The Trump administration has effectively unwound the Biden era chip controls by selling the H200 to China; I agree with the decision, which is a return to longstanding U.S. policy.
An interview with MoffettNathanson's Michael Nathanson about Netflix's acquisition of Warner Bros. and the Hollywood end game.
Listen to this post : Warner Bros. started with distribution. Just after the turn of the century, Harry, Albert, Sam, and Jack Warner bought a second-hand projector and started showing short films in Ohio and Pennsylvania mining towns; in 1907 they bought their first permanent theater in New Castle, Pennsylvania. Around the same time the brothers also began distributing films to other theaters, and in 1908 began producing their own movies in California. In 1923 the brothers formally incorporated as Warner Bros. Pictures, Inc., becoming one of the five major Hollywood Studios. What the brothers realized early on was that distribution just wasn’t a very good business: you had to maintain the theater and find films to show, and your profit was capped by your capacity, which you had to work diligently to fill out; after all, every empty seat in a showing was potential revenue that disappeared forever. What was far more lucrative was making the films shown in those theaters: you could film a movie once and make money on it again and again. In this Hollywood was the tech industry before there was a tech industry, which is to say the studios were the industry that focused its investment on large-up-front costs that could be leveraged repeatedly to make money. Granted, Warner Bros., along with the rest of Hollywood, did come to own large theater chains as well as part of fully integrated companies, but when the Supreme Court, with 1948’s Paramount decrees, forced them to split, it was the theaters that got spun out: making content was simply a much better business than distributing it. That business only got better over time. First, television provided an expansive new licensing opportunity for films and eventually TV shows; not only were there more televisions than theaters, but they were accessible at all hours in the home. Then, home video added a new window: movies could not only make money in theaters and on TV, but there were entirely new opportunities to rent and sell recordings. The real bonanza, however, was the cable bundle: now, instead of needing to earn discrete revenue, the majority of Hollywood revenue became a de facto annuity, as 90% of households paid an ever increasing amount of money every month to have access to a universe of content they mostly didn’t watch. Netflix, which was founded in 1997, also started with distribution, specifically of DVDs-by-mail; the streaming service that the company is known for today launched in 2007, 100 years after the Warner brothers bought their theater. The differences were profound: because Netflix was on the Internet, it was available literally everywhere; there were no seats to clean or projectors to maintain, and every incremental customer was profit. More importantly, the number of potential customers was, at least in theory, the entire population of the world. That, in a nutshell, is why the Internet is different : you can, from day one, reach anyone, with zero marginal cost. Netflix did, over time, like Warner Bros. before them, backwards integrate into producing their own content. Unlike Warner Bros., however, that content production was and has always only ever been in service of Netflix’s distribution. What Netflix has understood — and what Hollywood, Warner Bros. included, was far too slow to realize — is that because of the Internet distribution is even more scalable than content. The specifics of this are not obvious; after all, content is scarce and exclusive, while everyone can access the Internet. However, it’s precisely because everyone can access the Internet that there is an abundance of content, far too much for anyone to consume; this gives power to Aggregators who sort that content on consumers’ behalf, delivering a satisfying user experience. Consumers flock to the Aggregator, which makes the Aggregator attractive to suppliers, giving them more content, which attracts more consumers, all in a virtuous cycle. Over time the largest Aggregators gain overwhelming advantages in customer acquisition costs and simply don’t churn users; that is the ultimate source of their economic power. This is the lesson Hollywood studios have painfully learned over the last decade. As Netflix grew — and importantly, had a far more desirable stock multiple despite making inferior content — Hollywood studios wanted in on the game, and the multiple, and they were confident they would win because they had the content. Content is king, right? Well, it was, in a world of distribution limited by physical constraints; on the Internet, customer acquisition and churn mitigation in a world of infinite alternatives matters more, and that’s the advantage Netflix had, and that advantage has only grown. On Friday, Netflix announced it was buying Warner Bros.; from the Wall Street Journal : Netflix has agreed to buy Warner Bros. for $72 billion after the entertainment company splits its studios and HBO Max streaming business from its cable networks, a deal that would reshape the entertainment and media industry. The cash-and-stock transaction was announced Friday after the two sides entered into exclusive negotiations for the media company known for Superman and the Harry Potter movies, as well as hit TV shows such as “Friends.” The offer is valued at $27.75 per Warner Discovery share and has an enterprise value of roughly $82.7 billion. Rival Paramount, which sought to buy the entire company, including Warner’s cable networks, bid $30 per share all-cash for Warner Discovery, according to people familiar with the matter. Paramount is weighing its next move, which could involve pivoting to other potential acquisitions, people familiar with its plans said. Paramount’s bid, it should be noted, was for the entire Warner Bros. Discovery business, including the TV and cable networks that will be split off next year; Netflix is only buying the Warner Bros. part. The Puck reported that the stub Netflix is leaving behind is being valued at $5/share, which would mean that Netflix outbid Paramount. And, it should be noted, that Paramount money wouldn’t be from the actual business, which is valued at a mere $14 billion; new owner David Ellison is the son of Oracle founder Larry Ellison, who is worth $275 billion. Netflix, meanwhile, is worth $425 billion and generated $9 billion in cash flow over the last year. Absent family money this wouldn’t be anywhere close to a fair fight. That’s exactly what you would expect given Netflix’s position — and the most optimistic scenario I painted back in 2016 : Much of this analysis about the impact of subscriber numbers, growth rates, and churn apply to any SaaS company, but for Netflix the stakes are higher: the company has the potential to be an Aggregator , with the dominance and profits that follow from such a position. To review: Netflix has acquired users through, among other things, a superior TV viewing experience. That customer base has given the company the ability to secure suppliers, which improve the attractiveness of the company’s offerings to users, which gives Netflix even more power over suppliers. The most bullish outcome in this scenario is Netflix as not simply another cable channel with a unique delivery method, but as the only TV you need with all of the market dominance over suppliers that entails. The most obvious way that this scenario might have developed is that Netflix ends up being the only buyer for Hollywood suppliers, thanks to their ability to pay more by virtue of having the most customers; that is the nature of the company’s relationship with Sony , which had the foresight (and lack of lost TV network revenue to compensate for) to avoid the streaming wars and simply sell its content to the highest bidder. There are three specific properties I think of, however, that might be examples of what convinced Netflix it was worth simply buying one of the biggest suppliers entirely: With regards to KPop Demon Hunters , I wrote in an Update : How much of the struggle for original animation comes from the fact that no one goes to see movies on a lark anymore? Simply making it to the silver screen used to be the biggest hurdle; now that the theater is a destination — something you have to explicitly choose to do, instead of do on a Friday night by default — you need to actually sell, and that favors IP the audience is already familiar with. In fact, this is the most ironic capstone to Netflix’s rise and the misguided chase by studios seeking to replicate their success: the latter thought that content mattered most, but in truth great content — and again, KPop Demon Hunters is legitimately good — needs distribution and “free” access in the most convenient way possible to prove its worth. To put it another way, KPop Demon Hunters is succeeding on its own merits, but those merits only ever had a chance to matter because they were accessible on the largest streaming service. In short, I think that Netflix executives have become convinced that simply licensing shows is leaving money on the table: if Netflix is uniquely able to make IP more valuable, then the obvious answer is to own the IP. If the process of acquiring said IP helps force the long overdue consolidation of Hollywood studios, and takes a rival streamer off the board (and denies content to another rival), all the better. There are certainly obvious risks, and the price is high, but the argument is plausible. That phrase — “takes a rival streamer off the board” — also raises regulatory questions, and no industry gets more scrutiny than the media in this regard. That is sure to be the case for Netflix; from Bloomberg : US President Donald Trump raised potential antitrust concerns around Netflix Inc.’s planned $72 billion acquisition of Warner Bros. Discovery Inc., noting that the market share of the combined entity may pose problems. Trump’s comments, made as he arrived at the Kennedy Center for an event on Sunday, may spur concerns regulators will oppose the coupling of the world’s dominant streaming service with a Hollywood icon. The company faces a lengthy Justice Department review of a deal that would reshape the entertainment industry. “Well, that’s got to go through a process, and we’ll see what happens,” Trump said when asked about the deal, confirming he met Netflix co-Chief Executive Officer Ted Sarandos recently. “But it is a big market share. It could be a problem.” It’s important to note that the President does not have final say in the matter: President Trump directed the DOJ to oppose AT&T’s acquisition of Time Warner, but the DOJ lost in federal court , much to AT&T’s detriment. Indeed, the irony of mergers and regulatory review is that is that the success of the latter is often inversely correlated to the wisdom of the former: the AT&T deal for Time Warner never made much sense, which is directly related to why it (correctly) was approved. It would have been economically destructive for AT&T to, say, limit Time Warner content to its networks, so suing over that theoretical possibility was ultimately unsuccessful. This deal is more interesting. The complaint, if there ends up being one, will, as is so often the case, come down to market definition. If the market is defined extremely narrowly as subscription streaming services, then Netflix will have a harder time; if the market is defined as TV viewing broadly, then Netflix has a good defense: that definition includes linear TV, YouTube, etc., where Netflix’s share is both much smaller and also (correctly) includes their biggest threat (YouTube). That YouTube is Netflix’s biggest threat speaks to a broader point: because of the Internet there is no scarcity in terms of access to customers; it’s not as if there are a limited number of Internet packets, as there once were a limited number of TV channels. Everything is available to everyone, which means the only scarce resource is people’s time and attention. If this were the market definition — which is the market all of these companies actually care about — then the list of competitors expands beyond TV and YouTube to include social media and user-generated content broadly: TikTok, to take an extreme example, really is a Netflix competitor for the only scarce resource that is left. Ultimately, however, I think that everything Netflix does has to be framed in the context of the aforementioned YouTube threat. YouTube has not only long surpassed Netflix in consumer time spent generally, but also TV time specifically, and has done so with content it has acquired for free. That is very difficult to compete with in the long run: YouTube will always have more new content than anyone else. The one big advantage professionally-produced content has, however, is that it tends to be more evergreen and have higher re-watchability. That’s where we come back to the library: implicit in Netflix making library content more valuable is that library content has longevity in a way that YouTube content does not. That, by extension, may speak to why Netflix has decided to initiate the Hollywood end game now: the real threat to Hollywood isn’t (just) that the Internet made distribution free, favoring the Aggregators; it’s that technology has made it possible for anyone to create content, and the threat isn’t theoretical: it’s winning in the market. Netflix may be feared by the town, but everyone in Hollywood should fear the fact that anyone can be a creator much more. In 2019, Netflix launched Formula 1: Drive to Survive , which has been a massive success. The biggest upside recipient of that series, however, has not been Netflix, but Formula 1 owner Liberty Media. In 2018 Liberty Media offered the U.S. TV rights to ESPN for free; seven years later Apple signed a deal to broadcast Formula 1 for $150 million a year. That upside was largely generated by Netflix, who captured none of it. In 2023, NBCUniversal licensed Suits to Netflix, and the show, long since stuck in the Peacock backwater, suddenly became the hottest thing in streaming. Netflix didn’t pay much, because the deal wasn’t exclusive, but it was suddenly apparent to everyone that Netflix had a unique ability to increase the value of library content. In 2025, KPop Demon Hunters became a global phenomenon, and it’s difficult to see that happening absent the Netflix algorithm. First, it is in part a vertical merger, wherein a distributor is acquiring a supplier, which is generally approved. However, it seems likely that Netflix will, over time, make Warner Bros. content, particularly its vast libraries, exclusive to Netflix, instead of selling it to other distributors. This will be economically destructive in the short term, but it very well may be outweighed by the aforementioned increase in value that Netflix can drive to established IP, giving Netflix more pricing power over time (which will increase regulatory scrutiny). Second, it is also in part a horizontal merger, because Netflix is acquiring a rival streaming service, and presumably taking it off the market. Horizontal mergers get much more scrutiny, because the explicit outcome is to reduce competition. The frustrating point for Netflix is that the company probably doesn’t weigh this point that heavily: it’s difficult to see HBO Max providing incremental customers to Netflix, as most HBO Max customers are also Netflix customers. Indeed, Netflix may argue that they will, at least in the short to medium term, be providing consumers benefit by giving them the same content for a price that is actually lower, since you’re only paying for one service (although again, the long-term goal would be to increase pricing power).
Welcome back to This Week in Stratechery! As a reminder, each week, every Friday, we’re sending out this overview of content in the Stratechery bundle; highlighted links are free for everyone . Additionally, you have complete control over what we send to you. If you don’t want to receive This Week in Stratechery emails (there is no podcast), please uncheck the box in your delivery settings . On that note, here were a few of our favorites this week. This week’s Stratechery video is on Robotaxis and Suburbia . What the Times Missed in Its David Sacks Story. On Sharp Text this week, I wrote about the commotion that ensued in tech and media after the New York Times profiled Trump Crypto and AI Czar, David Sacks, including an OpenAI-style outpouring of Sacks support, why the piece failed on its own terms, and an entirely different story that went unexplored. While the Times focused on the private interests that may benefit under Sacks’ watch, there are better questions about the public’s interest in leaning on someone like Sacks , and why the government might need Silicon Valley expertise as it confronts a variety of tech questions that have enormous implications for the future of the Western world. — Andrew Sharp Atlassian’s History and the Near Future. My favorite part of every Stratechery Interview is Ben’s “how did you get here?” question to first-time interview guests, and this week’s interview with Atlassian CEO Mike Cannon-Brookes is a terrific entry in the series. Come for the story of how a Qantas Frequent Flyer program eventually led to a $40 billion software business in Sydney, and stay for Cannon-Brookes on how his company is adapting to the AI era, as well as his take on “correct, but chronologically challenged” snake oil salesmen. Finally, as a rabid F1 fan, I’d be remiss if I didn’t recommend the end, where Cannon-Brookes expounds on Atlassian’s role sponsoring and helping to transform the once moribund Williams team (a story that can also be marketed to enterprises the world over). — AS Code Red at OpenAI. I have, for three years now — i.e. ever since ChatGPT took the world by storm in November 2022 — been convinced that we were witnessing the birth of the next great consumer tech company. Today, however, there are very legitimate reasons to be concerned that OpenAI is going to eventually succumb to the Google behemoth, just as Yahoo, Microsoft, Blackberry, and countless others have; I still want to believe that OpenAI can be an Aggregator, but they don’t have the business model to match, and that may be fatal. I summarized all of these feelings in this week’s episode of Sharp Tech , which covered both this week’s Article about OpenAI and Nvidia angst , and Tuesday’s Update about the bear case for OpenAI . — Ben Thompson Google, Nvidia, and OpenAI — OpenAI and Nvidia are both under threat from Google; I like OpenAI’s chances best, but they need an advertising model to beat Google as an Aggregator. OpenAI Code Red, AWS and Google Cloud Networking — OpenAI is declaring code red and doubling down on ChatGPT, highlighting the company’s bear case. Then, AWS makes it easier to run AI workloads on other clouds. AWS re:Invent, Agents for AWS, Nova Forge — AWS re:Invent sought to present AI solutions in the spirit of AWS’ original impact on startups; the real targets may be the startups from that era, not the current one. An Interview with Atlassian CEO Mike Cannon-Brookes About Atlassian and AI — An interview with Atlassian founder and CEO Mike Cannon-Brookes about building Atlassian and why he is optimistic about AI. The Forest the New York Times Missed Among the David Sacks Trees — The New York Times failed to support its David Sacks headline, and ignored better questions about the how U.S. devises modern tech policy. Google Looms Alan Dye Leaves Apple Let’s Break Down the 45nm Process Node A Quiet Chinese Mobile Giant in Africa Trump, Takaichi and a Game of Telephone; Japan Jawboning Continues; An Internet Governance Study Session; China Making Trade ‘Impossible’ Wolves and Cavs Concerns, The NBA Cup in Year 3, Questions on the Magic, Suns, Thunder and Raptors The Game of the Week, A Giannis Inc. Emergency Board Meeting, Chris Paul Gets Cut at 2 a.m. in Atlanta OpenAI Declares a ‘Code Red,’ Alan Dye Leaves Apple for Meta, Questions on Tranium 3, Substack, and F1
Good morning, This week’s Stratechery Interview is with Atlassian founder and CEO Mike Cannon-Brookes . Cannon-Brookes and Scott Farquhar — whom I interviewed in 2017 — founded Atlassian in 2002; their first product was Jira, a project and issue-tracking tool, followed by Confluence, a team collaboration platform. Atlassian, thanks in part to their location in Australia, pioneered several critical innovations, including downloadable software and a self-serve business model; over the ensuing two decades Atlassian has moved to the cloud and greatly expanded their offering, and is now leaning into AI. In this interview we discuss that entire journey, including Cannon-Brookes’ desire to not have a job, how the absence of venture capital shaped the company, and how the company’s go-to-market approach has evolved. We then dive into AI, including why Cannon-Brookes believes that there will be more developers doing more, and why Atlassian’s position in the enterprise lets them create compelling offerings. Finally we discuss Atlassian’s sponsorship of Williams, the F1 race team, and why Cannon-Brookes thinks they can both help Williams win and also accrue big benefits for Atlassian. To repeat a disclosure I have long made in my Ethics Statement , I did, in the earliest years of Stratechery, take on consulting work for a limited number of companies, including Atlassian. And, for what it’s worth, I’m also a huge F1 fan! Go Max. As a reminder, all Stratechery content, including interviews, is available as a podcast; click the link at the top of this email to add Stratechery to your podcast player. On to the Interview: This interview is lightly edited for content and clarity. Mike Cannon-Brooks, welcome to Stratechery. MCB: Thank you for having me, Ben. So this is admittedly a new experience for me, I’ve already interviewed the founder of Atlassian , but it wasn’t you. I’m of course referring to Scott [Farquhar] . That was eight years ago, actually, before I even had podcasts. It was very brief, but hey, like I said, new experiences. MCB: That’s true. That’s true. And you wrote a consulting paper for us in 2014! I was going to disclose, yes, in the very brief period where I did consulting work, you flew me down to Sydney for a week, I had a chance to learn a lot about Atlassian. And on a personal note, that consulting contract helped me a lot, that was when I was just starting. It’s funny how small the numbers seem in retrospect, but maybe that’s why I’ve shied away from writing about you too much over the years, because it meant a lot to me. So I appreciate it and there’s my disclosure for the interview. MCB: Thank you. It’s a good piece of work. Don’t forget, ironically, we started as a consulting and services business and then decided that software was a better business model, so I think you did the same thing. You went the scalability route instead of the consulting work via Sydney. Absolutely. I’m not doing anything that doesn’t scale anymore, but I did love visiting Sydney, so it was great. MCB: Still, we pulled out the old consulting paper you wrote for us in 2014. Why are we going to win, why are we going to lose, everything else, it was classic Ben work. Was it good? MCB: It’s pretty good! It’s interesting, I’d probably be embarrassed if I read it today. Anyhow, the good news is that since it’s the first time I’m interviewing you, I do get to do my favorite segment, which is learning more about you. Where did you grow up, but also, where were you born? I know they were different places. Then, how’d you get interested in technology and what’s your version of the Atlassian origin story? MCB: Sure, I feel like I’ve heard this question 1,000 times! Where to start? My dad was in banking, he joined the glorious institution that is Citibank today, from England. Parents are both from Cambridge and bounced around the world a lot as part of that job. Took the, “Hey, we need someone to go to this country”, and he was like, “I’ll take that”. So I was born in America, in a period I lived in New York. To be honest, lived there for three months before I moved to Taiwan. Really? Whoa. I didn’t know that. MCB: Yeah, in 1980 when it was very different than what it is today. Yeah. Were you saving that to drop that off me? I had no idea. I thought you went straight from America to Australia. MCB: I only just thought about it about 30 seconds ago, actually. No, I went to Taiwan for a few years, lived in Hong Kong for a few years, went to Australia for a few years. So how I got into technology is actually related because my parents were moving around so much, the logic was being English, that they would send us to English boarding schools and that would be a stable thing while they were moving once we got old enough. So at the mighty age of seven, I was put on Qantas and sent to England and back four times a year to go to boarding school in England for about five, six years. Because of that boarding school, I have one of the lowest frequent flyer numbers in Australia, they introduced the frequent flyer program and that was at the end of year one or end of year two. I get given this catalog by my parents and how you’ve earned all these points, “What do you want to buy?”, and it’s like, “I don’t know, trips, winery things, booze”, I’m flicking through this catalog and I’m like, “There’s literally nothing in this catalog”, of gear that you used to be able to get that I wanted and at the back is this computer, so I was like, “I guess I’ll get that”. The only thing that was potentially age appropriate. MCB: That was the only thing in the catalog, I didn’t want a toaster, I didn’t want wine, so that became my first computer, the mighty Amstrad PC20 . Four colors, no hard drive. Eventually, I bought an external floppy drive, so you could put in two and did buy magazines and type in programs and write games and stuff from magazines and play with it, played a lot of video games basically back in that era. I was into computers peripherally all through high school, came back to Australia at 12, my parents had settled here by then and weren’t moving, and so I came back here, did all high school and university here. In high school, I was always going to be an architect, that was my dream the entire way through, but come to the end of grade 12, applied for a bunch of scholarships, because university, applied for the scholarships, ended up getting one and so I thought, “Oh, well, maybe I’ll take that”, and it was in a course called BIT. Basically, half computer science, half finance and economics, but it was 15 grand a year, tax-free, so I was like, “Well, I’ll do that for a while and go back to the architecture thing”. Of course, famously in that scholarship, I met my first business partner of my first startup, met my second business partner of the second startup, they went in radically different directions in terms of outcome, but it was just 30 kids right at the right time, did the dot-com era thing. Now, ironically, as a part of that scholarship, you had to spend six months in three industrial placements, so the origin story of Atlassian comes from then a little bit, because those industrial placements were so boring. Scott spent six months installing Windows at a large corporate and he was crazy freaking smart and it was like, “Hey, go from computer to computer and upgrade to Windows 98”, or whatever it was. It was like, “Guys, this is our life, this is going to be horrible”. I worked for Nortel Bay Networks, which was a good, at the time, massive competitor, Cisco then completely disappeared and so a good tech lesson in and of itself, I basically cataloged the room full of networking gear and routers, it was mind-numbingly boring. So towards the end of the university course, I famously sent an email to a few people saying, “Look, I don’t really want to get a real job, why don’t we start a company and we’ll try some stuff?”