Acquired - Amazon Web Services

Episode Date: September 6, 2022

So, how DID an online book retailer end up building the infrastructure layer that powers the entire internet? (Or at least 39% of it, per latest market share data.) While many myths, legends,... and some downright falsehoods exist, the real answer to that question deserves a full Acquired episode of its very own. So here it is: the story of Amazon Web Services. Who’s got the truth? Tune in and find out. :) Sponsors:ServiceNow: https://bit.ly/acqsnaiagentsHuntress: https://bit.ly/acqhuntressVanta: https://bit.ly/acquiredvantaMore Acquired!:Get email updates with hints on next episode and follow-ups from recent episodesJoin the SlackSubscribe to ACQ2Merch Store!Links:Steve Yegge’s Platforms Rant (so good!) Ben Thompson on AWS and Snowflake Episode sourcesCarve Outs:Moon KnightJohn Carmack on The Lex Fridman Podcast‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

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Starting point is 00:00:00 People, turns out, loved the Amazon.com episode. That was so awesome. Makes me a little nervous for this one. Oh, massively. By far and away, our biggest episode ever. Is this how George Lucas felt when he was doing Empire Strikes Back? You did not just compare us to George Lucas, did you? I swear we're humble. All right, let's do this. Who got the truth? Is it you? Is it you? Is it you? Who got the truth now? Is it you? Is it you? Is it you? Sit me down, say it straight
Starting point is 00:00:36 Another story on the way Who got the truth? Welcome to Season 11, Episode 3 of Acquired, the podcast about great technology companies and the stories and playbooks behind them. I'm Ben Gilbert, and I am the co-founder and managing director of Seattle-based Pioneer Square Labs and our venture fund, PSL Ventures. And I'm David Rosenthal, and I am an angel investor based in San Francisco, cold San Francisco here in August.
Starting point is 00:01:04 And we are your hosts. All right, David, let's say you run a lemonade stand. You sell me the highest quality lemonade you can for the lowest price, $1 a cup. And when you add up all your costs, the variable ones like the lemons and the fixed ones like the table that you rented, it costs about 98 and a half cents to give me that lemonade. And you're happy your turn to profit, I'm sure. But man, you are going to have to sell a lot of lemonade. So you're telling me I'm amazon.com in the fourth quarter of 2001, which is actually where we're going to start our story. Perhaps. But you discover something
Starting point is 00:01:41 interesting. By making all this lemonade, you get really good at the stuff it takes to run a lemonade business. The perfect cups and ice and lemons, everything. And it turns out, all that stuff that you just got good at, you can sell to other businesses. And guess what? You realize further
Starting point is 00:01:58 that when you sell your services to other companies, when you charge them a dollar, it only costs you 70 cents to make it. So 30% margins instead of something like a percent and a half, you have to sell a lot less of those services than you ever did on Lemonade to make the same amount of money. Well, then if you told me that, I would dig into it even further. and I would realize that the existing companies that sold stands and cups and whatnot, they were actually making 70% margins on their stands and cups. And so I would be quite happy to take 30% margins and disrupt them and still do better than my lemonade business.
