very specific thing for customers, I think you're going to be at a relative disadvantage compared to, you know, the larger players out there that do multiple things because if you do multiple things, you have lots of data across, you know, the life cycle of that customer and that can mean your experiences can be way, way better than they could be initially. And so I do think there's going to be a bit of a, the big get bigger in this next phase of the internet. I'm not sure if that's good for everyone. I mean, it's great for us and I don't know how good it is for society, but I do think that the,

SPEAKER_44: you know, the use of data is going to be the big, big, big win here.

Chamath Palihapitiya: It does seem that you could switch these out really easy. I've been playing with it and you can

SPEAKER_05: very easily, you know, send your prompt engineering through one and then try it in the other, look at the response teams. I think there's going to be some meta layer here, kind of like CDNs or, you know, I guess some people with their cloud providers create, um, I've got, there's a, there's a term of art for it where you can have your, you know, jobs in the cloud go to different providers. You go to AWS for one thing, go to another and have that redone. Multi-cloud, yeah. So you can have like a multi-cloud thing. I could see people having like multiple, you know, uh, chat GPTs and just go to the language model that you think is best for this current

SPEAKER_72: job. Uh, and meta's model obviously is Lama. Google's is Lambda.

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SPEAKER_05: Yeah, it does seem like they're already getting commodified in some way and then whoever has the data is going to win the day. You have all this data on you know, I mean, that's another thing with a long tail of 260,000 customers. You've got a lot of data and

SPEAKER_06: you can provide a lot of speed efficiency if people are trying to manage tasks or clear out bugs or whatever they're doing in the software that you provide, you're going to be finishing their sentences and being their co-pilot. Any of those products released yet?

SPEAKER_00: something that is harder to change. There might be a better search engine but if I'm used to using Google every single day, am I going to try a vertical search engine for that one search to do something? Probably less likely. OpenAI has probably got the lightest consumer side of things. From a B2B sense, there will be a lot of providers. I think it's still open how the consumer side will play out. If I go back to Atlassian strengths, we have knowledge about how teams work and how particularly around engineering teams and development teams. We have information around what code gets written, what customer problems happened, what bug reports happened. I keep challenging my teams to not just improve the way our current customers do something, but really sit about the job to be done. Take an example like customer support. No customer wants a faster customer support experience. They have not had to reach out to customer support in the first place. If you take it to the example of an app on your phone, why don't we send all the log files and all the errors from that app on your phone every single night back to the developer. Previously, if there were minor errors in products, you just couldn't find the needle in the haystack and or fixing them would be too expensive. These days with AI, you can see, this little bug here, I can even see the code that creates that bug. To fix that bug is a trivial change. I can change the code and maybe it's a human gets reviewed it. Maybe it's a different large language model that has a whole two different sets of eyes reviewing that code and suddenly your code gets more robust and sent out based on real life data that comes out from the field. Instead of your customers having to file a bug report that actually never saw the bug in in customer experiences

SPEAKER_36: how far away do you think those will

SPEAKER_05: be we've had this parlor trick like incredible helping me write the blog post I make it shorter and make it funnier and hey it got 60% done 70% done I polish it wow this is crazy I need to I don't need to have a PR firm write a press release the AI wrote it for me and I just polished it so for a young startup why hire some PR firm if I

SPEAKER_00: years that we're working on things like that at the moment and to take a more knowledge work example for the listeners that don't write code if you go away for a long weekend you come back on a Tuesday and you like hey I want to catch up what did I over on Monday all collaborated on this document by the way here's at the end of the day here's the change from X to Y and I don't need to do that sure your time is like reading through or understanding what to read through is like a huge burden for

SPEAKER_16: most knowledge workers and that's the stuff we're working on at the moment

SPEAKER_05: that's absolutely brilliant and I'm having this experience we started recording every meeting we have at founders for funding then we zoom gives you the transcript so you kind of get that for free then we put it into Notion got AI built in and we said summarize it and so now I get these little summaries hey the investment team met with this person they talked to the founder about this the founder said this they're talking about a term sheet there's a liquidation preference I mean it's scary how accurate it is and it's saving me having to do that catch up it's like having Jarvis in Iron Man or that is invaluable that doesn't exist as a current product and I don't know why Slack doesn't do that right now Slack AI is just that is kind of MIA it would be incredible to open up my Slack and just have it tell me

SPEAKER_06: here's what's going on here's the changes that you missed and so it's that's a

SPEAKER_00: at the moment you're stringing multiple tools together you're saying okay let me do a Zoom meeting they get a Zoom transcript and throw it into you know Ocean or Confluence and get Confluence to summarize it and then I'll organize that in some way where I get to see the summaries in get summarized and for you to really understand a Slack conversation you need to understand the context who is this person what is their job what have been doing what are they written in Confluence like you know today what have them been doing in their coding and I way that is much more turnkey than you having to do it a bit at a time and so that's what I think someone like Slack might be able to do it