. And this was after the dot-com era? This was the early 2000s? MCB: This was after the dot-com era, yeah. So I lived through the dot-com era actually as a journalist and writer, analyst and technology. I worked for a company called Internet.com, which became Jupiter Media and Jupiter Research and that was great, that was an amazing era for me. We ran events, newsletters, what would’ve been podcasts, didn’t have them back then. And we ran events on Mobile Monday, I think one of them was called and it was all about WAP and— Well, the real secret is you’re not the only one. There are some founders that are very successful, that they’re like, “Look, I just want to pontificate about technology”. MCB: A little bit like you, I remember getting in a lot of trouble from some of the startups, because some company would launch and I wrote basically 500 words on, “This thing’s never going to work, this is a disaster of an idea”, and they would ring up and yell at my boss and he was awesome, he’d be like, “Dude, just keep writing what you think”, and it didn’t make you very popular as a journalist type. Anyway, emailed some people, tried to start a business, we didn’t actually know what we were going to do. Atlassian has, I always tell people, a terrible origin story. You should not copy us. You just didn’t want to be installing Windows or upgrading software. MCB: We literally did not want to get a real job. And Scott replied and said, “Yeah, sure, I’m in for trying that”. He was one of the smartest kids in our class and his nickname is Skip, because he was the president of our student association and always a leader type and Eagle Scout and everything else, so we’re like, “Yeah, okay, let’s do that, we’re good mates” — and that started Atlassian. We picked the name in about five minutes, which if you consulted any branding company, would not have been chosen. Ironically, originally, we were going to do customer service and consulting, that was what the gig was. Hence the name, because Atlas was a Greek titan whose job was to stand on top of the Atlas Mountains and hold up the sky, that’s what he was supposed to be doing. He was a bad guy, so his punishment was to hold the sky up and we thought that was an act of legendary service, and so we were going to provide legendary service by holding up the sky for customers and as I said, did the service thing for about six months, decided that this is a terrible business. People paying us $350 US to answer their questions and didn’t scale and was at crazy hours of the morning and night and everything else. So in the meantime, we wrote the first version of what became Jira . We actually wrote three pieces of software, one was a knowledge basey type tool, one was a mail archiving tool for groups, so you could see each other’s email as a shared archiving. And were you seeing this and you were building tools for yourself, for your consulting business? MCB: Literally, yes, exactly. So all three were tools that we needed for ourselves. People would email us and I couldn’t see Scott’s email and he couldn’t see mine at the time and it was like this is silly, and we built Jira to handle questions and issues and problems that we were having ourselves that became a teeny bit popular. There was this glimmer that someone else cared, so we poured all the effort into that. What was that? What was the glimmer? Because this is when Agile is taking over software development and at least the legend is Jira and Agile go hand in hand, is that a correct characterization? MCB: A little bit, but this is actually pre-Agile. So Jira comes out before Agile is even a thing. I think it was about two or three years before we had any version of marketing or feature sets that involved Agile. This was just a web-based, at the time, a bug tracker. So the interesting evolution part of the company obviously is it started as a bug tracker for software developers, it became an issue tracker for technology teams and now it’s like a business workflow for tens of millions of people every day across the world, most of whom have nothing to do with technology, so it’s gone on its own evolution. Would anything have been different if this was the plan from the beginning, or did it have to be this organic, “We’re figuring it out as we go along as we’re running away from Windows installations”, sort of story? MCB: I think, look, obviously, if we could choose to follow in our own footsteps, the Back to the Future skeptic in me would say it’s gone pretty well, so I’d follow every single footstep I took. (laughing) Yep, totally. MCB: And that would’ve become the plan. But look, we had two hunches really, which both turned out to be radically correct. Now, I would say we were following waves or whatever else, but one was that the Internet would change software distribution, which sounds ridiculous now and when I talk to graduates nowadays, I have to put them in the right time and place and say, “Look, when we started, software was distributed on a CD”, BEA WebLogic was the bee’s knees and you used to have to get it on a CD if you were lucky. If not, someone would come and install it for you and that’s how software was distributed. We made that CD into a ZIP file and put it on the Internet for people to download. You didn’t access it like a SaaS application, you literally download it from our website. Right. It’s funny that when you first say that, it’s like, “Oh, it’s completely transformative”, well, but you were an on-premises software story. But actually, no, there’s several steps to getting to SaaS, one of which is just downloading software. MCB: And we had people call us before they would download to check that we were real and stuff and I’m like, “Why don’t you just download the damn ZIP file?”, and I also date them, because, well, maybe I’ll get to the business model part, but the second innovation was that we thought open source would change software costs. So we had this big hunch, we were both writing a bunch of open source code at the time. Open source was a massive movement, especially in the Java space. Embarrassingly, I actually wrote a book called Open Source Java Programming that you can find with some mates. It’s still on Amazon and we sold a few thousand copies, I think, but I swore I’d never write a book again, it was a very painful experience. Thank you, you’re validating my life decisions . MCB: Yeah. Open source did bring the cost of building software down radically. We were writing a very small layer, 5% of the code at best on top of masses of amazing open source libraries and we contributed to those libraries, but we could deliver an amazing experience for a very low cost. We learned a lot, pricing and packaging. So what was the implication of that hunch though? Just that the market for developers, that would subsequently mean there was more software? MCB: A little bit that was the implication of the hunch. Largely for us, it was that the cost was going down. Pre-open source, you had to write everything so if Jira was back then, I don’t know, a million lines of code, if you added all the open source libraries together, it was 25, 30, 40 million lines of code. It was so big that it was so expensive, because you had to write all of that. To think of Windows, they wrote everything, the networking stack, there were no libraries, there was no open source involved in the original versions, it was all written by Microsoft. So the cost of that was very high, then you had to charge a lot of money. So we thought, look, if we could take all these amazing open source libraries, contribute back to them — we were a great open source citizen — and build a piece of proprietary software on top of them that solved customer’s problems, we could deliver that really cheaply. In fact, we sold the original versions of Jira, they were $800, unlimited users, unlimited use with no lifespan. So it was just 800 bucks, one-time fee forever and we learned a lot about pricing and packaging firstly, but secondly, it was very simple. Our goal in the early days, we had to sell one copy a week to stay alive, that was it. Some weeks, we’d sell two copies. $1,600 US would roll in and we’d be like, “Cool, we got a week off to survive”, and then one copy a week became two and two became five and five became ten, and now it’s hundreds of thousands. Well, isn’t the thing you just didn’t want to have a job? So I love this part of the story, because when I started Stratechery, I had a job from Microsoft that made, I think, $104,000 or something like that. I’m like, “I just want to make that, because I don’t want to work for a corporation, so if I could just get to there, it’ll be great”. MCB: We had exactly the same sets of goals. We had a few things we wanted to make somewhere that we wanted to go to work. I wanted to get up every day and think, “I want to go to work”, and weirdly, almost 24 years later, I love coming to work, so a tick achieved. We wanted to make it so we didn’t have to wear a suit, neither of us really like wearing suits at all — in fact, it’s a bit of an allergic reaction often and so tick, don’t turn up to work in a suit every day. And thirdly, most of our friends, so this is right where IBM bought PwC ironically, so out of the 30-odd kids in our class, maybe 10 went to IBM as consultants and 10 went to PwC and then they all end up going to the same shop and their grad salary there was $47,600. So our goal for year one was to end the year making at least a grad salary and convince ourselves we’re not crazy kind of thing and we smashed that goal, so that was good, but that was there. The Internet, the distribution part is important, knowing your favorite topics. Tell me about that and along with the business model, because again, this goes back so far, I don’t think people appreciate the extent to this entire idea of self-serve or bottoms up selling. This is really where it all started. MCB: Yes. And look, a few things. Firstly, if you come from Australia, we’re an exporting nation. “We’re built on the sheep’s back”, is a phrase, Australia’s built on the sheep’s back. What that really means is because we were this colony originally, then country on the far side of the world, anything we did to make money largely had to leave the country and go somewhere else. Originally, that was a struggle to find a product that could do that. “Built on a sheep’s back” is because wool was the first product that could do that, you could put it on a wooden boat, because it wasn’t very heavy and you could ship it a long distance, because it kept really well, so we could make sheep’s wool and make money as a country by shipping it back to Europe and it could survive the journey and so the country was built on the sheep’s back. We are a massive exporting nation. Trump brings in his tariffs, we’re the only country with a negative rate of return, we have a positive trade relationship with America and we’re like, “Wait a second, why did we get taxed?”, so obviously, it’s rocks, technology, we build and export everything as a country that we do. So our mentality was like, “Well, if we’re going to make money, it’s going to be overseas”, that was the first thing, is, “Okay, it’s going to be somewhere else, it’s not going to be Australians buying our software”, and so the Internet allowed us to do this. We put up a shopfront, early website and people could come to our website, download our software and then we just needed a way to get paid for it. The problem was in order to do that and the trust barriers of the Internet, we had to have a very low price and we had to have a fully installable offering. So we spent so much time on making it installable, documentation, “How would you get yourself up and running and try it?” — the software, as we put it, had to sell itself. Our software had to be bought, not sold. We didn’t have any salespeople, we couldn’t travel to your office in Sweden or London and help you out with it. For $800, we couldn’t have done that and secondly, it didn’t make any sense. So the evolution was, “Okay, this is the only possible path that we can go down is we have to figure out how to get people to do this”, now it turns out once you have figured out how to do that, it’s an incredibly powerful motor because you have lots of people coming, you have a very cheap piece of software for its relative performance, and you get people using it in all these big businesses all over the place. I would say 50% of the customers I go meet nowadays, probably meet a handful of customers, a couple a day on an average kind of thing, many of those have been a customer for 20 years, 22 years, 23 years. How many customers have been a customer 23 years? I’m like that’s crazy, we’re only 24 years old. That’s awesome. MCB: And so they downloaded very early, they didn’t download as all of , all of them are customers. Just one guy who’s like, “I need a way to track my issues”. MCB: Exactly. It was some guy in a backroom who needed to track it. I know the Cisco origin story, that was literally a guy, he’s still there, he’s been there 22, 23 years, he’s awesome. And they started with just, “I just needed a way to manage my issues for 10 people”, and now it’s hundreds of thousands of people, seats that we have there, it’s kind of grown over time. How did we know that business model was working? Again, it dates us a lot, this didn’t mean we didn’t answer questions, we were big on customer service and helping people, email was the way to do that. A bit of IRC back then, we had a channel you could log into and we’d help you. But the first customer, we used to walk into the office in the morning and we had a fax machine with literally rolls of paper. So if you wanted to pay for this distributed software, this says how old, there was no SSL keys, I heard you complaining about it the other day, totally agree with that era. You had to download a PDF off our website, which was pretty modern that it was a PDF, fill in your credit card details, and fax it to us, that is how you paid when we started. So we would walk in the morning and there’d be these rolls of paper on the ground, you be like, “Ah, sweet, someone bought something”, you know what I mean? It became a weird dopamine drug for us. The very first company was American Airlines… MCB: About six months in that we came in the morning and there was a fax on the ground with $800 and a credit card number written on it and we had never talked to American Airlines, they had never emailed us, they had never asked for customer service, they’d never gone on IRC, they had never talked to us in any way, shape or form. Man, this thing could work, we just made $800 out of the air. MCB: I mean, there was a lot of pre-work to get them there, but obviously that was kind of different. MCB: Then secondarily, as you wrote, I’m just trying to finish a very long answer here, we started Confluence in 2004, and those two became the jewel engines and both of those I think were probably major moments. I often say Confluence is a bigger moment, actually. The business model was kind of established, this is two years into the business. We made, I think, $800 grand in year one, $1.6 million in year two, maybe $5 million in year three, and $12 million in year four, if I remember the revenue numbers. So the thing was working really well. You’re the company that’s the Microsoft heir in some respects, which is the really just you took venture eventually, but didn’t really need to, just pure bottoms up. You and Scott, we’re able to keep a huge portion of the company because of that, it’s an amazing story that is, I think, under-told in some respects. MCB: Yeah, well, we actually did. I mean, we did and didn’t. So the venture story is one of my favorites because it describes how we think from first principles. Firstly, the first capital we put on the balance sheet, institutional capital to put on the balance sheet, I guess you could argue our initial, I don’t know, $10 grand each was some money, but was in the IPO . So in 2015, when we went public, that was the first capital that went into the business all time. We took two rounds of funding, one in 2010 and one in 2013, but both of which were to employees, the first was to the founders and the second was to large number of employees who bought in so both of those companies bought ordinary stock. Secondary shares basically, yeah. MCB: They bought ordinary stock, there were no preferences, there were no anything, that was kind of the way it is. And we love the Accel guys that invested, it’s kind of funny because their business model was wildly wrong, we now have their original spreadsheets and stuff. We’ve 15 years in, you know them really, really well, they wanted us to grow it. I think we had to grow at 30% for two years, 20% the year after and something like that to double or triple their money and at the time they put in $60 mil US , that was the largest investment I think Accel had ever made in anything software, digital kind of world and it was this massive bet. It was a one-page term sheet for ordinary stock, so credit to those two partners who took massive risk on us, had to fight, we know that GC, everybody else to do this unusual funding round and I think we did 50% growth the first year, and our CAGR since then is probably 40%. Yeah, it worked out pretty well. MCB: They did very well. I think their 2-3x was more like a 300x or something. You mentioned the Confluence moment. Why was that a big deal? Usually the story is you have one product and you need to focus and you’re two years old, you’re launching a completely new product. Is that the aspect you’re referring to? MCB: Yes, I think it comes down to being bootstrapped. Look, we spent nine years convinced we were going to die every day, there was just such a mentality that this thing was all going to fall over and we better work harder and keep going. The Confluence moment was important because I remember, I don’t know exactly, but sometime around then we understood venture capital. Firstly, on the venture capital side, because they do relate to each other, there was no VC available in 2001 and 2002 in Australia. We’re a nuclear winter, we’re two idiots with no credibility. Right. You could barely get funded in San Francisco, you’re not going to get funding in Sydney. MCB: No, because 2001, you weren’t even finding San Francisco funding because the whole dot-com boom had just happened, no one was getting funded anyway. We’re in Australia and we have no credibility, so we didn’t even bother. We literally, 2010 when we went to the Accel thing and we talked to five VCs, was the first time we’d ever pitched the business. It was just not a thing, people don’t understand, we used to say we were customer-funded when people would ask the also awkward question of, “Who’s your funding come from?”, we were like, “We’re customer-funded”, They go, “Oh, okay”. Lifestyle business! MCB: But we did understand venture capital, massive readers, I have an army full of technical books, books about technology and the industry and history and stuff from that magic era of airport bookstores. We read every episode of Red Herring and Industry Standard and Wired Magazine, I have just this huge library, so voracious readers. One thing you understood about venture capital is they put the portfolio theory on their side — and I’m a big fan of venture capital, I should say, I’m the chair of Australia’s biggest VC fund and that’s my other mate that I met in university, Niki Scevak . But we wanted portfolio theory on our side, we’d done finance and economics, we had one product, this was highly risky if you’re bootstrapped. So there was a little bit of the thinking that actually if we have two products, our chances of total failure are less, one of them can fail and we’ll be okay and so we started a second product. Yes, arguably it was hard, but our first one was going all right, it was like making, I don’t know, five million bucks a year and we had a handful of really awesome backpacker programmers. And the early people, it’s like a whole total band of misfits that somehow made this thing work and we’re having a lot of fun, we’re working really hard and so we made another internal tool that became Confluence and being adjacent, but very different, selling to different audiences, but having a lot — if you bought one, there was a good reason to have the other one, no matter which way you started, became a really good symbiotic loop of these two engines that powered us for a very long time. So it was more a case of reducing our risk actually than anything else. Wasn’t it risky to be splitting your resources or did that not even occur to you? MCB: I don’t think it occurred to us, no. It was more about splitting our risk and we were doing pretty well, but it changed the business because we moved from being the Jira company to a software company, and I say that’s probably the most under-understood moment because we had to learn about not how to market Jira, but how to market software, not how to build Jira, but how to build software. So now we have 20, 25 apps in 5 different categories that sell to all sorts of different teams who own a business, but we had to become a software company. Microsoft, I don’t know the analogy’s really that fair to them, to be honest, or fair to us, it seems massively over-glamorizing what they’ve achieved, which is amazing, I’m huge fan of Microsoft. The need to understand how to sell, in their case, like Minecraft, SQL Server, Azure, AI, you have to understand the building, the creation of technology, the selling of technology, the marketing of technology at a generic level, it really helped us generify the business. I think if we’d gone too much longer, everybody would’ve been on the Jira team, it would’ve been too hard to start a second thing and instead, we’ve always been a multi-product company. You just mentioned selling a lot. When did you finally realize or transition away from just being self-serve to actually, “We’ve got to grow beyond this”? Was it almost like a pivot that came too late because your identity was so wrapped up into the, “We’re the self-serve company”? MCB: Look, it’s never been a pivot, I get asked this by investors all the time. I would say our go to-market model and our process has kept evolving pretty much every year or two for 20 years and I say evolving because we’re very aware of the strengths of the model that we came up with and we’re very aware of what it takes to power that and we’ve been very careful when we’ve evolved, changed, added to it, not to destroy the original one. So nowadays, we have two amazing business models where we call them high-touch and low-touch. So we have the low-touch model, which is literally the same thing as it’s always been, hundreds of thousands of people show up every week, they try our software, we want them to have a great experience trying the software, we want to spread it as widely as possible and as many enterprises as we can, and some of those will stick, some of those will get working and we measure aggressively the rates of return and dollars and flows and funnels and everything else. This whole team whose job is to make sure that that’s working at now massive scale, right. But at the same time, what happened is as customers got more