Starting point is 00:02:40 Well, listeners, of course, on our last episode, we talked about Amazon's retail business. And today we are talking about Amazon Web Services, the cloud computing pioneer. And those margin percentages that I just used are the real ones for the retail business and for AWS. AWS's revenue is only about 15% the size of Amazon's massive retail business. But their profits, or the operating income to be specific, from AWS are in total the same, if not more, than their e-commerce store. I think it's the case that every year since 2015, when they started breaking out AWS's financials, the total operating income from AWS has actually been bigger than the retail business. There may have been some quarters where it was off, but generally that trend is accurate. Wild. So we're going to talk
Starting point is 00:03:32 about a completely different type of business today than we talked about last time. Sort of. There's a lot of similarities and a lot more than you would sort of guess when looking at an online retailer that started as an online bookstore and a cloud computing pioneer. Well, speaking of e-commerce, we have huge news. You can finally, finally buy Acquired merch on the internet. That is available at acquired.fm store or click the link in the show notes. You can grab your favorite tee, crew neck, hoodie, tank, or even a onesie, since I know a lot of you out there are like David and have little ones at home. Okay, listeners, now is a great time to tell you
Starting point is 00:04:11 about longtime friend of the show, ServiceNow. Yes, as you know, ServiceNow is the AI platform for business transformation, and they have some new news to share. ServiceNow is introducing AI agents. So only the ServiceNow platform puts AI agents to work across every corner of your business. Yep. And as you know from listening to us all year, ServiceNow is pretty remarkable about embracing the latest AI developments and building them into products for their customers. AI agents are the next phase of this. So what are AI agents? AI agents can think, learn, solve problems, and make decisions autonomously. They work on behalf of your teams, elevating their productivity and potential. And while you get incredible productivity enhancements, you also get to stay in full
Starting point is 00:04:58 control. Yep. With ServiceNow, AI agents proactively solve challenges from IT to HR, customer service, software development, you name it. These agents collaborate, they learn from each other, and they continuously improve, handling the busy work across your business so that your teams can actually focus on what truly matters. Ultimately, ServiceNow and Agentic AI is the way to deploy AI across every corner of your
Starting point is 00:05:23 enterprise. They boost productivity for employees, enrich customer experiences, and make work better for everyone. Yep. So learn how you can put AI agents to work for your people by clicking the link in the show notes or going to servicenow.com slash AI dash agents. After you finish this episode, come discuss it with David and I and 13,000 other smart members of the Acquired community at acquired.fm slash slack. And if you're dying for more Acquired in the meantime, go check out the LP show by searching Acquired LP in any podcast player.
Starting point is 00:05:57 The next episode is with David's partner in crime and kindergarten ventures, Nat Manning, talking about his company Kettle and how the business of reinsurance works. That, of course, is already live if you are a paying LP, which you can become at acquired.fm.lp. Now, without further ado, David, take us in. And listeners, as always, this show is not investment advice. David and I may certainly do have investments in the companies we discuss, and the show is for informational and entertainment purposes only. Well, we left off the Amazon.com episode in 2007 with the sort of Sony PlayStation-like coda of the Kindle story and the new chapter. One might say that it seemed at the time to the outside world that Amazon was opening as a true technology company with the Kindle. I believe the quote from
Starting point is 00:06:54 Eric Schmidt in the Everything Store was, the book guys finally got technology. And of course, as we talked about, Jeff Bezos always got technology. This was not a shift. And in particular, this was not anything new because of everything we are going to talk about on this whole separate episode today. So to do that, we need to rewind back, as I early 2002, the immediate post.com bubble popping crash era. And Bezos and Amazon, as hard as it is now to remember, he was like an embattled CEO at this point. They'd just gotten rid of COO Joe Ghali. The board has brought in Coach Campbell. Amazon's fighting for its life against both eBay and Wall Street. Isn't it insane to think that the board was sort of in the place with Jeff Bezos thinking, we really need some adult supervision to be a scale CEO and help this guy out?
Starting point is 00:07:57 Freaking Jeff Bezos. Obviously, that did not pan out, and Bezos came valiantly riding back in and ran the business for another 20 years. Another 20 years until handing the reins to somebody else who we're going to spend a lot of time in just a little bit here talking about, of course, current Amazon CEO, Andy Jassy. Yep. So I don't even know what the right word is to use to describe AWS. I was going to say I wrote behemoth in my notes. Pioneer, inventor. I don't think there's anything you can say that captures how big and how important AWS is. It is one of the biggest and most important businesses, technologies, products of the modern world.