SPEAKER_05: you know you have these three this topic of this customer churning or threatening to churn here's ways in which we've saved customers before whatever issue that you've suddenly been faced with the AI could start giving you ideas of how to address that incoming issue how efficient have you gotten internally I know you guys did a small riff maybe 5% of the company or something during the 2022 period I they didn't see they saw things get more efficient obviously if you cut the bottom couple of people it's going to do that it's just a performance metric there on any team but today with AI in the enterprise do you see yourself having to add a ton of people or just making the decision hey how

SPEAKER_00: we're the largest company that's committed to remote work in the world we have about 11,000 employees and no one is required to come to an office any day you can work from home you can work from the office you can work from a cafe you can work from a trailer you know traveling around the United States if you wanted to and you we know how to save a customer or not and one way to learn in a sales call is to listen sit next to the person at a desk when they do the sales call but that's a whack-a-mole at the right place at the right time to hear someone slightly better if I look at using a saving of a customer from this particular competitor or this is the best pitch in this particular scenario or this vertical I'm selling to the healthcare space like here's the best person that pitched the healthcare space I think we capabilities and we're kind of the canary in the coal mine about how we're building out those experiences whether it's whiteboards in our confluence product and how do you make a digital whiteboard experience better than running into people or the summarization of data so you can catch up on people and what's happening that's not bumping into the water cooler so we put remote and AI together because we think the combination of those two is really changing how knowledge workers interact and so to back to your original question around how are we doing this internally we've got AI projects across the entire business and we think sales and customer touch will be heavily disrupted because I think there's a lot of busy work in many sales teams job in terms of communicating with customers but even just researching and understanding what a customer is doing with our products and we can surface that in incredible ways and so take an example of a sales person wants to upsell someone to an enterprise version of the product they can see we have all this data about what our products get used for and how they get used of course not looking at the customers private data but just like hey which features get used but previously all that stuff would have been too hard to look at on a feature basis but we

SPEAKER_05: doing that in real time that that's data that some team would work on a team of data scientists for three or four weeks for some offsite meeting every other year people would say this is amazing that quickly be outdated and it would be like institutional knowledge that doesn't exist anymore now it's going to be real time right so these assistants are going to be telling you in real time while you're on the phone call yeah you know this this type of customer has got these features that work best this customer is using two out of the three so maybe this third one they don't even know that maybe they need training on that one maybe they don't even know that product exists and we need to sell that into them do you worry about I mean it's kind of have a tremendous displacement effect on certain jobs so do you

SPEAKER_72: worry about that or do you think yeah you know it's overblown

SPEAKER_29: it's a couple things here

SPEAKER_00: one is that you know the initial technologies I did a lot of research around how electricity ran through and kind of changed the world in the 1800s and it's interesting if you go to New York you see these multi floor you know warehouses basically that have often been turned into loft apartments but you walk down you think okay this is the manufacturing district and it looks nothing like how we do manufacturing these days and it turns out the way it worked was back then you had a steam engine that was in the middle of these factories often on the second or third floor and effectively the steam engine would drive belts and pulleys to effectively have all these machines and you would bring your products up to the floors because it was really almost a sphere because you want to be as close to that steam engine as possible because the belts and pulleys would effectively lose momentum and slack and over time so you had to be as close to the center as possible and when electricity came in what they did is those steam engines used to explode and kill people and other things the factories would replace that steam engine with an electric engine in the middle of the same factory and the same floor with the same doors and pulleys and now it was great people didn't die but the jobs didn't really change you know there's less someone throwing coal into a steam engine but apart from that if you were a worker on the floor you didn't notice the Henry Ford production line it's like well actually let's move the product between the different tools as opposed to the reverse and that's sort of the second stage is where you start retooling how things get made and eventually then the third phase is of course electricity being embedded in all the products like and I guess you've probably seen that now with electric cars but you existing tools existing products existing processes slowly augmented we've still got the belts and pulleys to the same engine but it's a better way of doing things and that's what we're seeing right now and then over time you say okay well actually you have to reimagine what that looks like and you know that reimagining part that does change the jobs that are available but all the experience we've had in the past is that the jobs that are available exceed the new ones exceed the previous ones but there is a period of turmoil in between that period of turmoil can last a decade as things get jumbled up when I look at the industries to be affected I say well what's demand constrained and what's supply constrained and in software which what we sell to you know if we could have more software I think the open question is in sales is sales supply constrained or demand constrained if my sales people were twice as effective would I hire more of them or I have less of them and I think that is open in certain industries as to when we can make more effective do we need more of them or less of them things like accountants and back office things are

SPEAKER_05: constantly trying to now that we have our we both have like three decades of this and we watched the dot-com bus we watched the great recession and we watched multiple paradigms shift in our own lifetimes from mainframe computing mini computing desktop client server cloud we watched this so many times mobile that we even go back further and look for additional context the one I use you did electricity I did and I'll pull it up here because I think it's hilarious while was obsessed with that area in the warehouse I wound up living in a warehouse building on the west side of Manhattan on 26 and the west side highway 13 14 foot ceilings and it