and more Atlassian software deployed, they wanted a different relationship with us, they wanted a bigger relationship. Those days they used to be spending, as soon as we were spending $20 grand, we were like, “Oh man, maybe we should talk to these people”, nowadays it’s more like around $50 to $100 grand is when we’ll talk to you. So the lines kept moving for different reasons and we actually have online sales, inside sales in between actually, the sort of classical someone gets on an airplane and goes to travel to you. So it’s just kept evolving. We talk about the IPO a lot, it’s our 10-year anniversary coming up this month, I’m off to New York next week to ring the bell and celebrate 10 years. When we went public, as an example, we had less than 10 companies paying a million dollars a year, now we’re well north of 500 in 10 years. So that doesn’t come without an amazing enterprise sales team and teams that go out and help customers and customer success and all the trappings of a really top flight enterprise sales organization, because for most of those customers, again, I think it’s north of 85% of the Fortune 500 are deep Atlassian customers. We become a strategic partner to these businesses that if we go down, rockets don’t take off, banks shut down, it’s a real critical importance to most of these customers. How big is your business outside of directly working with developer teams? As I recall, this was part of the consulting thing was you were wanting to do Jira for sales or Jira for all these different sort of functions, where and how did that evolve? MCB: So it’s been a continuum for a long time. So nowadays, less than half of our users are in technology teams, and probably a third of those are developers, less than half of them. So a portion of our audience, it’s a very important point of words. When I talk about this, all the engineers are like, “Hey, you don’t care about us anymore”, I’m like, “No, that’s not true”, that business is a great business, it’s just the rest of our business has grown massively around it. There are not enough developers in the world for our business. Our fundamental value has always been actually, and it took us one of these things, it took a decade to realize, firstly, we don’t solve technology problems, we never have, we’ve never had anything that’s like, “I care what code you write, which language the code is in, what the code does”. We solve collaboration and people problems, we always have solved people problems, even Agile was a people problem. It’s not a technology problem, actually, it’s a people problem. It’s, “How do we organize a group of people to build a piece of technology that best meets the customer’s needs and goes off track as little as possible?”, that is a collaborative people problem, we’ve always solved people problems. Our value actually came because there’s a lot of tools for technology teams and we never wanted to be in the dev tools business, that’s a road of bones, it’s very hard to build sustainable competitive advantage and dev tools, the history shows this. There’s just a different company every few years, developers tastes are fickle, our developers taste are fickle, this is not me sledging developers at all, we have a massive R&D arm and that group changes languages every couple of years, they change how they build software every couple of years, they’re constantly moving on, they change our analytics tools and everything else because they are tool builders and toolmakers, that makes sense, but that’s a hard place to build a business. Interestingly topical today, so we’ll see. But the easier place to build a business in the long term was the level above that, which is the collaboration problems that came, which started as, “How do we get engineers, designers, product managers, business analysts to all be on the same page about what it is that they’re building and have a repeatable process for that?”. It turned out that as the world has become technology-driven, as we say, our customers are technology-driven organizations. If you’re a large organization for whom technology is your key distinct advantage, it doesn’t matter whether you’re making chips and databases or whether you’re making rockets or cars or whether you’re making financial services or insurance or healthcare, I would argue for most of the businesses that are great, technology is their key competitive advantage, then you should be our customer, that is it. And what we help you do is we help your technology teams and your business teams collaborate across that boundary because that’s actually the hardest boundary. Building great technology is one set of problems, making it work for your customers usually means in different industries, a different amount of working with all sorts of business people and that’s what Jira did from the very start. Now that’s what our whole portfolio in service management, in strategy and leadership teams is about doing that at different scales and different amounts in different places. Does it bug you when you get complaints on the Internet of, “Jira’s so complicated”, “Hard to use”, blah, blah, blah? And are you speaking to, the problem is that the problem space we’re working in is not the single developer trying to track an issue, it’s trying to herd a bunch of cats and get them the same direction and muddling through that is a lot more difficult than it seems. MCB: It bothers me anytime people don’t like our software, sure. We’ve worked for the last 20 years to make it better every day. We’ll probably work for the next 20 years to make it better every day and people will still probably be dissatisfied and that is our fundamental core design challenge. There’s a few reasons they say that. Firstly, the on-premise business model and the cloud shift is really important because with the cloud shift, we update the software, with the on-premise business model, we don’t, so you would often be on older data versions, customers would upgrade once a year or every two years or something, and so we can’t control that. Secondly, the challenge of Jira is at our core, we solve a whole lot of what we say is structured and unstructured workflows. Confluence is an unstructured workflow, Jira’s a very structured workflow. You have a set of steps, you have permissioning and restrictions, you have fields, you have what’s happening in this process. The auditor will do something and pass it to the internal accounting team, the accounting team will do this and pass it to legal, legal will do this and pass it to these people. You’re defining a workflow and you’re having information flow back and forth and a Jira work item is, as we call it, it’s a human reference to work. That’s the best description of what Jira is work in the knowledge work era is this very ephemeral concept. Back to your development example, is the code the software? Is the idea the software? Is the designs in Figma — these are all parts of what it is, this thing that’s called this virtual thing that we’ve built. What we track is with a human reference to that, so someone can say it’s a new admin console. Cool, here’s the design for the admin console, there’s the spec for the admin console, there’s the code for the admin console, here’s where it’s been tested, here’s where it’s deployed. Did customers like it? We need a reference to this thing that is otherwise spread across hundreds of systems and virtualized. Once you’re building a workflow system, companies, ours included, love process, we love workflows, we love control, and that control usually comes with more data. “Hey, don’t fill in these three fields, fill in these 50 fields”, and they’re all required for some reason and our job to customers is to say, “Do you really need 50 fields?”, because you’re creating a user experience- You’re ruining it for us! MCB: Your users are going to have to fill in all 50 fields, and it feels like that’s going to take you a while. We have customers — I went back and checked, I think almost every single person you’ve interviewed on your podcast is a customer of ours. I don’t know if it’s 100%, but it’s definitely north of 95% out of the last 20 guests. Stratechery is a customer of yours, so there you go. MCB: Oh, really? Well, there you go. Thank you. One of my engineers adores Jira, so I get the opposite angle from what I asked about. MCB: That’s right. So look, it’s a challenge for sure, but at the same time, man, the value we’ve created, the business value, the number of customers that run on it, it’s ironic, we talk about the AI era and all these other things. Literally, no chips go out of any of the chip companies you love talking about, every single one of them, soup to nuts. So at what point did you realize that AI was going to impact you in a major way? Was there an “aha” moment or it’s just been in the air? Or is it a specific time you realized, “Look, this is going to completely change what we do?” MCB: Again, I’m one of these — I’ve realized I’ve become the old man in the room. We’ve done machine learning for a long time in lots of ways because of our online business model, so I’d say we’ve done AI for a long time. Obviously, LLMs are what people refer to nowadays by AI and agents and these words that have corrupted the entire thing, the meaning changes in technology when it means something else. The launch of various versions of ChatGPT were very instructive obviously, they were a moment for everybody. The optimism, and I would say we’re massive AI optimists, it is the best thing that’s happened to our business in 25 years. Why? Because people might look at you from the outside and say you’re still characterized as — even though your business expanded far beyond developers — “Oh, you have a lot of developers”, I’m skipping over the transition to the cloud just because we’re running out of time, but it’s an interesting story. You did announce you are finally ending the on-premises software, which I’m curious, it is a sentimental moment to come to that decision, but people might look at you from the outside and say, “Oh, there’s a company that’s going to have a problem with AI, AI is going to replace developers, it’s the decreased seats . What are they going to do?” MCB: There’s a few ways to take that. I’m trying to put it on a tee for you. I think I know what you want to say. MCB: There’s a few ways to look at it. Firstly, I think AI is a good example where people are very concrete about the negatives and the positives are upside. I think it’s a huge force multiplier personally for human creativity, problem solving, all sorts of things, it’s a massive positive for society. That doesn’t mean there aren’t any negatives, but the net effect is really high. And we spend a lot of time, you hear it in the media talking about the job loss, the efficiency gains, whichever way you want to put it, that’s the thing. Well, that’s because it’s really concrete in a spreadsheet, “I can do this process with half as many people”, “Wow, look at that, that’s great”, what’s never written in the spreadsheet is all the new processes that get created, all the new ways of doing things, the quality of the output is going to be twice as high. If software costs half as much to write, I can either do it with half as many people, but core competitive forces, I would argue, in the economy mean I will need the same number of people, I would just need to do a better job of making higher quality technology. So our view on AI overall is an accelerant, not a replacement to everything we do, and just the next era of technology change is really positive. We’ve loved technology, we love the cloud, we love all the tech changes we’ve been through, mobile. Look, us as a business, we are in the game of knowledge work. We solve human problems, workflows, business processes, this is what we do. These largely revolve around text, or if it’s video nowadays, that can be reduced to text in various ways. LLMs allow us to understand that text in a massively deeper way than we ever have been, and the problems we solve aren’t going away. 20 years time, there’ll be groups of people trying to solve some sort of problem as a team and working on a project, and so these things aren’t going to go. They’re going to need to talk to each other and collaborate of what work’s going on and how it’s working, so the textual aspect of it has been amazing. The features we’ve been able to ship, we never could have built five years ago, it was literally impossible, so the ability to solve customer problems is so much higher than it ever has been. Secondly, our software is incredibly valuable at the core of these workflows, but it’s also incredibly promiscuous. What I mean by that is we have always been very highly interlinked with everything else. If it’s a sales team, there are links to Salesforce and customer records, there are links to internal systems, there are links to maybe features that need to be built, there are links to some content and document. So any Jira, Confluence, or Loom , you don’t record a Loom unless you’re talking about something, you don’t have a Jira issue without pointing to all sorts of different resources, whether that’s a GitHub or Figma, whether it’s Salesforce or Workday. That gives us a really unique knowledge, which we’ve turned into the teamwork graph, that actually started pre-AI, so the irony is the Teamwork Graph is about 6 years old. Well, it started with Confluence. This is the whole thing where you look backwards, and to your point, if you had just been the Jira company, but because from the very beginning, you mentioned Confluence was different but it was adjacent and you had to build the links and stuff together, and as you build all these different tools, because everyone wants to be this point of integration. And I wanted you to tell me about Rovo and this idea of being able to search across all your documents. Who gets permission to do that? It’s someone that’s already there, and you made the critical decision to be there back in 2004 or whatever it was. MCB: That’s true. Certainly back in 2004, and then in I think 2019, the Teamwork Graph starts, which is trying to take all of those links and turn them into a graph. The connectivity, two things linked to this Figma thing, five things linked to this customer record — okay, cool, that means something, so we built this Graph. To be honest, it was a bit of a technology lark. We have a lot of these projects that are really cool and we’re like, “We’ll be able to use this somehow and it’s going to grown”, and now it’s a hundred billion objects and connections connecting all of the company’s knowledge. It becomes the organizational memory nowadays and context and all these things nobody knew in 2019 that’s what it was going to be, it just seemed we needed it for various process connections. That turns out to be because it’s got permissions and compliance and all of the enterprise stuff built in, which is incredibly difficult, the best resource to point AI at in various forms. You still have to be good at the AI parts to get the knowledge, the context for any area, so the Teamwork Graph is our data layer. It’s not only the best kind of enterprise search engine for your content from a 10 Blue Links kind of way of thinking. If you’re chatting through your content, you still need all your organizational knowledge. I actually obviously found your Article, I was like, “Hey, what has Ben Thompson written about us last year?”, and I asked Rovo in chat and it comes back to me with he wrote this, that and the other and pulls out some snippets. I’m like, “Tell me more, do you think we’ve hit that?”, I literally got a report written by Rovo on your report as to whether it had been accurate. “Go look at the last 10 years with deep research and web search and come back and tell me, was he right or wrong?”, and it gave me a really interesting analysis of whether you were right and wrong. It’s like most AI things, it’s like 90% correct, it’s pretty good. It solved a lot of the first problem and I would not have done that work otherwise. I would have read it quickly and so I wasn’t going to put an analyst on it internally to do this work, but I could send something to do work I never would’ve done. Who’s your competitor for this spot, for this Rovo position where you have all this context, you can actually search your company in a way that just wasn’t possible previously? MCB: Who are the competitors you say? Yeah, because everyone is claiming they’re in this spot, “We can be the central place that you go and we have visibility everywhere”, why is Atlassian the one that’s going to win that space? MCB: A few reasons why we will. I think we have a great chance to be a great player is maybe the easiest way to say it. I think everybody loves this absolute win position, we don’t believe in enterprise technology, you usually get these absolute wins, it’s not quite the same as in the consumer world. We have a lot of business processes and workflows, millions every day that run through us, those are human collaboration workflows, so they are cool. The auditing team hands off to the accounting team, hands off to the tax team, whatever it is, sales workflows, marketing workflows, and they span lots of our applications and many others. If you’re going to go and introduce agents, these autonomous AI-driven software programs, whatever you want to call an agent, you’re going to put them into existing processes to make those processes either more efficient, more accurate. When the human picks up a task, it’s got all the information they need because something’s gone out to find it, that is an incredibly powerful position, which is why we support our agents and everybody else’s. You can assign a Jira work item to a Cursor agent in terms of code, you can assign it to a Salesforce agent. If you have your agent technology choice, I don’t think you’re going to have one agent platform, I think you’re probably going to have multiples, there are going to be a handful of organizational knowledge graphs that are powerful enough to solve these problems across multiple tools, but we have access to all those tools. We already know the information to some level, and that becomes a very unique advantage. Do you see this as a way to expand even further how much of a company you cover? You started with developers, then you expand to adjacent teams, and you talk about it’s now just a fraction of your user base. Do you own entire companies or could you get there? It’s like, “Okay, we still have these teams over here that are not on Jira, but Rovo’s so good that we need to bring everyone in”? MCB: Look, again, it would be great. I think it is unrealistic, and we should say “Absolutely”, right? MCB: If [Salesforce CEO Marc] Benioff was here, he’d be like, “Absolutely, we’ll own the world”, we love him, that’s the way he is, I don’t think about it as owning a customer. Our mentality has always been — I always use the subway analogy versus we have some competitors, for example, that want to be the control tower, their whole thing is we’ll be the control tower, just give us control and we’ll go and control everybody else, we’ll move the planes around. I think in enterprise IT, that’s an unrealistic view. Every CIO has been sold this for decades, it doesn’t happen because the world changes too quickly. Our philosophy and our commitment to customers has always been we will be a great citizen on all sides, we will interact with all of the applications you need, the old ones and the new ones, and we will be a valuable point of exchange in your business workflows and processes, whether those are structured like in Jira, whether unstructured like in Loom or Talent or something else. The reason for that is you have lots of systems. We want to be a valuable station on your subway network, we don’t want to be at the end of one of the lines, we want to be one of the handful of hub stations that are about moving trains around, and that is the best way to get your knowledge moving in your organization, it’s the best way to deal with your processes. Therefore, we need to have amazing AI capabilities. We have a massive investment in R&D, we have thousands of people working on AI tooling at the moment, and we have a huge creation bent, which is one of the reasons I think — we’ve talked a bit about the data advantage we have, I think we have a huge design advantage, and I actually think design is one of the hardest parts of building great AI experiences because it’s real fundamental design for the first time. You had a great line, you did a podcast a couple of weeks ago that I’ll put a link to, but you mentioned basically, the customer should not need to understand the difference between deterministic and probabilistic in the context of design, that’s what you’re driving at here. MCB: They should not need to understand that, they should need to understand when outcomes, outputs may be wrong or may be creative. Again, you talk a lot about the fact that hallucination is the other side of creativity, right, you can’t have one without the other. Hallucinations are a miracle. We have computers making stuff up! MCB: Our job is to explain to a customer when that happens, so it’s like this might be something you want to do, and that requires a lot of design. We have a feature in Jira called Work Breakdown which is super popular, where I can take a Jira issue and say, “Make me a bunch of sub-issues, this task has to be broken into a set of steps”. I don’t believe in the magic button theory of AI, that I’ll just hit a button and it’ll do all the things, I believe deeply in the value from AI will come from human-AI collaboration in a loop. It’s me and the AI working back and forth. You talk about yourself and Daman quite a lot , and it’s you, Daman and ChatGPT working together, but it’s not like you ask one thing and it’s done. It’s an interaction, it’s a collaboration back and forth, and that’s going to happen everywhere. In Work Breakdown, what it does is it says, “Hey, based on these types of documents I’ve gone to find from your whole graph in Google Docs and Confluence, whatever, I think this piece breaks down into these, is that correct?”, and it goes, “No, actually, that one doesn’t make any difference, these two are really good, you forgot about this document”, “Cool, let me go do that for you again”, and come back and say, “Is it these?”, “That’s closer”, and then you’re like, “That’s good enough, it’s 90% of what I need”, and then I go add the two that I need myself. That is a huge productivity boost but it’s not magically correct, and it requires a lot of design to tell people, “These are not the answers, these are possible answers, help us refine them and get better at it so that you get the 90% upside and the 10% downside is managed”. Are all these people pursuing these full agents that act on their own, are they just totally misguided? MCB: No, because I think, well, agents will take — there’s a snake oil sales thing going on as there always is in any bubble, and the snake oil sales is not wrong, it’s just chronologically challenged. (laughing) That’s so good. MCB: Well, customers are struggling. When I talk to customers every day, they’re like, “Is everyone else using these things to just magically transform their business with this simple, it took them five minutes and it’s replaced entire armies of people?”, and I’m like, “No, nobody’s doing that”. What they’re actually doing is taking business processes that are really important to their business and saying, “Okay, can I make this step better? This is highly error-prone. It’s compliance in a large organization, how do I make this part of the process better?”, and we’re like, “Oh, we can totally do that”, and they will replace small bits of lots of processes so that in Ship of Theseus style, five years from now, the process will look radically different. Occasionally, they are replacing entire processes, but this is the 1% case, what they’re actually doing is they have whole machines that are running and they’re trying to fix this cog and fix that cog, and that’s super valuable for them. That’s not a downside, that’s really, really valuable. And often, it’s work they didn’t want to do, work that wasn’t getting done, it wasn’t done at a high quality, so we got to remember that, I say this quite a lot, people shouldn’t be afraid of AI taking their job, I fundamentally believe this, they should be afraid of someone who’s really good at AI taking their job. That’s actually what’s going to happen, is someone is going to come along, in a sales sense, they’re really good at using all these AI tools to give better customer outcomes or handle more customers at one time. Is this why you’re hiring so many young people? MCB: Yes, I guess so. Yes, they’re more AI-native, they come out understanding these tools and technologies. I find the biggest irony in universities is all these people who “cheat” their way through every assignment, I use cheat in quote marks, using ChatGPT to handle these assignments, and then they’re worried AI is going to take all these jobs. I’m like, “Wait, you literally took your own job of writing the assignment, but you’ve also trained yourself on how to use these tools to get the outcome required” — now one might argue the university degree should be different, but just like when Google came along and you could look up any fact, knowing facts became far less important than the ability to look it up. I still think AI, it doesn’t create anything, maybe slightly controversial, but I argue it synthesizes information, it’s really good at processing huge amounts of information, giving it back to you, changing its form, bringing it back. Humans are still the only source of fundamental knowledge creation. I point out one of the flaws in the one person billion dollar company argument, and this will happen but it’ll be an anomaly. That company doesn’t get created without that one person, so there’s not AI creating companies magically. It’s like can a company eternally buy back its stock? No, because at some point, someone is going to own the final share? MCB: That’s right and I think this is missed, right? This is where we say it’s about unlocking creativity and what we do for our customers is put Rovo and these amazing data capabilities that we have alongside all the enterprise compliance and data residency, and there’s a massive amount of making this work in the enterprise with trust and probity and security. It’s very difficult. And great design to say, “What do you hire us to do? How do you get these technology and business teams to work together? What workflows do you have in your projects and your service teams, and how can we make those workflows better with more data and make your teams more informed?” That will end up with us having more share of employees in a business that use our stuff every day. Awesome. You made two big acquisitions recently, the DX acquisition , I think, makes a ton of sense to me measuring engineering productivity, particularly in the area of AI. What actual ROI are we getting on this? MCB: And how much money am I spending? Because I’m spending suddenly a lot of money, right? This is not cheap at all, I have huge bills. Internally, we use Rovo Dev , we use Claude Code, we use GitHub Copilot, we use Cursor, we have them available to all. We have a huge R&D — again, I think we’re still number one on the NASDAQ for R&D spending as proportion of revenue. You can take that as a good thing in the AI era or a bad thing, everyone gets to choose their own view on that, but we’ve always been incredibly high on R&D spending since day one. The bills that we pay though are very high, so DX is simply saying, “Okay, cool, how do I measure what I’m getting for that? Should I pay twice as much money because these bills are worthwhile, or is there a lot of it that’s actually just it’s really fun and it’s not actually leading to productivity gains?”