Starting point is 00:08:48 Yep, no doubt. I don't think it's controversial to say even much more so than Amazon.com. Yeah. I mean, it's interesting. During the pandemic, you could argue that Amazon.com was more important because everybody needed to sort of buy goods and get them at home. But everybody also needed to be on the internet and the internet runs on AWS. Yeah. So today we're going to tell that story. It's funny as we did the research. So there's no like everything store book dedicated to AWS. There are a lot of very disparate resources
Starting point is 00:09:21 and stories out there. And there actually are quite a few conflicting and competing stories about what the true origin is of AWS. You might say it has a cloudy origin. See what we did there? Ew. Ew. It is true. As we were doing the research, you know, of course, David and I read both of Brad Stone's excellent books. I watched the PBS Frontline documentary, which of course is already a specific angle that they're trying to take on the company. You sort of read any of these Amazon analysis pieces, they're like 95% about the retail business. And they'll talk about things like the relationship with employees and the big New York Times piece that came out in 2015. And they'll talk about the relationship with the warehouse workers, or was this good for the world? And everyone indexes on that, which is important and deserves all the attention it's got. But almost none of these spend a material amount
Starting point is 00:10:16 of time on AWS other than mostly an apocryphal founding story, which is not even really how it happened. So we identified, you're referring to one origin story of AWS. We identified not one, not two, not three, but four separate origin stories. And we're going to tell them all here. I think there is something important to learn about what AWS is and about Amazon and about Amazon culture in all of these. So let's start with the first and most obviously untrue one, which is ironically also the one that the layperson believes the most. Yes, because it's tempting. I mean, it's like an, oh, like it's too convenient. Yes. And that story is the excess capacity narrative. So the way this story goes is that right around this time, 2001, 2002, 2003, amazon.com, the retail business, like all retail businesses in America, at least is highly seasonal.
Starting point is 00:11:23 They have huge spikes of traffic and demand in Q4 for the holiday shopping season. And that's when most of, maybe not most, but the largest share of any quarter revenue happens in Q4. So much so that for the first at least five years of the business, there was a rule in November and December that you could not commit new code to production. That's right. It was so all hands on deck that no new features were allowed unless it was a red flag bug fix. Oh, and we didn't talk about this in the Amazon.com episode, but for years and years and years, the executive team and the business side of the company and the engineers,
Starting point is 00:12:09 everybody would go work in the warehouses in Q4. That or customer service. Oh, how times have changed. Can you imagine someone sitting down in day one North or Doppler being told that they have to go pick and pack for a while? I think for a while they continued to do it even when it wasn't necessary just as like a culture thing. But obviously those days are gone now. So the urban legend is that because of this dynamic, Amazon had this brilliant realization around that. And again, when they're trying to achieve profitability, that they had excess technical infrastructure capacity in their IT operations during quarters one through three. So they had to build out for the peak demand of Q4, all the traffic on the website, all the transactions happening. But the rest of the year, all that capacity was just sitting there. And so they decided, let's rent out that capacity
Starting point is 00:12:57 to other developers. Brilliant, brilliant. We are going to turn a large expense line in the business into a revenue line. Magic. And of course, this falls down in two enormous places. One is if you've ever been inside a pre-cloud technology company, you know that... It doesn't work that way. Yeah, you can't just say like, oh, cool, like the servers aren't in use right now. And there's nothing highly customized about these servers. And they're not tightly coupled to our applications in any way. So we'll just make it so that anyone can very easily just run their applications on it. And there's enough security set up correctly so that anyone can just get access to our data center, and the network hardware
Starting point is 00:13:38 sort of understands how to serve other tenants other than us. None of that existed, and none of that was true. So there's just no way you can be like, oh yeah, other companies just started using our infrastructure and it was pretty rip and replace. In a pre-cloud infrastructure world, you installed your software, your code base on your servers that you owned. The amazon.com code base was literally installed on a bunch of boxes that they owned. You couldn.com codebase was literally installed on a bunch of boxes that they owned. You couldn't just rent out the capacity. Until 2000, they were servers from Digital Equipment Corporation, DEC. They were DEC alpha servers. These were unbelievably high