SPEAKER_06: was made to have you know like steam engines and all kinds of stuff in it there was a 95 year period which here's the

SPEAKER_53: place and coming up with new ways to systematically harvest it and ship it and maintain it and there were a ton of people who would just drive around with horse and buggy in New York to bring ice to your refrigerator you got it dropped off every day and then boom overnight electricity and then boom the refrigeration unit and this is what but we didn't have a permanent unemployed class after phones

SPEAKER_05: went away and phone operators connecting calls went away we found new uses for human ingenuity that's what will happen here but the thing that I do find very interesting is every time I look at the job and I look at the job and I look at the job and I I find about 20 to 30% of each job could be automated away so and watching a portfolio of hundreds of companies I'm seeing the same thing happen you know three or four person startups don't add the fourth or fifth position they just you know they had the fourth but they don't at the fifth and sixth so the capital efficiency of these you know the most um uh what's the word you know dexterous the most scrappy companies they're looking to AI first and then solving their problem with AI and then going on I have a friend uh Brad Gerson who

SPEAKER_06: labs or something to make a marketing video now this is something that a marketing agency would have spent I don't know ten low tens of thousands or an individual contributor might have spent three or four thousand dollars building but when I talked to him about it I had encouraged him to do it himself write the script himself and then he took it to the next step

SPEAKER_05: the the big learning is well if you take some people out of the process it becomes more efficient to your point about when hip chat went from 10 to 25 it's actually more efficient if you can do the tools yourself all these creative things you know you weren't allowed to as a business executive explore

SPEAKER_06: your like you made your logo with AI they're like yeah and then I remember five or ten years ago maybe ten years ago people were using like you know they would use five or something they'd make their logo for 500 bucks 10 years before that when you were you know doing it last in the 2001 to 2010 period what

SPEAKER_00: made a lot better I think you know if we had all the AI back then and I think it's the creative class I think that when people ask me what advice do I give to kids about you learning how to think differently and so I do think there's a benefit of still acquiring knowledge not for knowledge sake but for getting great at learning and so then it comes down to can you bring multiple different disciplines together which is sort of creativity like can you create some new idea or something new to the world and that's the interesting part and so I do think there should be a renaissance in the way we teach kids to be blessed about rote learning and more about what are the ideas that haven't been thought up yet again I don't know if there's any traditional schools in

SPEAKER_05: all of those skills which it's very hard to teach those things become really defining listen you give me a bunch of time I just want to ask you one or two more questions which some great philanthropy work investing you you backed a lot of the like I think you LP a lot of the Australian funds from what I understand did a bunch of angel investing and stuff like

SPEAKER_53: that you ever think of

SPEAKER_00: we give Atlassian 1% of our equity 1% of our profit 1% of our product 1% of our employee time away and we did that for a long time and it's been great for us employees love it they joined for it it's been a huge boon for us and about a decade ago I looked around and realized we were still one of companies doing this and so I started a foundation called pledge 1% and the aim was to convince every company to do that same model and in that decade since we've got about 17,000 companies now have pledged to give 1% of product employee time product or profit away and so we're really starting this corporate philanthropy movement so I no matter what stage you're at it could just be the first day of your business it could

SPEAKER_20: be you've been running for 10 years you know pledge is a very

SPEAKER_00: about we've given away about 200 something thousand hours we've given away 100 something thousand licenses either free or discounted to communities or non-profits and you know we've given away I don't know 50 or 100 million dollars to charities over that time obviously it's still corpus of money to give away so be huge for us but I think it's eclipsed by what pledge one percent you on the next side of things what's next I still get inspired by a mission which is to unleash the potential of every team and the sort of archimedes said give me a lever long enough and a fulcrum on which to move it and I'll move the world and to the Australian Antarctic division and if we can make every team 50% 100% more effective that is going to change the world more than anything else I could do individually I could go start a space company or start any sort of huge entrepreneurial venture out there that's made a difference but the compound effect of helping 250,000 companies and for the world that's way bigger impact that I could have in almost any other domain and so that keeps me excited at the mission level and then as an entrepreneur we're 11,000 people two decades ago we were two people so every single year there's a different challenge and a different journey to go every day

SPEAKER_05: but it's really interesting to think about what it's like to manage 11,000 people you must meet people you're walking around on the weekend with your kids you must meet people who work for you you don't you never met it's gotta be surreal

SPEAKER_48: you do yeah when people wearing a Lassian shirt

SPEAKER_00: you know is around the streets or you know getting a selfie with your staff is a new one for me relatively recently in the last couple

SPEAKER_20: years and again it's just a realisation that you know across 11,000 people you can't

SPEAKER_00: have a one-to-one relationship with all of them but you can inspire them in fact one of my maxims is that the most important thing about leadership is to set a vision people people work for a complete asshole who has a great vision they won't work for the nicest person in the

SPEAKER_05: one of those cities

SPEAKER_143: that would be great

SPEAKER_05: yeah congrats on everything and we'll see you next time on this week in service

SPEAKER_39: bye bye