. This is going to be a hard problem because there’s a lot of money on the line at the moment that people are paying for these tools, which is not without value, but measuring exactly what the value is is really, really hard, and that team’s done a phenomenal job. And we now have an Atlassian office in Salt Lake City, Utah, where I already spend a lot of time. Totally by coincidence, but it’s really nice. So that purchase, love it, makes a ton of sense. In perfect alignment with you. How does The Browser Company fit in? MCB: A lot of ways. So I have believed for a long time that browsers are broken. We’ve built browsers for an era of software that we don’t live in today. And I don’t, in my browser, have a bunch of tabs that represent webpages, I don’t have that. I have a bunch of tasks, I have a bunch of applications, I have a bunch of documents, and the browser was fundamentally never built to do that. That’s what Arc, first product from The Browser Company — if you don’t use Arc every single day, you should be, it’ll increase your productivity instantly because it’s built for knowledge workers and the way that they have to actually work every day and how they manage all of these tabs and tasks and flows versus serving the New York Times or whatever. That is a browser built for knowledge workers, and there’s a lot more we can do in that era as software changes. Secondly, obviously AI has come along, and we now have chats and applications as a extra part of the browser experience, so I think we can change how enterprises use browsers, security being a big issue. I think AI in the browser is a really important thing, but I suspect it’s not in the basic way of just combining Chrome and ChatGPT, that’s not how it’s going to play out. I suspect it requires a massive amount of design, which The Browser Company is phenomenal at, and it requires changing how people use their day-to-day applications. From our point of view, and I’ve been an Arc fan since day one, [The Browser Company CEO] Josh [Miller] and I have known each other a long time, there’s a knowledge worker angle and there’s obviously a business angle to it in a huge way that our customers are knowledge workers. We can change the way they do their work in a meaningful way of productivity, that is exactly what we have been trying to do in a lot of different ways. The browser itself, being chromium-based, Edge being chromium-based, Chrome being chromium-based, the rendering of webpages is not the problem, it is the fundamental user experience of, “How do I take all of my SaaS applications, my agents, my chats, my tabs, my knowledge, and put it all together in ways that make my day quicker?” — that is what we are trying to do fundamentally at the start. The context that we have is incredibly important for that. And the browser has, if you think about it, my personal memory. We used to call it the browser history. Great, it shows what I’ve seen, it does not have my organizational memory, which we have a great example of in the Teamwork Graph. So if I can put these things together, I can make a much more productive browsing experience for customers fundamentally in that world. I think we have an amazing shot of doing that and of changing how knowledge workers use SaaS. We’re not trying to make a browser, as I’ve said, for my kids, we’re not trying to make a browser for my parents, we’re not trying to make a browser for shopping or for anything else. We’re trying to make a browser for people who spend all day living in Salesforce and Jira and Google Docs and Confluence and Figma and GitHub, and that is their life. The laptop warrior that sits in that experience, I believe we can use AI and design to make that a far better experience and build an amazing product. They’re well on the way to doing that, we can supercharge doing it. You look skeptical. No, I’m looking at the clock, I skipped over a huge section. Your whole shift to the cloud, all those sorts of things. However, there is one thing I wanted to get to: you are wearing an Atlassian Williams Racing hat , I am a big F1 fan, I was very excited about you doing this . How did that come about? How was the first year? Was this another hunch this is going to work out? I mean, Williams is looking like a pretty good bet. MCB: Yes, our world’s largest sports bet. Look, how did it come about? So how do I make a short answer? F1 is changing, I think, in a massive way. I know now being incredibly deep in the business of it, the fundamental change is that hardware is becoming less important and software is becoming more important, this is a trend that we are used to. JV, James Vowles , the Team Principal, was the first person that approached us a long while ago now to help them, and for a teeny, teeny sticker in the corner, to help them get more productive as a team. What people don’t realize about F1 is these are large organizations, right? There’s 1100 people that work for Atlassian Williams Racing. And Williams was really pared down and skinny, he was brought back in with new owners to actually rebuild the entire thing? MCB: Yes, they were in deep trouble. But in rebuilding it, he is a software engineer, software developer by trade, by history kind of thing. He’s a technically-minded person. He downloaded Jira himself in 2004 to install it, so he knows us quite well. So we were brought on for our ability to help them with their teamwork and their collaboration, they really needed a technical upgrade to a whole lot of their systems. Turns out they need us in almost every part of their business because the service workflow’s important. We’re now in the garage, we’re using tons of AI to try to make them better, so there’s a lot of things we can do to build to hopefully help them win, and it’s a mission you can fall in love with. Here is one of the most storied brands in Formula 1 that’s fallen on tough times, every sportsperson loves a recovery story. And I was sold early on the recovery story, I’m like, “Fuck it, let’s go help, let’s make this happen. Let’s get back to being a championship team”. So we fell in love with the mission, and JV is super compelling, he’s got a one-decade goal, and they’re very goal-driven, and we love that, but they needed a lot of help, so that’s what they asked us for help with is initially. The more we looked at it, the more we learned about Formula 1, yes, it’s becoming a software-driven sport. So as an example, Atlassian Williams, I believe have twice as many software developers as the next team on the grid. Because it’s cost-capped, you got to choose, “Do I hire a software developer or an aerodynamicist?” — it’s a very clear cost cap, you’re choosing where to put your resources. As virtualization and everything get better, it’s less, “How well can I draw a curve?” and, “How much can I help 1100 people work together, and how can we build great software”, which really is the core of the car, right? So that then comes to us, tiny sticker, probably a founder-ish moment where I’m like, “How much is the sticker on the top?”, and they didn’t have a sticker on the top and I’m like, well, “What would that get us?” So we ran the numbers on that and the reason is twofold. You talked about our GTM, our go-to-market transformation, we have an ability to build various things. Firstly, branding is obviously massive, top three teams get 10 times the branding as the bottom three teams. So if you’re going to make a sports bet, you pay for a long period of time with the bottom three team, you help make them a top three team, and your sport bet pays out really well just on a sheer TV time and etc — the number of staff, parents, and other things, have said to staff members, “Hey, that company you work for, it’s really great, I saw them on the TV on the weekend”, and the staff member will say, “Dude, I’ve worked there for 12 years, why do you suddenly know about it?”, “Oh, I saw them driving. Carlos [Sainz Jr.] is great”, or something. And he is! So obviously, there’s a huge marketing and branding angle that’s about their position being better. The really interesting part of what we’re doing there is we have customers all around the world, we have customers in 200-odd countries, and we can’t go and visit all of our biggest customers in a meaningful way. We certainly can’t take them to some of our best and most exciting customers, right? There are electric car companies that use our stuff that we’d love to take many customers to a factory, or rockets, or whoever, I can’t take many customers into some of your favorite chip companies and say, “Look how they use our stuff”, I can maybe get one or two customers a year into that customer and show them how they use our things. With Formula 1, what we’re building is a mobile EBC, so an executive briefing center. Formula 1 goes around the world. It goes to Melbourne, it goes to Singapore, it goes to Japan, it goes to England, it goes to various parts of Northern Europe, it goes to various parts of America and you’re like, “Hey, where are our customers?” — roughly distributed like that. It comes to town, we can invite a whole lot of customers into a great experience, we can tell them a lot about Atlassian software, we can also invite them into one of our best customers. They can sit in the garage, and I can tell them how our service collection is helping power the assets, that when that wing’s broken, it gets known here, and they start making a new one back in the factory in Oxford, and this one gets shipped around the world and another one will get moved. And, “Here, I can show you the asset management and the service that goes along with it, I can show you how the garage is getting more efficient because of us, I can show you how we’re helping them win races”. We don’t drive cars, we help them be more productive as a team and I can do that in an environment of it’s an exciting environment. They can drink a great latte or a champagne or whatever they want, and I can explain to them how we are transforming this business in a meaningful way with our tools no matter which way they want to look at it, which is the most powerful customer story that you can go and tell a couple-hundred customers a year in their city. We come to their city, right? I was in Montreal, I took a whole bunch of Canadian customers over the three days, they were like, “This changes my view of Atlassian”, and I’m like, “That’s exactly our goal”, that is at the enterprise end of enterprise sales though, right? But that’s the ironic thing, it’s as far away from where you started as you could be. MCB: Well, they didn’t get there. I met two Canadian banks we had in Montreal as an example, both of whom had been customers for over 20 years, they started spending $800 bucks or maybe $4800 as we moved our pricing to around five grand — now they spend a million, two million dollars a year, and they could be spending ten. We have the ability to give the massive business value across a far larger swath of their business. And I can say, “What do you use from our system of work today? What could you use? Let me show you how Williams uses that piece of the system of work”, which is just a very visceral and exciting customer example to show them how they’re winning. And it helps, again, culturally, super aligned. They’re an awesome group of people trying really hard to win in the most ridiculously competitive sport and the highs are highs, the lows are low. Any sporting fan, you’re well familiar with various different sports that we have in common, but this is technology built by a large business team that has to win a sport. That doesn’t happen anywhere else in the sporting world, I would claim. Giannis [Antetokounmpo] doesn’t make his own shoes and have a team of people making better shoes and a better basketball so he can win, that doesn’t happen in other sports. It’s all about the people on the floor in an NBA game as to who wins, and that’s great, don’t get me wrong, I love basketball. The work in Formula 1 is done by 1000 people back in Oxford. It’s a Constructor Championship . MCB: The constructor championship I do think should be more important, especially given the current exact week we’re in, which is an amazing week for Atlassian Williams Racing, second podium . You talk about that bet, I told JV at the start of the year, I thought that he’s like, “What do you think our five-year future is?”, and I said, “Look, I think, number one, we’ll get one podium this year, 2025; 2026, we’ll win a race; and by 2030, we will have won a championship, that is my OKRs [Objectives and Key Results]”, and he said, “Oh, wow, okay, yeah I think so”. It lines up, I know the team OKRs and other things. And we won two podiums this year, so I was wrong, and I think we have a great chance for 2026, and we are working hard to make the team better and the single-best customer example we have of every piece of software that we sell. Mike, I’d love to talk again. It was great talking to you again. And, hey, good luck. And I’m a Williams fan, so I’ll be cheering for you this weekend. MCB: Oh, yeah. Well, I’m not sure this weekend, but 2026, 2027- Okay. I’m kind of kissing up, I am dying for Max [Verstappen] to win is the honest truth. I need the McLarens to run into each other . But other than that, Williams is my second love. MCB: Do you think McLaren will issue team orders to switch them if Oscar is in second and Lando’s in fourth? Yes. And I don’t know what’s going to happen if that happens, and this will be fascinating. MCB: We will have to see. It’s going to be a huge week. But that’s what makes the sport exciting, right? The whole thing is amazing. Talk to you later. MCB: All right. Thanks, man. This Daily Update Interview is also available as a podcast. To receive it in your podcast player, visit Stratechery . The Daily Update is intended for a single recipient, but occasional forwarding is totally fine! If you would like to order multiple subscriptions for your team with a group discount (minimum 5), please contact me directly. Thanks for being a supporter, and have a great day!
AWS re:Invent sought to present AI solutions in the spirit of AWS' original impact on startups; the real targets may be the startups from that era, not the current one.
OpenAI is declaring code red and doubling down on ChatGPT, highlighting the company's bear case. Then, AWS makes it easier to run AI workloads on other clouds.
Listen to this post : A common explanation as to why Star Wars was such a hit, and continues to resonate nearly half a century on from its release, is that it is a nearly perfect representation of the hero’s journey. You have Luke, bored on Tatooine, called to adventure by a mysterious message borne by R2-D2, that he initially refuses; a mentor in Obi-Wan Kenobi leads him across the threshold of leaving Tatooine and facing tests while finding new enemies and allies. He enters the cave — the Death Star — escapes after the ordeal of Obi-Wan’s death, and carries the battle station’s plans to the rebels while preparing for the road back to the Death Star. He trusts the force in his final test and returns transformed. And, when you zoom out to the entire original trilogy, it’s simply an expanded version of the story: this time, however, the ordeal is the entire second movie: the Empire Strikes Back. The heroes of the AI story over the last three years have been two companies: OpenAI and Nvidia. The first is a startup called, with the release of ChatGPT, to be the next great consumer tech company ; the other was best known as a gaming chip company characterized by boom-and-bust cycles driven by their visionary and endlessly optimistic founder, transformed into the most essential infrastructure provider for the AI revolution. Over the last two weeks, however, both have entered the cave and are facing their greatest ordeal: the Google empire is very much striking back. The first Google blow was Gemini 3, which scored better than OpenAI’s state of the art model on a host of benchmarks (even if actual real-world usage was a bit more uneven). Gemini 3’s biggest advantage is its sheer size and the vast amount of compute that went into creating it; this is notable because OpenAI has had difficulty creating the next generation of models beyond the GPT-4 level of size and complexity. What has carried the company is a genuine breakthrough in reasoning that produces better results in many cases, but at the cost of time and money. Gemini 3’s success seemed like good news for Nvidia, who I listed as a winner from the release : This is maybe the most interesting one. Nvidia, which reports earnings later today, is on one hand a loser, because the best model in the world was not trained on their chips, proving once and for all that it is possible to be competitive without paying Nvidia’s premiums. On the other hand, there are two reasons for Nvidia optimism. The first is that everyone needs to respond to Gemini, and they need to respond now, not at some future date when their chips are good enough. Google started its work on TPUs a decade ago; everyone else is better off sticking with Nvidia, at least if they want to catch up. Secondly, and relatedly, Gemini re-affirms that the most important factor in catching up — or moving ahead — is more compute. This analysis, however, missed one important point: what if Google sold its TPUs as an alternative to Nvidia? That’s exactly what the search giant is doing, first with a deal with Anthropic, then a rumored deal with Meta, and third with the second wave of neoclouds, many of which started as crypto miners and are leveraging their access to power to move into AI. Suddenly it is Nvidia that is in the crosshairs, with fresh questions about their long term growth, particularly at their sky-high margins, if there were in fact a legitimate competitor to their chips . This does, needless to say, raise the pressure on OpenAI’s next pre-training, run on Nvidia’s Blackwell chips: the base model still matters, and OpenAI needs a better one, and Nvidia needs evidence one can be created on their chips. What is interesting to consider is which company is more at risk from Google, and why? On one hand Nvidia is making tons of money, and if Blackwell is good, Vera Rubin promises to be even better; moreover, while Meta might be a natural Google partner , the other hyperscalers are not. OpenAI, meanwhile, is losing more money than ever, and is spread thinner than ever, even as the startup agrees to buy ever more compute with revenue that doesn’t yet exist. And yet, despite all that — and while still being quite bullish on Nvidia — I still like OpenAI’s chances more. Indeed, if anything my biggest concern is that I seem to like OpenAI’s chances better than OpenAI itself. If you go back a year or two, you might make the case that Nvidia had three moats relative to TPUs: superior performance, significantly more flexibility due to GPUs being more general purpose than TPUs, and CUDA and the associated developer ecosystem surrounding it. OpenAI, meanwhile, had the best model, extensive usage of their API, and the massive number of consumers using ChatGPT. The question, then, is what happens if the first differentiator for each company goes away? That, in a nutshell, is the question that has been raised over the last two weeks: does Nvidia preserve its advantages if TPUs are as good as GPUs, and is OpenAI viable in the long run if they don’t have the unquestioned best model? Nvidia’s flexibility advantage is a real thing; it’s not an accident that the fungibility of GPUs across workloads was focused on as a justification for increased capital expenditures by both Microsoft and Meta. TPUs are more specialized at the hardware level, and more difficult to program for at the software level; to that end, to the extent that customers care about flexibility, then Nvidia remains the obvious choice. CUDA, meanwhile, has long been a critical source of Nvidia lock-in, both because of the low level access it gives developers, and also because there is a developer network effect: you’re just more likely to be able to hire low level engineers if your stack is on Nvidia. The challenge for Nvidia, however, is that the “big company” effect could play out with CUDA in the opposite way to the flexibility argument. While big companies like the hyperscalers have the diversity of workloads to benefit from the flexibility of GPUs, they also have the wherewithal to build an alternative software stack. That they did not do so for a long time is a function of it simply not being worth the time and trouble; when capital expenditure plans reach the hundreds of billions of dollars, however what is “worth” the time and trouble changes. A useful analogy here is the rise of AMD in the datacenter. That rise has not occurred in on-premises installations or the government, which is still dominated by Intel; rather, large hyperscalers found it worth their time and effort to rewrite extremely low level software to be truly agnostic between AMD and Intel, allowing the former’s lead in performance to win the battle. In this case, the challenge Nvidia faces is that its market is a relatively small number of highly concentrated customers, with the resources — mostly as yet unutilized — to break down the CUDA wall, as they already did in terms of Intel’s differentiation. It’s clear that Nvidia has been concerned about this for a long time; this is from Nvidia Waves and Moats , written at the absolute top of the Nvidia hype cycle after the 2024 introduction of Blackwell: This takes this Article full circle: in the before-times, i.e. before the release of ChatGPT, Nvidia was building quite the (free) software moat around its GPUs; the challenge is that it wasn’t entirely clear who was going to use all of that software. Today, meanwhile, the use cases for those GPUs is very clear, and those use cases are happening at a much higher level than CUDA frameworks (i.e. on top of models); that, combined with the massive incentives towards finding cheaper alternatives to Nvidia, means both the pressure to and the possibility of escaping CUDA is higher than it has ever been (even if it is still distant for lower level work, particularly when it comes to training). Nvidia has already started responding: I think that one way to understand DGX Cloud is that it is Nvidia’s attempt to capture the same market that is still buying Intel server chips in a world where AMD chips are better (because they already standardized on them); NIM’s are another attempt to build lock-in. In the meantime, though, it remains noteworthy that Nvidia appears to not be taking as much margin with Blackwell as many may have expected; the question as to whether they will have to give back more in future generations will depend on not just their chips’ performance, but also on re-digging a software moat increasingly threatened by the very wave that made GTC such a spectacle. Blackwell margins are doing just fine, I should note, as they should be in a world where everyone is starved for compute. Indeed, that may make this entire debate somewhat pointless: implicit in the assumption that TPUs might take share from GPUs is that for one to win the other must lose; the real decision maker may be TSMC, which makes both chips, and is positioned to be the real brake on the AI bubble . ChatGPT, in contrast to Nvidia, sells into two much larger markets. The first is developers using their API, and — according to