Starting point is 00:14:17 margin servers that you, I believe, leased from the manufacturer. It was the same business model that IBM had forever and Oracle has or had forever, where you get this highly bundled hardware software platform that you would use to run your applications. And they would make 80% gross margins on these things. There's this massive markup. They were monolithic. And to be honest, the thing that really changed all this was Linux. When Linux came out, and you could do the stuff that you used to need Unix workstations for on an open source operating system, well then everything changed because you can go buy a whole bunch of different hardware, put Linux on it, and then
Starting point is 00:14:56 write your own applications. And so this laid the groundwork for maybe infrastructure doesn't have to be as insanely expensive and all the profit pools from all of this infrastructure don't have to be captured by, say, a DEC or an Oracle or an IBM. And this would lay the groundwork for a lot of things to come, including, frankly, just saving Amazon as a company. I mean, in 2000, they almost went out of business because they were so tight on cash and they were spending so much on infrastructure that this sort of moved to the open source ecosystem and doing a massive rewrite of all of amazon.com to run on Linux and run on these. They did this big deal with HP run on HP servers. Right. Rather than deck that frankly
Starting point is 00:15:42 saved the company from a cost perspective during that really tight time. But that is not virtualized cloud servers. That's not what we're talking about with AWS. Here's the other reason why this excess capacity myth is a myth. How is Amazon supposed to serve their AWS customers if all of them are on excess capacity during Q4 at all. Like, let's say I'm Netflix and I just took a dependency and all of my streaming is happening on AWS. Is Amazon just going to tell me I can't do it during Q4 when they need the servers? It's ridiculous. No holiday movies.
Starting point is 00:16:16 Can't watch Die Hard at Christmas. So it is a very convenient narrative when someone's trying to solve the puzzle of how did this internet retailer turn into a real technology company? Oh, they had all these extra servers dispelled. So the best and final word on this that we have to put here, because it literally is from part of the horse's mouth itself, comes from Werner Vogels, the, at the time, AWS CTO, now CTO of all of Amazon, who wrote flat out in a Quora post in 2011, quote, the excess capacity story is a myth. It was never a matter of selling
Starting point is 00:16:54 excess capacity. Actually, within two months after launch, AWS would have already burned through the excess Amazon.com capacity. Amazon Web Services was always considered a business by itself with the expectation that it could even grow as big as the Amazon.com retail operation. Maybe, maybe. The other interesting thing to point out is it doesn't give Amazon enough credit about their intentionality and strategy. It short sells Amazon. Yeah, they had this extra capacity, this cost center that they were using. Well, two things. One, technology was never a cost center for Amazon.
Starting point is 00:17:34 They never looked at it like, oh, we have an IT department. They always thought about themselves as a technology company. So it was always thinking about, okay, in 18 months, Moore's Law is going to make it so we have twice as much compute. What crazy cool stuff can we do with that? They always looked at technology as an investment, not a cost center. And the other thing, to your point that it sells them short on, is as if this wasn't an intentional strategy. This was an incredibly intentional strategy in a brand new business school case study type laser focus on an emerging market that they had reason to believe
Starting point is 00:18:06 that they could create. Okay, that's origin story number one. Origin story number two, we're going to get into this a lot more. And I didn't even really realize before diving into this, the depth of innovation of what AWS was and what Amazon was doing and led them to it is so beyond anything else that was happening at the time. This is a true fundamental innovation. So let's get into it. Remember from the Kindle Coda vignette, how it was one of those crazy stories about who was responsible for the inspiration for the Kindle. And it turned out it was Tesla founder Martin Eberhardt. Crazy. He invented the first e-reader that wasn't quite viable yet and tried to sell it to Amazon and tried to get investment from Amazon. And Amazon said, no, we'll wait till the world shifts a little bit, different technology.