OpenAI, anyways — this market is much stickier and reticent to change. Which makes sense: developers using a particular model’s API are seeking to make a good product, and while everyone talks about the importance of avoiding lock-in, most companies are going to see more gains from building on and expanding from what they already know, and for a lot of companies that is OpenAI. Winning business one app by one will be a lot harder for Google than simply making a spreadsheet presentation to the top of a company about upfront costs and total cost of ownership. Still, API costs will matter, and here Google almost certainly has a structural advantage. The biggest market of all, however, is consumer, Google’s bread-and-butter. What makes Google so dominant in search, impervious to both competition and regulation, is that billions of consumers choose to use Google every day — multiple times a day, in fact. Yes, Google helps this process along with its payments to its friends , but that’s downstream from its control of demand, not the driver . What is paradoxical to many about this reality is that the seeming fragility of Google’s position — competition really is a click away! — is in fact its source of strength. From United States v. Google : Increased digitization leads to increased centralization (the opposite of what many originally assumed about the Internet). It also provides a lot of consumer benefit — again, Aggregators win by building ever better products for consumers — which is why Aggregators are broadly popular in a way that traditional monopolists are not. Unfortunately, too many antitrust-focused critiques of tech have missed this essential difference… There is certainly an argument to be made that Google, not only in Shopping but also in verticals like local search, is choking off the websites on which Search relies by increasingly offering its own results. At the same time, there is absolutely nothing stopping customers from visiting those websites directly, or downloading their apps, bypassing Google completely. That consumers choose not to is not because Google is somehow restricting them — that is impossible! — but because they don’t want to. Is it really the purview of regulators to correct consumer choices willingly made? Not only is that answer “no” for philosophical reasons, it should be “no” for pragmatic reasons, as the ongoing Google Shopping saga in Europe demonstrates. As I noted last December , the European Commission keeps changing its mind about remedies in that case, not because Google is being impertinent, but because seeking to undo an Aggregator by changing consumer preferences is like pushing on a string. The CEO of a hyperscaler can issue a decree to work around CUDA; an app developer can decide that Google’s cost structure is worth the pain of changing the model undergirding their app; changing the habits of 800 million+ people who use ChatGPT every week, however, is a battle that can only be fought individual by individual. This is ChatGPT’s true difference from Nvidia in their fight against Google. This is, I think, a broader point: the naive approach to moats focuses on the cost of switching; in fact, however, the more important correlation to the strength of a moat is the number of unique purchasers/users. This is certainly one of the simpler charts I’ve made, but it’s not the first in the moat genre; in 2018’s The Moat Map I argued that you could map large tech companies across two spectrums. First, the degree of supplier differentiation: Second, the extent to which a company’s network effects were externalized: Putting this together gave you the Moat Map: What you see in the upper right are platforms; the lower left are Aggregators. Platforms like the App Store enable differentiated suppliers, which lets them profitably take a cut of purchases driven by those differentiated suppliers; Aggregators, meanwhile, have totally commoditized their suppliers, but have done so in the service of maximizing attention, which they can monetize through advertising. It’s the bottom left that I’m describing with the simplistic graph above: the way to commoditize suppliers and internalize network effects is by having a huge number of unique users. And, by extension, the best way to monetize that user base — and to achieve a massive user base in the first place — is through advertising. It’s so obvious the bottom left is where ChatGPT sits. At one point it didn’t seem possible to commoditize content more than Google or Facebook did, but that’s exactly what LLMs do: the answers are a statistical synthesis of all of the knowledge the model makers can get their hands on, and are completely unique to every individual; at the same time, every individual user’s usage should, at least in theory, make the model better over time. It follows, then, that ChatGPT should obviously have an advertising model. This isn’t just a function of needing to make money: advertising would make ChatGPT a better product. It would have more users using it more, providing more feedback; capturing purchase signals — not from affiliate links, but from personalized ads — would create a richer understanding of individual users, enabling better responses. And, as an added bonus — and one that is very pertinent to this Article — it would dramatically deepen OpenAI’s moat. It’s not out of the question that Google can win the fight for consumer attention. The company has a clear lead in image and video generation, which is one reason why I wrote about The YouTube Tip of the Google Spear : In short, while everyone immediately saw how AI could be disruptive to Search , AI is very much a sustaining innovation for YouTube: it increases the amount of compelling content in absolute terms, and it does so with better margins, at least in the long run. Here’s the million billion trillion dollar question: what is going to matter more in the long run, text or video? Sure, Google would like to dominate everything, but if it had to choose, is it better to dominate video or dominate text? The history of social networking that I documented above suggests that video is, in the long run, much more compelling to many more people. To put it another way, the things that people in tech and media are interested in has not historically been aligned with what actually makes for the largest service or makes the most money: people like me, or those reading me, care about text and ideas; the services that matter specialize in videos and entertainment, and to the extent that AI matters for the latter YouTube is primed to be the biggest winner, even as the same people who couldn’t understand why Twitter didn’t measure up to Facebook go ga-ga over text generation and coding capabilities. Google is also obviously capable of monetizing users, even if they haven’t turned on ads in Gemini yet (although they have in AI Overviews). It’s also worth pointing out, as Eric Seufert did in a recent Stratechery Interview , that Google started monetizing Search less than two years after its public launch; it is search revenue, far more than venture capital money, that has undergirded all of Google’s innovation over the years, and is what makes them a behemoth today. In that light OpenAI’s refusal to launch and iterate an ads product for ChatGPT — now three years old — is a dereliction of business duty, particularly as the company signs deals for over a trillion dollars of compute. And, on the flip side, it means that Google has the resources to take on ChatGPT’s consumer lead with a World War I style war of attrition; OpenAI’s lead should be unassailable, but the company’s insistence on monetizing solely via subscriptions, with a degraded user experience for most users and price elasticity challenges in terms of revenue maximization, is very much opening up the door to a company that actually cares about making money. To put it another way, the long-term threat to Nvidia from TPUs is margin dilution; the challenge of physical products is you do have to actually charge the people who buy them, which invites potentially unfavorable comparisons to cheaper alternatives, particularly as buyers get bigger and more price sensitive. The reason to be more optimistic about OpenAI is that an advertising model flips this on its head: because users don’t pay, there is no ceiling on how much you can make from them, which, by extension, means that the bigger you get the better your margins have the potential to be, and thus the total size of your investments. Again, however, the problem is that the advertising model doesn’t yet exist. I started this Article recounting the hero’s journey, in part to make the easy leap to “The Empire Strikes Back”; however, there was a personal angle as well. The hero of this site has been Aggregation Theory and the belief that controlling demand trumps everything else; there Google was my ultimate protagonist . Moreover, I do believe in the innovation and velocity that comes from a founder-led company like Nvidia, and I do still worry about Google’s bureaucracy and disruption potential making the company less nimble and aggressive than OpenAI. More than anything, though, I believe in the market power and defensibility of 800 million users, which is why I think ChatGPT still has a meaningful moat. At the same time, I understand why the market is freaking out about Google: their structural advantages in everything from monetization to data to infrastructure to R&D is so substantial that you understand why OpenAI’s founding was motivated by the fear of Google winning AI. It’s very easy to imagine an outcome where Google’s inputs simply matter more than anything else, which is to say one of my most important theories is being put to the ultimate test (which, perhaps, is why I’m so frustrated at OpenAI’s avoidance of advertising). Google is now my antagonist! Google has already done this once: Search was the ultimate example of a company winning an open market with nothing more than a better product. Aggregators win new markets by being better; the open question now is whether one that has already reached scale can be dethroned by the overwhelming application of resources, especially when its inherent advantages are diminished by refusing to adopt an Aggregator’s optimal business model. I’m nervous — and excited — to see how far Aggregation Theory really goes.
Anthropic's Opus 4.5 appears to be a big breakthrough that slots into Anthropic's enterprise strategy, while ChatGPT gets new consumer features, and Meta might use Google's TPUs
Nvidia earnings are the wrong place to look for evidence of an AI bubble; the company's margins should be safe if power is the limiting factor.
Welcome back to This Week in Stratechery! As a reminder, each week, every Friday, we’re sending out this overview of content in the Stratechery bundle; highlighted links are free for everyone . Additionally, you have complete control over what we send to you. If you don’t want to receive This Week in Stratechery emails (there is no podcast), please uncheck the box in your delivery settings . On that note, here were a few of our favorites this week. This week’s Sharp Tech video is on how Apple commoditized mobile carriers. Gemini 3 Arrives. There was about a week of high hopes preceding the Gemini 3 release, and sure enough, Google’s new model is apparently state of the art across the board (although Anthropic maintains a lead in one coding benchmark). So what does that mean? Wednesday’s Daily Update was exactly what I wanted to read in the Gemini aftermath, as Ben explored the implications for the rest AI ecosystem; this week’s Sharp Tech episode builds on that analysis with an extended discussion of winners and losers from Gemini week. And there is good news: contrary to the claims of many anon accounts on X this week, the Gemini gains aren’t necessarily a death knell for Nvidia or OpenAI, even if, with apologies to Satya Nadella , it appears that Google very much knows its way around the dance floor. — Andrew Sharp The Most Takeable Companies in Tech. Our goal here with Stratechery Plus is to provide rock solid analysis of tech first-and-foremost, but also China, the NBA, etc. Andrew is in the middle of that as the host of Sharp Tech , Sharp China , and Greatest of All Talk . However, at the end of the day, takes still matter: people get bored with spreadsheets and spreadsheet writing; it’s the opinions on the unknown that are the most entertaining and attention-grabbing. To that end, Andrew, an expert takesman, has produced the most important ranking of the year: the most takeable tech companies, from 15 to 1 . My take on this very entertaining Article is that the first 14 companies were a preamble to explain why we just can’t stop talking about OpenAI. — Ben Thompson China Is Very Unhappy with Japan’s New Prime Minister. In the past two weeks, Chinese diplomats and pundits have called new Japanese Prime Minister Sanae Takaichi an “evil witch,” an “American running dog,” and warned that her “dirty neck” will be “cut off” if she sticks her head into China’s internal affairs. This week’s episode of Sharp China explores why Takaichi’s comments on Japan’s options in the event of Chinese invasion of Taiwan inspired this reaction, including the history of recent tensions with Japan, and why the Chinese rhetoric is as much a signal to the rest of Asia as it is to Japan. Also discussed: Hasan Piker’s viral travels through China, and thoughts on a Useful Idiot Industrial Complex that continues to thrive in the digital age. — AS ChatGPT Group Chats, Meta and the Encryption Trade-off, Network Effects and Ad Models — ChatGPT is getting group chats, a long-standing Stratechery feature request. It’s also a clear attach against Meta, who can’t respond because of encryption, while Google looms. Robotaxis and Suburbia — Robotaxis are poised to further close the delta between suburbs and the city; the city (and Uber) might never recover. Gemini 3, Winners and Losers, Integration and the Enterprise — Gemini 3 is out, and looks to be state of the art. What does that mean for everyone else in the AI space, and what markets might Google win? An Interview with Eric Seufert About Advertising and AI — An interview with Eric Seufert about the right advertising model for AI, the right AI for Meta, and why personalized advertising is good for society. The Definitive Ranking of Tech Company Takeability — Notes on the most (and least) takeable companies of 2025, including Nvidia, OpenAI, Tesla, and many more. AI in the AI App Cloudflare and the Tragedy of the Commons TSMC Arizona: What About the Water? The Curious Database Powering America’s Hospitals A Maximalist Response to Japan’s PM; More Bad Real Estate News; Leaked Warnings on Alibaba; Hasan Piker Touring China A Standings Check After One Month, A Nightmare Pacers Year Continues Apace, Steph Curry Propaganda Hour Notes From LeBron’s Debut in LA, The Injury Bug Bites Early, Buyer’s Remorse Trade Value Power Rankings Google Starts Dancing, The Winners and Losers of Gemini Week, OpenAI Has an Advertising Problem
An interview with Eric Seufert about the right advertising model for AI, the right AI for Meta, and why personalized advertising is good for society.
Gemini 3 is out, and looks to be state of the art. What does that mean for everyone else in the AI space, and what markets might Google win?
Listen to this post : It was difficult in the beginning to answer the question I got from everyone: what’s it like living in America again? After all, I had been coming back to Wisconsin in the summer for years, and my move back happened in the summer; things mostly felt like more of the same. Then, the leaves started turning colors, the air became chillier, and, as daylight grew shorter I came to relish one decision in particular: living in the suburbs. There is much to be said for urban life, and I was certainly spoiled in that regard living in Taipei. It always seemed odd to answer the question “What is the best part about living in Taiwan?” with the word “Convenient”, but that’s the honest truth: everything you needed was within walking distance, the subway was extensive, clean, and reliable, and, once you understood that traffic was governed by the rule of rivers (the bigger you are the more right of way you have), driving really wasn’t that bad either. When my parents first moved away from Wisconsin I needed a new place to stay for the summers and, concerned about upkeep of an empty house in the harsh winter, I opted for a downtown condo; it helped that downtown Madison was a beehive of activity with the university and state government, and I liked the idea of walking everywhere. Then came COVID and the summer of 2020, and suddenly downtown wasn’t so busy anymore; I found myself driving more than I expected, and feeling rather sick of condos, which I had lived in my entire adult life. And so, when a house opened up near an old friend, I snapped it up, remodeled it to my liking and then, this past year, decided to live there full time. It’s fashionable to hate on the suburbs, particularly for millenials just a bit younger than I am; I was born at the tail-end of Generation X, and my experience in small town Wisconsin was one of leaving the house in the morning on my bike and not coming home until dinner, hopefully in one piece. It was, all things considered, pretty idyllic, but I can imagine that the clampdown on youth freedom that happened over the last few decades, along with the rise of indoor activities like video games and smartphones, made the suburbs feel increasingly alienating and isolating. What a relief to move to the big city, particularly in the 2010’s when Uber came along. There were, in the 2010s, few companies more contentious than Uber, and not just because of the scandals and willingness to operate in the gray area of the law. There was a massive debate over whether or not the company was even a viable business. Hubert Horan, in his seemingly never-ending series insisting that Uber would never be profitable, twice attacked me personally (and dishonestly ) for believing that Uber would scale into profitability: One does not have to immediately accept all of those conclusions to see that Thompson’s various claims suggesting that Uber might someday have a viable welfare enhancing business are not backed by any hard evidence about efficiency advantages or sustainable profitability. All of Uber’s growth has required massive investor subsidies — $2 billion in 2015 and $3 billion in 2016. All of these subsidies have been destroying competitors who are more efficient but can’t withstand years of subsidies from Silicon Valley billionaires. Thompson argues that Uber has grown total market demand and offered greater service options at night. True, but all due to unsustainable predatory subsidies. Thompson says that Uber’s app gives it the great competitive advantage of controlling its customers. False — people don’t like Uber because the app has a neat user interface, people like Uber because the app shows more cabs at lower prices than competitors can offer. All of those cabs and low prices are due to unsustainable, predatory subsidies. Thompson insists “the fact remains that both Uber riders and drivers continue to vote with their feet” justifies his belief that Uber’s approach to regulation is right, but again ignores that they are not voting for the more efficient producer, but for massive service subsidies. Thompson is falsely claiming that Uber’s growth reflects the free choice of consumers in a competitive market. Uber’s predatory subsidies are designed to undermine the processes by which competitive markets help allocate resources, and then to eliminate competition altogether. If these benefits were created by legitimate efficiencies, as Thompson imagines, there would be evidence showing how they made Uber more cost competitive, or how they similarly transformed competition in other markets. To refute the points here about Uber’s predatory, market-distorting subsidies, Thompson would need evidence that Uber has scale economies powerful enough to quickly convert $3 billion operating losses into sustainable profits, and evidence that Uber has competitive advantages overwhelming enough to explain driving everyone else out of the industry. Since Thompson does not have any of this evidence, he can’t claim Uber has produced benefits for anyone but itself. Well, here we are in 2025, and over the last 12 months Uber has made $4.5 billion in operating profit, and that number is trending upwards (and doesn’t include the significant profits Uber makes from its non-controlling interests in other mobility companies that it gained thanks to its aggressive expansion); no, I didn’t have evidence of that profit in 2017, but I did understand how scale works to transform money-losing software-based Aggregators into profitable behemoths in the long-run. Another classic of the Uber bear genre was this 2014 post by NYU finance professor Aswath Damodaran attempting to determine Uber’s true value; the startup had just raised $1.2 billion at a $17 billion valuation, and according to Damodaran’s calculations, “it is difficult to justify a price greater than $10 billion” (his actual valuation was $5.9 billion). Investor Bill Gurley — before his dramatic powerplay that led to the ouster of founder Travis Kalanick — explained what Damodaran got wrong in How to Miss By a Mile: An Alternative Look at Uber’s Potential Market Size : The funny thing about “hard numbers” is that they can give a false sense of security. Young math students are warned about the critical difference between precision and accuracy. Financial models, especially valuation models, are interesting in that they can be particularly precise. A discounted cash flow model can lead to a result with two numbers right of the decimal for price-per-share. But what is the true accuracy of most of these financial models? While it may seem like a tough question to answer, I would argue that most practitioners of valuation analysis would state “not very high.” It is simply not an accurate science (the way physics is), and seemingly innocuous assumptions can have a major impact on the output. As a result, most models are used as a rough guide to see if you are “in the ball park,” or to see if a particular stock is either wildly under-valued or over-valued… Damodaran uses two primary assumptions that drive the core of his analysis. The first is TAM, and the second is Uber’s market share within that market. For the market size, he states, “For my base case valuation, I’m going to assume that the primary market Uber is targeting is the global taxi and car-service market.” He then goes on to calculate a global estimate for the historical taxi and limousine market. The number he uses for this TAM estimate is $100 billion. He then guesses at a market share limit for Uber – basically a maximum in terms of market share the company could potentially achieve. For this he settles on 10%. The rest of his model is rather straightforward and typical. In my view, there is a critical error in both of these two core assumptions. Gurley argued — correctly in retrospect, given that Uber’s gross bookings over the last 12 months were $93 billion in rides and $86 billion in deliveries — that Damodaran failed to consider how a radically better experience could dramatically expand the addressable market, and completely missed the potential for network effects leading to an outsized share of that expanded market. I do feel Uber’s effects even out here in the suburbs: when I lived in Madison decades ago, there only seemed to be about five taxis in the whole city, and they were only ever at the airport; now a ride is six minutes away, and I’m sure it would be even shorter if I were more centrally located. That’s particularly appreciated in a place like Wisconsin, not only because of the cold, but also the culture of drinking; the reduction in drunk driving alone has long placed Uber solidly on the “societal good” side of the ledger, at least in my book. Of course I rarely take Ubers: if you’re in the suburbs you drive, and fortunately, I like driving. That’s not the case for everyone, however: while my wife has driven in Taiwan for years, she’s always been nervous about doing the same in America, with its higher speeds, longer distances, and more uncertain directions. That’s why I got her a Tesla: instead of her driving the car, her car drives her. I’ve actually dawdled in writing this Article because I wanted to try out v14 of Full Self-Driving (Supervised) first, but it’s been over a month since its release and I still don’t have the Update, so my experience is based on v13. That’s ok, though, because Full Self-Driving (Supervised) is actually pretty amazing. It really does go from origin to destination without intervention pretty much all-of-the-time (v14 reportedly addresses the actually leaving the driveway and parking part of things), although I take over more than my wife does. My issue with Full Self-Driving (Supervised) is two-fold: the first is that it is the absolute best worst driver in the world. What I mean is that Full Self-Driving (Supervised) always handles the situation in front of it with aplomb, including tricky merges, construction, etc. I’m particularly impressed at how it stays with traffic, including speeding when appropriate. That’s the best part. The worst part is that Full Self-Driving (Supervised) seems to have zero planning: it will change lanes even though a turn or an exit is half a mile away, which is particularly galling when an exit lane is backed up; if you don’t take over that leads to an embarrassing attempt to merge back in a quarter mile down the road. In other words, Full Self-Driving (Supervised) gets in more messes than it should because of a lack of foresight, but it handles those messes perfectly. As someone who thinks well ahead of my route in an endless pursuit of efficiency this drives me crazy, but honestly, I would take best worst driver over the vast majority of drivers I encounter on the road. My second issue is related to why I keep writing out the whole name: the “Supervised” part drives me absolutely batty. Yes, yes, I shouldn’t look at my phone, but is it better to be forced to exit a perfectly competent — more than competent — driving mode to manually steer while sending a text? More galling is when I am looking ahead at a turn — which necessitates turning my head — and get yelled at by my own car to pay attention. I am paying attention, by actually trying to plan more than two steps ahead! Regardless, I absolutely do believe that Full Self-Driving (Supervised) is good enough to be Unsupervised , at least in good weather; it’s a bummer to realize that that still may not happen for a long time, and even when it does, the price may be things like actually flowing with traffic, even if it’s a few miles over the speed limit. Even then, however, what exists today — and make no mistake, Full Self-Driving (Supervised), with its ability to follow a route, is a step-change from lane-following adaptive cruise control — is enough to make a meaningful difference to someone like my wife. It’s a lot easier to enjoy the big house and yard when you have the capability to go somewhere else. One challenge I didn’t anticipate was that while trash pickup comes once a week, recycling pick-up is only every other week; that’s a problem given the number of cardboard boxes we go through, mostly from Amazon. In all seriousness, Amazon has transformed suburban living. It was always the case that the idea of dashing off to the nearby store was more theory than reality, even when I lived downtown; at a minimum I usually still drove. Next day delivery, however, completely changes the mental calculus: the likelihood I will run out of time to go to the store tips the balance towards just ordering what you need the moment you need it; the next day — and sometimes sooner — it’s on your porch (Walmart deserves a callout here: their delivery is usually even faster if you order something in store). Of course it’s nice to not have to worry about your delivery disappearing, or have to cart it up the stairs or in the elevator; you also have the suburban advantage of having places to store supplies, so you don’t run out in the first place. That was always true though — it’s why big box retailers were very much a product of the suburbs — but marrying that advantage to maximum convenience is a big win. Food delivery definitely isn’t as good, particularly for the Asian food I sometimes crave; our family has always been one to cook our own food, however, which is of course easier with a big kitchen (and three different types of grills). The better restaurant options are also all downtown, so that’s a minus, but hey, you can always Uber. The broader takeaway is that while there are still certain conveniences that come from a central location, the convenience delta — thanks first and foremost to Amazon — has been dramatically reduced. There is a point to this diary, and it comes back to Uber. Not only was I a bull during Uber’s rise, I’ve also been fairly optimistic about the company’s fortunes when it comes to robotaxis. From an Update late last year : Robotaxis are a technology, not a market — a means, not an end, if you will. Markets are defined by demand, and the demand to be tapped is transportation. And, in this market, the dominant player is Uber; no they don’t have their own robotaxis, but from a consumer perspective, they might as well: the rider doesn’t own the vehicle they ride in, they summon it from an app, and they just walk away when the ride is done. The experience — if not the novelty — is the same with a human driver or a robotaxi. Moreover, the human drivers come with some big advantages from Uber’s perspective: they bear their own depreciation costs, and can make individual decisions about the marginal rate necessary to provide supply, which is another way of saying that Uber can more easily scale up and down to meet demand by using price as a signal. It is an open question as to whether robotaxis can ever economically scale to meet demand: having enough capacity for peak demand means a lot of robotaxis sitting idle a lot of the time, while maximizing utilization means insufficient supply during peak periods. This last point is why my assumption is that Uber will very much be relevant in the robotaxi era: their supply network will be essential for scaling up-and-down within cities, and serving all of the areas that the centralized fleets do not. What is less clear is their long-term profitability, which may be somewhat out of their control. That last sentence was about Uber’s diminished bargaining vis-à-vis a centralized robotaxi operator versus individual drivers, and it’s an important one in terms of Uber’s long-term valuation. However, as robotaxis continue to expand — Waymo is now in five cities (three via their own service, two via Uber), Tesla (with human supervisors in the car) in two, and Amazon’s Zoox in one — I do wonder if I am making a similar mistake to Horan and Damodaran. First, like Horan, am I too caught up in the current economics of robotaxis? As an apostle of zero marginal costs I am intrinsically allergic to the depreciation inherent in the cars themselves, along with the significant marginal costs in terms of energy and insurance; Uber side-stepped this by offloading those costs to the drivers. Can scale solve this? At some point — Cybercab already points to this future — vehicles will be purpose-built at scale to be robotaxis, and my experience with Full Self-Driving (Supervised) has me convinced that insurance costs will be manageable, not just because of scale, but because there will be fewer accidents. Second, like Damodaran, am I limiting my thinking by focusing on the current market — even if that market is already massively larger than the taxi & limo market ever was? The experience of a Waymo is certainly magical; it’s also peaceful, and by removing the human from the equation, provides a sense of safety and security that Uber has always struggled with. This last point could address a major suburban point point, which is kids: the lockdown in kids’ freedom corresponded with a dramatic rise in organized activities, the sheer volume of which leaves lots of parents feeling like unpaid Uber drivers themselves. Some may rely on Uber to solve this problem; it seems likely to me far more would be willing to entrust their children to a Waymo. That does still leave the peak demand question: even if kids become a major market, what do all of these rapidly depreciating cars do during the day? And thus we arrive at why Amazon acquire Zoox: the obvious answer is delivery. The only thing better than next day delivery is same day delivery; the only thing better than same day delivery is same hour delivery. The best way to make that happen in a cost-effective way is to have a huge number of robotaxis on the road that actually aren’t making the decision that prices aren’t high enough, at least as long as those prices cover the marginal cost of a trip, which, in the case of a robotaxi, includes energy but not a human. Of course you still have to get the package to the doorstep, which is where robots come in; Tesla is explicitly going in this directions. From The Information : Optimus is Tesla’s biggest long-term bet. Musk has said there will eventually be more humanoid robots than cars in the world, and that Optimus will one day be responsible for about 80% of Tesla’s market capitalization. Inside Tesla, he’s pushed the Optimus team to find ways to use the robot in tandem with another big, nearer-term bet: the Cybercab, according to a person with direct knowledge. That includes Musk’s desire to have the Optimus robot sit in the Cybercab so it can deliver packages. That should be possible: newer versions of the Optimus robot are capable of consistently lifting and moving around with roughly 25-pound objects for three to four hours on a 30 minute charge, another person with direct knowledge said. But the connection between the robot’s torso and legs isn’t flexible enough to allow it to seamlessly get in and out of a Cybercab, according to the first person. Tesla would need to redesign the robot to change that or use a different vehicle for deliveries more tailored for Optimus’ shape, that person said. This is obviously all still a ways out, but it all feels a lot more possible today than it did even a year ago; relatedly, it feels a lot more uncertain that Uber will have a long-term role to play — and the company may agree! I thought this announcement from Nvidia at GTC Washington D.C. was a bearish indicator for the company: Nvidia today announced it is partnering with Uber to scale the world’s largest level 4-ready mobility network, using the company’s next-generation robotaxi and autonomous delivery fleets, the new Nvidia Drive AGX Hyperion 10 autonomous vehicle (AV) development platform and Nvidia Drive AV software purpose-built for L4 autonomy. By enabling faster growth across the level 4 ecosystem, Nvidia can support Uber in scaling its global autonomous fleet to 100,000 vehicles over time, starting in 2027. These vehicles will be developed in collaboration with Nvidia and other Uber ecosystem partners, using Nvidia Drive. Nvidia and Uber are also working together to develop a data factory accelerated by the Nvidia Cosmos world foundation model development platform to curate and process data needed for autonomous vehicle development. Nvidia Drive AGX Hyperion 10 is a reference production computer and sensor set architecture that makes any vehicle L4-ready. It enables automakers to build cars, trucks and vans equipped with validated hardware and sensors that can host any compatible autonomous-driving software, providing a unified foundation for safe, scalable and AI-defined mobility. Uber is bringing together human drivers and autonomous vehicles into a single operating network — a unified ride-hailing service including both human and robot drivers. This network, powered by Nvidia Drive AGX Hyperion-ready vehicles and the surrounding AI ecosystem, enables Uber to seamlessly bridge today’s human-driven mobility with the autonomous fleets of tomorrow. The thing about Uber the first time around is that it wasn’t simply providing a fancy app for the taxi & limo market; it was providing an entirely new experience for both drivers and riders that was orthogonal to that market, which let it create a far larger one. This deal with Nvidia envisions a different sort of evolution, where Uber’s existing market slowly becomes autonomous; that’s possible, even if it means significantly higher capital costs for Uber (and cars that cost more, since they are retrofitted instead of purpose-built). What is also possible, however, is that Uber gets Uber-ed: a completely new experience for both drivers (as in they don’t exist) and riders (including kids and packages delivered at the marginal cost of energy) ends up being orthogonal to the Uber market, and far larger. Moreover, this market will, for specific qualitative reasons around safety and security, be inaccessible to Uber’s core business, meaning the entire vision of “bringing together human drivers and autonomous vehicles into a single operating network” ends up being a liability instead of an asset. There are larger sociological and political questions around things like urban versus suburban living, just as there were when suburbs were built out in the first place. I do believe that the suburbs are very much back, and not just because I’m back in the suburbs; what will be a fascinating question for historians is the chicken-and-egg one between technology driving this shift, versus benefiting from it. What is worth considering, however, is if the last wave of urbanism, which started in the 1990s and peaked in the 2010s, might be the last, at least in the United States (Asia and its massive metropolises are another story). The potential physical transformation in transportation and delivery I am talking about is simply completing the story that started with entertainment and television in the first wave of suburbia, and then information and interactivity via the Internet, particularly since COVID. There are real benefits to being in person, just like there are to living in the city, but the relative delta to working remote or living in the suburbs has decreased dramatically; meanwhile, offices and urban living can never match the advantages inherent to working from a big home with a big yard. Whether or not this is good thing is a separate discussion; I will say it has been good for me, and it’s poised to get even better.
ChatGPT is getting group chats, a long-standing Stratechery feature request. It's also a clear attach against Meta, who can't respond because of encryption, while Google looms.
Welcome back to This Week in Stratechery! As a reminder, each week, every Friday, we’re sending out this overview of content in the Stratechery bundle; highlighted links are free for everyone . Additionally, you have complete control over what we send to you. If you don’t want to receive This Week in Stratechery emails (there is no podcast), please uncheck the box in your delivery settings . On that note, here were a few of our favorites this week. This week’s Stratechery video is on The Benefits of Bubbles . SpaceX Buys Spectrum — and Apple Should Be Interested . I’ve been taking a lot of interest in space recently, particularly SpaceX’s recent moves to buy wireless spectrum. What is particularly interesting are the comparisons and contrasts to the early years of the iPhone and Apple’s relations with traditional cellular companies; in this week’s episode of Sharp Tech — triggered by Tuesday’s Update — Andrew and I discuss the history of Apple and phone carriers, and why satellites are different. Some of those differences give reason for optimism, others for skepticism; the best way to achieve the optimistic outcome would be for Apple and SpaceX to work together. — Ben Thompson Apple and Google, Together Again. I’m happy to endorse any business analysis that compares a trillion dollar company to an alcoholic making promises, to itself and others, that it almost certainly won’t keep. Monday’s Daily Update checked that box, as Ben unpacked the short term logic and long term questions surrounding another Google-Apple partnership and the news that Apple is partnering with Friendly Gemini to remake Siri for the AI era. And which of these trillion dollar companies is the alcoholic, you ask? I don’t want to spoil it, but we do know one of them became notorious earlier this year for some promises that weren’t kept . — Andrew Sharp When Will America Catch Cup Fever? We are three years into the NBA’s experiment with an in-season tournament, now called “the NBA Cup,” and it’s still mostly ignored by the mainstream. I wrote on Sharp Text about the ways in which that event is a keystone to understanding the NBA’s modern problems on a more general basis. Come for that story, and stay for my admittedly radical proposal to make the Cup itself worth watching — awarding first round picks to every team that makes the Final Four, including the number one pick to the winner — and why that solution could also be healthy for the league’s overall business . — AS Apple Earnings, Siri White-Labels Gemini, Short-Term Gains and Long-Term Risk — Apple is already benefitting from AI via the App Store. Meanwhile, Siri will white-label Gemini; the long-term implications are significant. SpaceX Buys More Spectrum, SpaceX’s Pivot, Why Apple and SpaceX Should Partner — SpaceX buys the spectrum it needs to be a standalone mobile carrier; the company should partner with Apple to deliver truly differentiated experiences. Microsoft Earnings, CoreAI/MantleAI, Additional Notes — Microsoft declares independence from OpenAI and sketches out its future role building scaffolding for AI. Plus, Windows is tiny now. An Interview with Unity CEO Matthew Bromberg About Turnarounds — An interview with Unity CEO Matthew Bromberg about a career focused on turnarounds, from EA’s KOTR to Zynga and now to Unity. The NBA Cup Doesn’t Have to Be Terrible — A closer look at the NBA Cup in Year 3, including the case for using the NBA Draft to save the event and walk back the league’s misguided push for parity . Cold Weather and EU Regulations iPhone Pocket and ChatGPT Prompts Why the Original Apple Silicon Failed Singapore Tried to Grow More of Its Own Food… US-China Follow-Through; New Xi Textbooks and a New Aircraft Carrier; A Wolf Warrior Greets Japan’s PM; More Setbacks for Nvidia Wemby Goes to Hollywood, Mark Daigneault Moving Different, The Mavs Are the War on Drugs Re-Drafting Paolo, Chet and the 2022 Draft Class, The Pistons are Electric, Changes Afoot in Dallas? How Apple Changed the Cellular Economy, What SpaceX Wants to Do With Spectrum, Airlines and Carriers, Yann LeCun Departs Meta
Listen to this post: Good morning, This week’s Stratechery interview is with Unity CEO Matthew Bromberg . Bromberg took over Unity last year, and previously worked at Zynga, EA, Major League Gaming, and AOL. In this interview — which ended up being primarily about Bromberg, who I found fascinating — we discuss the lessons learned in a career centered around turnarounds. Bromberg helped rescue AOL’s relationship with EA, which led to him being hired by EA and turning around Star Wars: Knights of the Republic. After that he helped turnaround Zynga, and now his task is to turnaround Unity. We discuss each of these steps in his career, and how he is bringing lessons learned to bear to make Unity into a better business. As a reminder, all Stratechery content, including interviews, is available as a podcast; click the link at the top of this email to add Stratechery to your podcast player. On to the Interview: This interview is lightly edited for content and clarity. Topics: Background | Lessons From AOL | Esports | Rescuing Knights of the Republic | Zynga | Taking Over Unity Matthew Bromberg, welcome to Stratechery. Matthew Bromberg: Thank you so much. It’s really a pleasure for me. So I think this might be a first for me wherein I interview the successor of a CEO that I interviewed previously . You are the CEO of Unity, having succeeded John Riccitiello about 18 months ago. I want to get into that transition, of course, but first I want to learn more about you, your background, how’d you get started in technology — and I want to go back, really back to the beginning. So where did you grow up and let’s go from there? MB: I was born in New York City, I grew up mostly in New Rochelle, which is a suburb of New York City and I suppose my upbringing was pretty straightforward and mainstream, I was really into athletics and other things. But I also had this sort of other side in which I would kind of play Dungeons & Dragons with a separate set of friends and I’d play these really complex military strategy board games by myself because I couldn’t find anybody else I knew who had any interest in that whatsoever. Are these the ones where you’re like painting the figurines and stuff like that or…? MB: No, they were the ones with the little tiny cardboard units. It was like they were Civil War battles and other things and I had to play both sides, which makes it, by the way, particularly uninteresting, I suppose since I always knew what I was up to, but I could not find any other human being who had even occurred to me to ask, by the way, if they’d be interested. Now of course, the Internet’s made that kind of thing much easier now. It makes you really appreciate the upside of the Internet. MB: Yeah, exactly, it really is, it’s a big thing. So it’s like my brain is not highly mathematical, but it has always been drawn to complexity and systems thinking. I went to college and majored in literary theory. I was particularly interested in structuralism, which is really about how language is really comprised of systems or signs. In order to figure out what’s being said, you have to figure out how the system works and you have to look for really deep structures and patterns. That kind of thing turns out, by the way, later to be incredibly critical to thinking about how to make video games. No, this is amazing because I once considered majoring in linguistics for the exact same sort of reason. I don’t think I’ve ever revealed that fact about myself, but I can relate to it to exactly what you’re talking about. MB: Well, once I revealed that I played board games by myself, I think we were just in that space where anything could be revealed here, Ben. Well, but it’s interesting though that you mentioned the athletics part, because I talked to a lot of people who played Dungeons & Dragons and “Oh, I got my first computer when I was 12 and started programming XYZ”, in this job I don’t talk to a lot of people who are athletes. Athletics was a big part of my life, I played multiple varsity sports, and I’m curious what perspective you think that has given you. Is that a tie into gaming, which has certainly a competitive aspect to it? Or is it just sort of a happy coincidence and a fun fact about young Matthew? MB: Yeah, I don’t know. I think that in life, the more broadly you can expose yourself to different kinds of things and different sorts of people and different experiences, the better off you are. I think for me, I’ve always had this sort of — in a funny way, it’s good training to be a CEO because there is a very kind of a mainstream performative aspect to it. But especially when you’re working in technology, there is also a really kind of a detailed deep scientific element to it and balancing those two things, I think, has ended up being helpful for me. And by those two things you mean the competitive aspect versus the structural analysis? MB: Yeah. I think understanding how to work inside, not just competition, but inside the mainstream as opposed to sort of being shut up in your room and being a quiet genius. That was never my instinct, but it was my instinct to sometimes shut myself up in my room. So I think that balance can be helpful. Yeah, for sure. That’s just another angle that I thought about in the context of Stratechery over time. I always joked that my friend John Gruber , sort of like Daring Fireball has gone along on the ride with Apple, and for Stratechery, it’s kind of been that with Facebook. There’s a bit about Facebook where I feel like I always understood the company more and better by virtue of having a pretty normie background and being in sports, and the people that I grew up with, they just want to hear updates from their friends and family. This whole idea of being on Twitter and following your interests, has not even occurred to them. Meanwhile I was a huge Twitter guy, but I feel like I had that recognition of this whole other world that benefited me hugely over time. MB: It’s really true. That’s why, especially when you’re running a company, it turns out to be super critical for you to make sure you have a mixture of kinds of folks in the room all the time because otherwise, everyone thinks something stupid and it’s really not stupid, it’s going to actually be the thing that dictates how the whole world’s going to unfold, but nobody in the room has any idea. So you’re studying literary theory, now you’re the CEO of Unity, there’s been a long stretch in the middle. What happened next? MB: Well, when I was in college, I wanted to be a college professor — I don’t know, what else do you do when you’re studying literary theory? But my dad passed away suddenly when I was a senior in college and that sort of made me rethink becoming an academic. Maybe it was the idea of not having a backstop or either literally in the form of money or figuratively towards of support. But I decided to gravitate to something more concrete and I worked for a few years and then ended up going to law school. What sort of stuff did you work on in the intervening period? MB: I was a magazine editor. Got it. Literary theory, you got a job. MB: Yeah. What else could you do? I got a job where — but there were a lot of journals and magazines then that don’t exist anymore. Yeah, for sure. MB: So it was easy in fairness in that time. And then I thought, “Well, gee, I really want to go back to school, but what do I do?”, so law school made some sense to me. And at the time, I think I was intimidated by the idea of going to business school, which is what most people were doing. It struck me as this sort of closed, hermetically sealed thing that investment bankers did and I had no real kind of exposure to it. I just decided not to be a college professor so that idea seemed too far, but I thought, “Okay, I could go to law school and I’ll try to get a general education”. I knew I didn’t want to be a lawyer, so I went to school avoiding any of the classes that were like, Blank Law. I knew I didn’t care, so what I ended up doing, I ended up working a lot on the philosophy of language in the law. Turns out that what a word means and why it means that thing isn’t particularly critical and I actually ended up interestingly, oddly working with a MIT professor, working around some really early rules based AI systems. So you take legal statutes and you try to create these decision trees out of them and see if the computer can help you decide cases and I just was just knocking around looking for things that looked interesting and I worked over summers to pay tuition as a lawyer, and then I didn’t become a lawyer and I did something completely different instead when I left. So what was that? MB: Well, it took me a while to get into gaming. I started going around looking for a job and in those days, it was much less common than it is now for lawyers to do other things and people kept looking at me like it was insane. I had gone to Harvard Law School, I could get any legal job I wanted, and they thought there must be something really wrong with me, so everyone kept saying no to everything. I found an entrepreneur, his name was Steven Brill , he was the creator of Court TV, if you remember, the cable television network that was about the law, and he was a legal entrepreneur. He owned newspapers and businesses around legal media, and it didn’t seem odd to him, and I went to work for him creating one of the first online systems for lawyers, it was called Counsel Connect and we were going to create this marketplace for legal expertise. I’m not even going to tell you what year this was, it was a really long time ago and so I immediately got back into technology and systems. I ended up going from there to work in technology media and then ultimately, I gravitated to America Online where I worked in a whole host of things, but then finally was able to get into gaming that way. Got it. What did you learn from America Online? It’s interesting, you look backwards, it’s kind of like almost a joke in some respects, but it’s like, you had to be there — it’s one of the companies in that regard. MB: Oh my God, yes. You were literally there, so I guess you know what it was like from the inside. MB: And Barry Schuler who is on the board of Unity, was the CEO of AOL at one time, too. I would just say this for folks who are too young to remember, it’s critical to understand that AOL was the Internet and so imagine operating in a laboratory where you owned, controlled, all of the Internet as a walled garden. It was an extraordinary laboratory to learn anything and everything you could ever want to understand about how that ecosystem would work and how you would bring partners into it, how you draw customers, it was all of it. I have never seen a business model or a structure since then that we either did not do or did not try. So for me, it was an education in this world that was absolutely critical. Well, it is really a classic of the, speaking of Harvard, Clayton Christensen ‘s framework around, the first thing is deeply integrated because the whole experience is not good enough so you have to do it all, and the Internet was way too difficult for most people to figure out, particularly pre-Google. So you get AOL and it’s all there, to your point, but then over time, as all the component pieces become more possible and more viable and stuff gets built to glue it all together, the integrated thing becomes too heavy under its own weight, people start going elsewhere. That’s the AOL story in a nutshell but I’m curious, as you look back, as I asked about AOL, which you weren’t expected to be asked about right now. MB: (laughing) No, I haven’t talked about it in a long time. You say, “I learned so much stuff”, what’s the one thing that sticks in your head that you learned from there that you held onto ever since? MB: I learned a lot about how to structure relationships, content relationships with partners in a way which is mutually beneficial and I’ll give you the perfect example. The way I got into gaming was I was running the consumer products group at AOL, I was doing something having nothing to do with gaming, and Electronic Arts had a big deal with AOL at the time, it was several hundred million dollars I think. I can’t really recall, but back then we were selling what we called anchor tenancies to third party. So imagine being able to say, “Hey, I’m going to choose one partner in the video game space that I’m going to expose to the Internet and I’m going to charge you for that, and we’re going to have a relationship and we’re going to sell advertising, we’ll send the money back to you and we’ll have commerce and other things, but let’s do a deal like that”. So we had a deal like that with Electronic Arts, I had nothing to do with it, the deal had gone completely sideways. AOL was coming off the boil a little bit, we no longer had the ability to just shoot advertising dollars to partners who needed it any given quarter. The market was struggling, Electronic Arts was incredibly angry at us, they had made all these big payments, they weren’t getting value back. The night before, John Riccitiello was the president of EA at the time, I think not the CEO, was coming into New York to have a negotiation about this terrible relationship we were now in and he had told the CEO of AOL, “Listen, if I come back and I have a meeting and you show me the same people from this games group you’ve had, I’m going to just get up and walk out and see you”. So the CEO of AOL called me the night before and said, “Hey, could you go to this meeting, please?”, and it had never occurred to me in a million years that I was going to work in video gaming. I don’t know why I was too dumb to think like, “Oh, you could do this for a living”, and so, here’s where it all came together. It was the night before. I said, “Okay, could you send me the agreement that we have with EA? I don’t know anything about it”. So the lawyer sent me a 300-page agreement with side letters and it was the night before and here was all this training coming to a head, I read the agreement. In a way only a lawyer can, right? MB: And by the way, it’s English, anybody could read it. But I think in a way, it’s like I wasn’t intimidated about it. I thought, “Okay, I can read this and figure out what it is”, and I came into the meeting the next day and everybody’s very angry at each other, it was this big room of people and I said, “Listen, I stayed up late last night, I read all 220 pages of this the agreement, and here’s the thing I know for sure, I have no fucking idea what it means, and by the way, I don’t think any of you do either. Now it stands for something, which is that we’re partners and we’re going to be partners, but how about let’s stop arguing about what it says because it’s nonsensical, and just step back for a second and try to recreate a relationship, which clearly is not working”. And everyone kind of grumbled and looked at me and they’re like, “Yeah, we don’t really know what it means either”. (laughing) So the literary theory guy has a point. MB: Yeah, I made a point. And then I threw the piece of paper away. With any good relationship, once you pick up the contract, you’re already in trouble. That’s right, that’s a good point. MB: And we spent six months negotiating, renegotiating a relationship and that is how I actually met John Riccitiello to begin with. I later left AOL and started a company with two founders called Major League Gaming . It was the first big esports business in North America, and it was very, very early. And I ended up leaving that business, we sold it later and I was unemployed, and this is years after that meeting with John, and he called me and offered me a job at Electronic Arts and that’s actually how I got into video gaming. I actually did have a question about Major League Gaming, you said it was very early. That is sort of a natural tie in between your sports background and gaming, quite literally. Is there a real market for esports? It’s kind of come and gone. It’s been a fad, then it’s gone away. Is it one of those things, just like the barrier to entry is almost like too low, you have issues with cheating , is this ever going to be a thing or is it a thing and I’m just oblivious to it? MB: Listen, in 2000, which is when we were doing this, there were a couple of things that struck me as completely obvious that most people didn’t see. The first one was that watching video games was going to be something that billions of people did. I mean, geez, it’s unbelievable. The kids on YouTube and just these streams and all that. MB: Yeah, and this is now, whatever, 20, 24, 25 years ago, I knew how compelling it was and I knew everyone was going to find it compelling. By the way, there’s a super obvious way to explain this to people who don’t get it. Everyone in our generation watches sports, and I’m not a sports player anymore, I could promise you that. I tried to make my basketball come back a couple years ago, pulled my groin five minutes in, and I’m like, “That’s it, I’m done” — I still watch a lot of basketball, so. MB: And as more and more, I was sure that as more and more people played video games and had that first party relationship with the experience, they would then watch it in a very different way, just like with any other sport. But is it watching it like sports where you’re looking for a competition in a league in championships? Because a lot of streamers, it’s just really, it’s just entertainment. It is something happening in the background a lot of times. MB: Well, my view at the time was that competition was going to be the key to this. And I did believe that, and I thought that to make it truly compelling to watch, there had to be competition and also to draw the community and the online aspect to it, which we need to build into a real business, you need to create online competition associated with it. And so what we did was essentially try to create a league, the league for this activity before it really existed at all in North America. We had a players association and we signed pro players and we signed them to exclusive contracts, and we streamed video to millions of people. Even at this time, we had to deal with ESPN where we did SportsCenter updates of these things, and it was all absolutely working. We had multimillion dollar sponsorships with KFC and Hot Pockets and other things, and it was working like a small league. The challenge was that as it grew, the fissures in the relationships and the business model started to appear, because as the league, we didn’t own the underlying intellectual property. So you’re having a competition, it’s Call of Duty or it’s Halo, or it’s Rainbow Six or whatever it is, you don’t own that. They’re happy to give you rights to do that when it’s not that interesting, when you start streaming and millions of people are watching it and now you’re making tens of millions of dollars of advertising, guess what? They’d like to participate. And by the way, they might even want to own it themselves, which pulls against the idea of having one league. So we were always saying, “Listen, the best way to create value here is to create it inside the league structure, these things have existed for generations, we already know this to be true”, but you have this problem where all the participants were local maximizing for the activity. And so it’s hard to control players, it’s hard to control the intellectual property, and it balkanizes it and it keeps it from being as big as it otherwise would be. Right. Now if I wanted to watch competitive gaming, I’m not even sure where to go, to your point, what’s the one place, because everyone’s tried to roll out their own thing. It’s like a tragedy of the commons . MB: It has been, and it’s become a series of really large and really interesting vertical communities, but folks have struggled to build businesses out of that. You’ve seen this rise where on all this viewership, first people thought they’d invest in teams and that’s how they create equity value, and that didn’t work. And they thought they’d invest in the media and it’s just been a struggle for the industry, which is a shame. Which you know what happens, this happens again and again when these markets get super fragmented and end up in pieces, and this is the story of the Internet. There is one company that excels in coming up and cleaning up all the pieces and making all the money — and that’s Google . So now basically the winner of video game streaming is YouTube, that’s how it ends up. MB: If you can’t control it, and it just becomes an enormous part of something even more enormous, and that’s just how it goes. Tell me about EA. What did you do at EA and your experience there? MB: I had worked in online systems and done all these things, and I was a huge gamer myself, but I had never made a video game and John called one day and said, “Hey, we built this game”, it’s a massively multiplayer online game called Star Wars: The Old Republic . The company had been building it for five or six years, and it was going to be the game that took down World of Warcraft and catapulted EA to the next level. It was years late by that point, and it had been launched and it went up like a rocket ship and then was screaming down towards the earth and it was dragging all of EA with it and John called and said, “Hey, would you like to move to Austin, Texas to fix this game?”, and I said, “John, I don’t think I can do that, I don’t think I know anything about, I’ve never built a video game before”, and he said, “No, no, you understand online systems, you understand how to execute, we don’t have anyone can do that, you’ve got to come”. So I went down and visited and I went with my family. They refused to move, together, my wife and kids said, “Absolutely not”. They went back. I ended up moving to Austin, Texas where I lived by myself during the week, I flew home back to New York every weekend and for reasons I still don’t understand, I took this job and I literally thought maybe we wouldn’t even be in business for another — maybe we had another 30 days, maybe 90 days — it was one of the worst things in business I’ve ever seen. But I was so fascinated by the game and the opportunity and the opportunity to turn it around that I had to do it. Did you succeed? MB: I did. And it was really, what’s fascinating about it is in a way it made not only my whole career, but it actually gave me a sense of what it is that I do that I did not have before. Well, what is that? Tell me about that and how you developed it through this process. MB: Well, it’s like anything else in life. You stumble into these things, and I had been feeling a little bit frustrated in my career up to that point. I’d done a few different things and I was reasonably successful, but I thought, “Gosh, I thought this would be going better”, I feel like I have some unique skills, but I can’t seem to get it going exactly. Then I’ve been in startups and I’ve been in big companies and in startups, I was always frustrated, there’s not enough scale and maybe it’s not interesting enough. Then you get to big companies and they’re slow. Bureaucracy and all that. MB: There’s no urgency and you hate it. So you go back to a startup and you’re frustrated, I had gone back and forth, and now I’m put in the middle of this turnaround situation, and I suddenly realized that, “Hey, wait a second, this is the best possible combination of both things”. You get the scale and you get the urgency all at the same time. MB: That’s right. Nobody’s suggesting that we don’t need immediate and complete change, so I don’t have to go around convincing people of that fact, which is just mind-numbing and I don’t have the patience for it. But by the same token, there were 700 people there, it was hope that would be this multi-billion dollar business like, “Wow, there’s a lot I could do”, and I was drawn to the chaos and how much of the work was needed and how much difference you could make. There’s just so much low-hanging fruit. It’s like, “Look, I can keep myself extremely busy forever here”. MB: So much low hanging fruit. And for whatever reason, my personality is one where high degrees of chaos, high degrees of uncertainty are cool with me. I don’t find the upsetting or stressful, and I actually find it interesting. I find those puzzles interesting, and I don’t have a lot of fear about those sorts of things. Fear is the thing, especially in those circumstances, but it’s really true in any circumstance, which ruins your judgment because you’re trying to protect something, and so you’re afraid to do the thing you know have to do to make it better. I just don’t really have that bone in my body. But the good thing is in that situation, you don’t have to convince everyone to go along with you. MB: You don’t need it. That’s right. They’re just following. MB: Because by the way, I’ve been fired plenty of times. Lots of times in other jobs where people are like, “Hey, could you just take a breath? We don’t need to move so fast. Why do you have to change everything?” — God, is this really aggravating. It’s like in The Godfather, are you a wartime consigliere or not? In big companies especially, there isn’t a ton of enthusiasm for making change, for relentlessly pursuing improvement and refusing to settle for anything less than great. Nobody’s interested in that in big companies. In fact, it aggravates them, and so finding environments where that wasn’t true, which is critical for me. Was there a key thing that you did that turned the tide, or other than just picking up all the low hanging fruit? MB: I started to learn as I went. I think that in this particular game, it was a fascinating thing, there was a social contract that we have the players in which we were going to provide, it was a Bioware game, and we were going to provide fully voiced story, cinematic, massive amounts of story. We worked for five years to make that, and then people stayed up all night and played through it in a month, and that was hundreds of millions of dollars and they wanted more of it, and it’s just not going to work. A lot of times what happens in these businesses is you’re sideways in the model for one reason or another because the world has changed because you made a mistake. And what people tend to do is they bang their heads against that. “Do it harder”. MB: And they do it harder, and they try to solve a problem which is clearly insoluble. So when I got there, and this is particularly true if you have resources, when I got there, it was a subscription business and the obsession was fighting churn. So I said, “Okay, churn is bad because we’re losing all these subscribers, let’s go off and try to identify all the sources of churn that we can and then attack each one of them, and we’ll have hundreds of people do that all at the same time”. The first insight is that in a subscription business, churn is like death for an actuary. It’s not bad, it’s just a thing that happens and you have to manage it. Speaking of being not afraid, but yes. MB: Yeah, you can’t. I mean, death is a part of life, you can’t stop it. And when you think about it that way, it prevents you from thinking about it the right way, which is we are not trying to identify every source of churn to mitigate it, we’re trying to ask ourselves, “Are there sources of churn that if we could mitigate them would be impactful enough to keep us from going out of business in 90 days? What’s the answer to that question?”, because that’s different. So how did you end up with, “Let’s get rid of the subscription”? Because that’s one way to stop churn. MB: Well, so the first thing is, well, we need to open the size of the funnel, right? MB: That was clear. And the second thing was listen, and by the way, this is always the answer in all online businesses, but particularly in gaming, the only way to move mass numbers of consumers move their engagement is community and social connection. It’s always the only answer. If you want 10 or 20 or 30% more people to do something, you have to connect them to other human beings. So the voices you needed were not the specially-made voices for the game, it was people talking to each other. MB: That is absolutely correct. And as much as folks said, “Well, but that’s not the game we built”, I said, “Accept that, but that game’s going to fail. How about we build a game and we won’t keep all the customers, but there is a group of customers who want to play an MMO together, and we’re going to take all our resources, every last one, and just do the things that make more people connect with one another socially. I will not do anything else for the next six months and let’s see what happens, and we’re going to combine that with making it free-to-play and changing the model and let’s do that”. This was May or June, and we leaned into that. We told all the public investors that we were going to do that, and we relaunched that I think by that fall, it was very fast and it worked immediately. What’s so fascinating is you mentioned Knights of the Old Republic, and I think anyone who knows about that game thinks about it as one of the great successes in gaming, and it’s like that whole first period where it’s a total failure is just totally gone from memory. Has that struck you with some of these turnaround situations? But then also, like you said, you invented a lot of stuff. Of course, World of Warcraft was first, but we’re now all into live action games, or what’s the word for it, where you’re online all the time with other people? People play the same game now for months or years on end, did you see that the industry was going in this direction or was just really a, “Look, there’s a spark here of something that’s happening, we’re going to follow it”, and you ended up there by accident? MB: For me, it’s all those same threads like competition and social connection and playing together and against other people is the purest, most enjoyable form of entertainment there is. Human beings playing with one another is as foundational to our understanding of ourselves as it can be. It was never a doubt in my mind that that is where we should lean into for this particular game, but that would be the future of entertainment in my mind, that was always really clear to me. The other thing that I really took away from that experience, to your point, is that even in circumstances where you have a lot of very angry, upset customers and you really feel embattled and you feel like you’ve done the wrong thing and people are super angry, you can turn those sentiments around. Well, at least they have a sentiment, right? MB: That’s correct! In my first job with Steven Brill at Court TV, we were doing focus groups and people were angry and thought it was the stupidest thing they’d ever heard. “Why would anybody watch a trial on television?”, they thought it was so stupid, they were angry, and we were doing these focus groups and I was beside myself. I thought, “Oh no, this is terrible”, and he was thrilled, and I looked over and said, “Why are you so happy?”, he’s like, “Look how upset they are, this is going to be huge”. And to your point, it’s a reaction you need that means people are connected to something and they care. Just a quick question on this. Would you have succeeded, would it have made it over the hump if it wasn’t Star Wars, which of that was why people were upset? MB: That is a critical question, there’s pluses and minuses to that. Part of the reason I took the job, despite the fact that the game was so troubled, was that I could see that over the prior six years, we had made many, many, many hundreds and hundreds of millions of dollars of investment, and there was all this incredible value sitting there that we hadn’t fully optimized or exposed or connected. There were 300 ideas that were 80% done. I could see that the raw material was there, it just needed to be finished and that’s the other thing that’s fascinating, it’s not like every turnaround is a good idea. Right. Some stuff deserves to die. MB: Some things are just bad, and it’s always bad. The things are a good idea is where there’s incredibly smart people, enormous value, but just something’s going wrong. When you turn those things into the wind, they tend to turn much faster than anybody believes because everyone thinks it’s a disaster because they’re lost in all the negativity and noise. Yeah, but the reason there’s so much noise and negativity is because there’s a latent bit of people who care and something there, which if you align it’s going to explode. MB: Yes. There’s an expectation and a love, and you must have gotten a good start if all people did — everyone played this game for several months and then they quit and were angry, but they loved it to begin with. The mistake though that companies make in these moments is that what you have to do at that point is very, very humbly and very authentically and in a really candid way, say to customers, “Hey, I understand where we are, I understand why you’re upset, here’s what I’m going to do about it, and I know you’re not going to be really happy with me right now, because you don’t trust me because you think I’ve done a terrible job, but here’s what I’m going to do, and I’m going to do this next month, and I’m going to do this a month after, I’m going to keep giving you new stuff and I’m going to behave in a different way, and you’re going to see different things in the game. Pretty soon, you’re going to see that we are authentically trying to make this thing better and create something that you can really enjoy to the best of our abilities. I’m not going to wave my arms and I’m not going to use stupid corporate words, I’m going to try to explain to you in a way that you know that I know what the problem is, and then we’re just going to grind it out”. Every day, every week we’re going to give some people something better than they had the week before and before you know it, to your point about people forgetting, yeah, you lose some of the people, and in gaming communities can be toxic and you always have some people upset, but you can turn everything just by authentic application of effort and a real understanding of the issues. It is interesting how that this does seem to be the norm now. Games that do become large seem to inevitably go through this first year of just total disappointment and frustration before they figure it out. They’re like, “Destiny went through this”, the name’s escaping me [Cyberpunk 2077], but there’s another game that was really struggling for a year or two, now it’s huge. MB: It’s very common. They’re just so complex. I guess, well, you figured it out and now life’s too easy, so you’re like, “Well, I’ve got to find another flaming disaster”. MB: Well, here, let me just tell you why though, what you’re putting your finger on, why it happens, and then I will tell you about the next step. The thing is, when you are introducing a new video game into the marketplace, by definition, you are competing with behemoths. It’s like introducing a new social network into the market or anything else. There are someone who for the last 5 or 6 or 7 or 8 or 10 or 15 years has been building out in this genre an experience which by definition, hundreds of thousands or millions of consumers find really compelling. You’re going to come into this marketplace and say, “Hey, I have this new offering”, and sure, people might try it to see what it is and how good is it, but moving them and the social connections they have, the literal experience and the meta digital experience that they’ve built and in the existing game, ripping them out of that into something else is really, really hard. Launching a game that has not just parity with competitors but is in many respects better than competitors, is nearly impossible. This is why you spend years and years building these systems, and by the way, we can get into this later, this is my hope and expectations for how AI is going to impact gaming. We can talk about that later, but this is the core challenge of video game development in our world, and that’s why folks struggle with. I mentioned you jumped to a new ship, I assume you went with Frank Gibeau he took over as the CEO of Zynga. I think everyone assumes Zynga was pretty much dead at that point, famously started out with Facebook games, did the shift to mobile , and then by 2016 as a public company completely in the gutter. Were you interested in mobile or were you interested in tire fires? What was the motivation here? MB: Both. Both combined my two passions again, and it’s funny, isn’t it, to think that you could make a life out of helping revive broken video game businesses? That could be enough of a thing that it could make your life. In a million years you’d never, who would think of it? That’s the answer to the, “AI is removing all the jobs” — can you imagine describing this job to even you when you were in law school? MB: No. It’s like, “What are you even talking about?”. But yes, Frank and I had worked together really closely at Electronic Arts, as did Bernard Kim , who is our head of marketing and publishing, and the CFO from Electronic Arts. We all came together, and you’re right, at the time, I think Zynga effectively had no equity value. It was valued at the cash on the balance sheet, and we owned a building at the time, and my view of it was the following. If someone says to you, “Hey, here’s a billion and a half dollars and 2,000 people and some really great, but maybe dinged up, but really great gaming properties”, and you don’t think you can build a great video game company out of that raw material, you are doing the wrong thing for a living. What else could you need? People, money, an institution, some great brands, like good people to work with? Like let’s go, of course we can do this. Is this thing that customer acquisition is actually much harder than cultural change, so you’d rather do the latter than the former? MB: Well, listen, it is. I think the thing that folks often don’t value as much as they should, and this is what we’ve been gesturing at several different times, is the incredible magic that has to happen to build an online property of any kind, whether it be entertainment or otherwise that has millions of players engaging with it. That is not something to sneeze at. People said to me at time, “That’s the worst company I’ve ever, why would you go there?”, I thought to myself, “You have no idea what you’re talking about”. There are millions and millions of players who love these games, that can’t be recreated. Can we do a better job? Of course we can, that’s just the work. We were able to again, really, really quickly to turn that business around and then ultimately, if it was worth a billion and a half at the time, we ultimately sold it for 12 and a half, maybe four-ish years later. But more important than the money, it was just we started out with a company full of people who felt that they were failing, the business was shrinking, it was getting smaller, and we ended up creating the best mobile game developer in the West. If you learned about the importance of the social layer when you were turning around Knights of the Republic, what did you learn from Zynga that has stuck with you? MB: What I really learned at Zynga was that it was all about cultural change to your point, because Zynga was a freestanding company. It had been public, it had been up and been down, and the culture when we arrived was quite difficult and quite toxic, and the company was failing, and that means often that a lot of the great people have left. Sometimes what you can have is you’ve got some true believers who are great, and then you have some folks who just thrive on toxicity and misdirection who are just miserable. Then you got some people who maybe don’t think they can get another job or it just seems like a lot of work to look, so it’s like, “This is not a great recipe for success”. What you really need to start attacking is like, “Hey, what is our approach going to be like? What are we going to be as a company? I know who we were, what we going to be going forward?”. Not to make coffee mugs and t-shirts about that — it’s like, be bold. Here’s a t-shirt, it says, “Be bold”. It’s not like that, but to relentlessly communicate a clear series of values and then to have people watch you walk those values, that is the key to turning any company around. Was it important that you had that whole team come in at the top? Wholesale changes into the C-suite, you’re all a group coming in together. Does that just give you more freedom of movement and you get a throw the old regime under the bus start afresh? MB: Yeah. I think what was incredibly important for us was that we didn’t need to negotiate one another. We all knew each other, and we knew our strengths and weaknesses and we knew how we were going to work together and we had trust so we could go out together as a group and go out and fix this thing and build it. Skipping over the like, “What did he mean by that?”, we had worked together for years, so we had a real shorthand and there’s no question that helped speed the process. Where did Unity fit in this spectrum of Knights of the Republic to Zynga, to Court TV or whatever else it might be? MB: It had some things were similar and some things were different. I think the most important similarity they had was that I thought Unity was a generational business, that the opportunity was beyond my ability to articulate. I thought it was really — there was that much upside in it and I could see that the company had lost its way and was not succeeding. But I could equally see the 20 years of investment in unique and uniquely important tools and platform and an ecosystem and a community of millions of passionate developers, and a broader community that really wanted this company to survive and wanted it to thrive because the gaming ecosystem works better when Unity is doing a good job. Now, when you’ve got a company that has lost its way and off its customers and has been failing, by the way, a lot of times customers say, “You know what? I’m just done with this. There’s other alternatives. I’ll just go”. But isn’t it the fact it’s basically impossible to leave, almost make it, that’s a good thing on one hand, but it makes it way more toxic on the other. It’s like your employee problem at Zynga but 100 times worse. MB: Well, exactly. When people rely on you for something and it’s critically important to their livelihoods and you don’t deliver, it makes them very angry and upset. By the way, that’s understandable. You have to recognize the importance and the criticality of the role you play and treat your work and treat that community with reverence and a real sense of the privilege you have to be in that position, but really understand what’s required of you. You’re right, it makes it a lot harder, but it also meant that as we, again, just going back to the conversation we were having, as we got clear on what we wanted to do and how we wanted to be and how we would be different and promising we’d be different, and then beginning to deliver, that emotional bond and how important we are in the ecosystem, allows people to come back really fast, and to thank you for it. You use some interesting language there, which is “deliver”. And if anything, the most well-known issue is that Unity did deliver — they delivered a new runtime fee . I want to get more into the specifics later, but when you’re using that word “deliver”, they were failing to “deliver”. Was there a bit, as you look back on where Unity ended up where they were, was the runtime fee a culmination of a deteriorating relationship with developers? Or was it something that was out of left field and was so disruptive to their business models that it sent everything south right away? MB: Yeah. Actually somebody told me someone was writing a case study about it, actually, although nobody asked me about it. I would say this, I think the runtime fee idea, the idea itself was an outgrowth of a deep company-wide insecurity about its ability to deliver excellent product. What I mean by that is the following — we were looking to business models and bundling and tricks to fundamentally change the nature of the economics of the business we were in because we didn’t like it, it wasn’t working. Isn’t there a point there though? The problem is that — so Unity, I’ve written about this multiple times — we’ll have links over here where people can get background, but you have this SaaS business where the developers are paying for their seats, and ideally they incorporate Unity ads who make money there. But the problem you have is if the developer base is shrinking, it’s exploding during mobile, that’s no problem, but if the developer base is shrinking or not growing, you are not growing. You have this simultaneous thing where you have all these games where people are playing the same game for months or years, there’s just getting those hits in the first place is a challenge anyways. Isn’t there a bit where actually the core business model was in fact broken? MB: Well, here’s what I’d say. You said, wouldn’t it be great to get a piece of every transaction and mobile? Sure. That sounds great. But customers have to be willing to give it to you. Yeah, it sounds like a great idea, but as it turns out, it created a revolt. Our customers, they were literally boycotting us. To your point earlier, you need to find a business model which is acceptable to your customers and which feels commensurate with the value you’re delivering. It doesn’t really matter what you want, and to your point about the business model, it was all very inward looking. It’s like, “Well, gee, here’s our business model and here’s how this works, and we’d like more money, so we’re going to come up with this new thing”, it’s like, “Okay, great”, but the best way to get out of a box you don’t like is to get out of the box, not find a more profitable way to live in the box. What is that? How do you get out of the box? MB: We were and it was my view, and I think we feel comfortable now having operated on this for a while, that we could deliver fundamentally more value than we were delivering. We could deliver better, more impactful products that helped our developer customers in different ways, and that we can have a much bigger business doing that without needing to make everybody angry. So, we took it in stages. The first piece was to repeal the runtime fee, because it was so antithetical to how people imagined the way they’d be charged. It was one of those things where if you zoom out and you’re weighing out the logic of it, it makes sense. If the developers succeed, you succeed. That’s sort of like the core idea of this piece here, but we don’t live in theory. MB: We don’t, you don’t. You live in a twenty-year history of how you monetize up to date and people built entire companies, and livelihoods around one model, and it’s hard to change. MB: And by the way, you know how you figure this out? You just pick up the phone. What I did when I got there was I called all of our customers, all of our big customers, this is not rocket science. And I said, “Hey, help me understand this”, I could tell from the Internet — before I was thinking about beginning, I could tell that this is a bad idea, help me understand. And understanding from their perspective how they were thinking about it, why it made them angry, that is the most important thing you can do. Because by the way, in those conversations, what our customers said to me was and when I picked up the phone, I was a little scared, I knew a lot of these folks before. I thought you were never scared. MB: Well quiet, I keep my tiny voice, I’m a human being, it was my tiny scared voice. And inside I thought, I didn’t know if I was going to get yelled at, and almost to a person they said, “Look, we are happy to pay you more money, we understand that you are delivering more value than we as a community are paying you, but I will not pay you this way” — that’s a solution, they’re giving you a solution. How often do you show up to customers and they let you know that it’s okay if you have to raise prices substantially? Not 5%, not 10%, substantially, like model-changing, but with us in partnership in a way that’s predictable for us and doesn’t feel like you’re reaching into our pockets. Because if you write a movie in Microsoft Word, Microsoft doesn’t get a piece of the gross. Now, whether we could pick that analogy apart on where it’s not accurate, but here’s some power in it and that’s how people felt. And so, we went in a different direction. So, as part of the runtime fee , you raised prices right off the bat. So, you gave them what they wanted right away. But as you think about the business going forward, I mentioned before the fundamental tension does still exist. We don’t have smartphones growing at the rate they were, where you’re basically surfing this secular wave. You are delivering ongoing value, every time these games are run, 80% of games or whatever it is, they’re running on a Unity Runtime, which you’re not benefiting from. At the same time, it is zero marginal cost software, it’s not like it’s costing you for it to run. That’s running on the phone, on someone else’s power and whatever it might be. So what’s the solution going forward? What was the confidence that Unity was lacking that you think they can deliver, that they weren’t previously? MB: It is my view and I think it’s now really the whole company’s view, that there are other areas of massive upside in our business, and I’ll give you a few examples. The first and most important one is our advertising business. So, the real challenge coming into Unity, by the way, coming in, and this also goes back to the runtime fee, is nobody can figure out how the advertising business and the game creation business were connected to one another. Beyond the fact that you had the customer like, “Hey, click this button over here and sign up for ads”. MB: Yeah, but there were often different people inside the same customers. So, there’s the developer and then the person buying an ad, maybe they’re not even the same person. And by the way, we had done an acquisition and so we had two different groups of people doing this and when I first started, the investors would always ask me, “Shouldn’t you just split these things up? What do they even have to do with one another?”, and in many ways that core question was also one of the drivers of the runtime idea, because the idea was no, no, no, the connection is going to be in the business model, not in the product. So because what we’re going to do is we’re going to raise prices so substantially, but we’re going to say, “Hey, you don’t have to pay that if you buy advertising from us”. Yep, that’s right. MB: So, actually we’re like, “Hey, we’re going to make sense of this acquisition we’ve done”, we’re going to make sense of these business units that aren’t integrated, by creating a business model which unites them. But also, sadly flies in the face of what customers want and articulates no additional product value so that’s just a bundling, which just feels like you’re jamming something down my throat that I don’t want. If our advertising product was more effective and more efficient, people would use it on their own. What did AppLovin get right? Because this is sort of the period ATT comes along, Unity laughs at it, “Not a big deal, doesn’t impact our business” — turns out it did impact your business. Meanwhile, AppLovin comes along, acquires MoPub, just starts really crushing it, obliterating you in particular. What did they figure out that you didn’t? And how are you going to compete with them going forward? MB: Yeah, we missed a cycle of technology investment. While we were integrating acquisitions, while we were thinking about business models and ways of getting folks to buy more advertising by bundling products, they were building a completely new machine learning stack that was fundamentally more effective and efficient than the one we were operating on. We were on a old style algorithmic ML, really not even a deeply ML stack. Much more deterministic. MB: Yeah, they were moving to neural nets and into the future. Which was the way you had to deal with ATT, was you were losing that deterministic signal, so you had to be in a probabilistic world. MB: That’s correct. And so, that’s the thing you should be up all day and night thinking about. Not movie effects. MB: Yeah, exactly. Or, “Hey, my ad business is fundamentally uncompetitive, how can I strong arm customers into buying more of it?”, the answer is the product’s uncompetitive. How do I make the product competitive? Once the product is competitive, we have all sorts of opportunities and that’s what I mean about getting out of the box. And so, what we did was we built a modern self-learning neural net system from scratch, with some of the best engineers in the world, called Vector AI , and we launched it and it had an immediate, and market positive, impact in our business. You’ve talked about using Vector AI to basically incorporate gameplay into understanding the target. How does that work? MB: Yeah. So, the part one of this was, “Hey, let’s be fundamentally more competitive on our ad business”. Part two is, how do you think through, as you mentioned, those real connections between advertising, game creation, and the runtime? What actually connects those things? And what connects those things is the need to have a really deep and clear understanding of the gaming consumer, because that sits inside how you succeed in all phases of the game business. Whether you’re prototyping a new game, and want to understand how people are behaving in that game, and what’s engaging them, and what’s causing them to transact, and what’s causing them to quit, and what’s causing them to make friends, all that is a data challenge. How do I interpret data which we can have access to through the runtime, as a way of better understanding how to build a game? And then when I’m operating in live service, how do I use that same connection to consumer understanding to optimize my live service? Last two weeks ago, we announced the commerce product — I was going to ask you for that. It’s been so fascinating, we’ve gone a little bit long, but I mean I’m actually quite interested in this. You launch this new commerce product in partnership with Stripe, people can do transactions outside of the App Store. But you’ve talked about solipsism and focus on your own problem. Aren’t developers doing this a little bit? Isn’t actually the App Store pretty great for consumers? Are we going to get a situation where they spend a lot of time building alternatives and the drop-off in conversion is so high because it’s not fully integrated, that they’re just going to end up back where we started? MB: I think we’re going to end up over time in a more open environment in which there are more choices. And yeah, do I think the app stores are going to go away? Do I think they should go away? I don’t. I really don’t, but I do think that more choice is a good idea. And to your point, the mechanics of, “Okay, maybe I’m recapturing 30%, but I’ve also got to move customers off of the App Store” — so, I’ve got to incentivize them, and then I’ve got to operate a web store, and then I’ve got to figure out how to do these transactions myself. It’s not simple, but it’s that very complexity that gave us an opportunity to deliver for our customers, because this is precisely the kind of thing Unity should be doing. You’re already building the game in Unity, we should provide you a native simple way to operate stores across any device, across any platform. And then by the way, over time, we can build machine learning driven products to help you optimize and personalize the experience of your gamers inside the game, based on a really greater native understanding of how and why people are transacting and that is the piece in general that connects game creation, game operation, and then new player acquisition. It’s all built around this need to understand the consumer and the future vision of interactive entertainment as being personalized on a literal basis, which is to say all of us should have a somewhat different path through a video game based on who we are and how we play games. That optimization is very possible and AI in particular is making that possible and all that is going to sit on top of the Unity platform. Those opportunities, by the way, especially as interactive entertainment explodes, and more and more people make games, that opportunity is going to dwarf any opportunity we had to raise prices in a funky way on the game developer. It’s like, you’ll look back on that and go, who cares? That’s pretty exciting, this idea of anyone can make a game and they can just use Unity to do it. Is that though the real growth opportunity? Or is there a bit where we’ve been in stasis, the smartphone’s been dominant, you’ve had the three consoles, you’ve had PC, but maybe we’re on the verge of a re-explosion of new hardware form factors of different things? And you just need to get the company right and tight, so that when that comes along, we’re back in a world that plays the Unity’s write once, run anywhere strengths? MB: Listen, I think it’s both and either. And I think that’s exactly right, by the way. When you’re running any company, especially in the technology business, you need to keep both those things in mind at the same time, which is, I have a vision, it’s really clear but also, we have to be super attentive to the facts on the ground and the execution at any given moment in time. That’s the original Unity story, they’re riding this almost by accident. They started on the Mac of all things, writing this engine and mobile comes along and they just ride it. It’s not like it was brilliant strategy, it was the right place, right time. MB: That is our DNA, democratization of video games is literally our founding mission. We had an environment which we want to give any developer, any software developer, the ability to make a video game and that didn’t exist, and that has been achieved. The next version of that vision is to enable any content developer to make an interactive experience and we can work both at the same time, by which I mean we’ll offer AI tools to help our professional developers build more effectively and efficiently, so that they don’t have to spend three or four years making the table stake systems and can get to innovation faster, as we talked about earlier. But we can also open the top of the funnel to all those content creators who, by the way, are obsessed with engagement, are going to discover that linear video cannot engage anywhere near the way interaction can and so every creator is going to be looking to figure out ways to make their creations more interactive. If we can provide those tools as well, and we can come at it from the top-down and the bottom-up, there’s an enormous opportunity I think that we have. All right. Matthew Bromberg, it’s great to talk to you, I could go another hour, this is super interesting. MB: Me too. I hope we talk again soon sometime. MB: I really appreciate you taking the time and I really enjoyed it. I’m an enormous fan of your work, so I really appreciate it. This Daily Update Interview is also available as a podcast. To receive it in your podcast player, visit Stratechery . The Daily Update is intended for a single recipient, but occasional forwarding is totally fine! If you would like to order multiple subscriptions for your team with a group discount (minimum 5), please contact me directly. Thanks for being a supporter, and have a great day!
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