Starting point is 00:18:58 It's actually something we can own outright rather than funding and potentially having competitors use too. And of course, that would be a few years later and Amazon would create the Kindle internally. So there is a similar sort of figure involved in inspiring the vision for AWS. And that is Tim O'Reilly. And for anybody of a certain age, you certainly remember the O'Reilly programming books, the O'Reilly conferences. And in particular for me, I mean, they were the organization and Tim as the leader of the organization championed the whole idea of Web 2.0. For sure. I mean, I remember first reading, I think, the PHP book that they put out. And then when Web 2.0, this sort of idea of, you know, I can consume on the web, but also
Starting point is 00:19:51 I can post on the web. And that sort of led to social media. And one of the key enabling technologies in all that is AJAX. And I remember reading the O'Reilly AJAX book of, wow, I can use, what is it, asynchronous JavaScript and XML to make dynamic web pages without needing to refresh. That was truly magical at the time. And there were a few core tenants that they sort of defined as what Web 2.0 meant. Part of it was in opposition to Web 1.0, which they considered static. And so Web 2.0 was dynamic, like you're saying, but that wasn't
Starting point is 00:20:25 all of it. Another huge part of what they meant by Web 2.0 was what they called participatory culture and interoperability. And they meant that both users on websites could interact with the website. So you had Flickr, you would upload your photos and you would interact and change the website. Or Google Maps, of course, was such a canonical Web 2.0 project. But even more than users interoperating and interacting with Web 2.0 sites was other developers. Remember mashups, Ben? Like mashing up APIs? Yes. So Web 2.0 mashups were such all the rage and Google Maps was like a core part of this. People would take the Google Maps API and build all sorts of other websites using
Starting point is 00:21:22 Google Maps data and content underneath it, or Flickr had an API. It was APIs, it was interoperability, it was anybody can access. It's democratizing what we've built. Totally. It's so funny to hear all the crypto people today talk about composability. I feel like the old man yelling from tree or get off my lawn person. But it is very clear that people did not experience the 2006 to 2010 era of the exact same promise. But instead of smart contracts or composability on blockchains, people were saying, it's a RESTful API. It has CRUD operations to create or read or update or delete things on a service. So if you're authenticated, then you don't need to necessarily use a web UI. You can just use the API and you can upload a
Starting point is 00:22:12 photo programmatically or you can fetch your entire list of tweets programmatically. It was like all the web, instead of being in these siloed applications, was magically free for data to sort of move about in a utopian way without anybody's capitalist intentions getting in the way and siloing the data all to themselves. So in the early days of all this, I think it was early 2002, Tim O'Reilly flies up to Seattle and meets with Jeff Bezos. And the reason he wants to come see Jeff, they've had a sort of checkered history in the past. You know, O'Reilly has not always been the biggest fan of Amazon. He's a book publisher, obviously, so he has some feelings. But he wants to make the pitch to Jeff that Amazon should embrace Web 2.0 and transform Amazon.com into a participatory website.
Starting point is 00:23:10 And this is a great idea. Being a Web 2.0 company means that you can do business with other companies without needing like a BD agreement in place. You don't actually need a partnership agreement. You basically can just publish your API. You can say, pay as you go, and here's how you pay, and here's how you get an account, and we can shut down your account if we need. But you can get API access to do business with us programmatically through this application programming interface. And it's great. Maybe no one of our two companies will ever even need to talk to each other, which means you can do business with thousands of companies out there, not just a few that your BD people cherry pick. Yes. And Jeff totally gets it. He gets this in so many ways. Amazon.com has this obvious
Starting point is 00:23:57 business use case for APIs and allowing other developers and other websites to access data and content from amazon.com, which is they have a giant affiliate program that's called the Amazon Associates Program. And they've got a catalog of every uniquely identifiable product in the world, certainly in the media space, but at this time growing into many other categories too. So wouldn't it be nice to access that authoritative catalog to fetch an image and display that image on my website if I'm trying to tell people, hey, go buy this CD. Display the CD right there and then share the revenue with Amazon. It's good for both of us if I can do that. So after this meeting, Jeff does two things. One, he completely embraces this idea. Tim and O'Reilly, he invites Tim up regularly to Seattle,
Starting point is 00:24:48 has him speak at all hands within the company, evangelize this idea of Web 2.0 and APIs within Amazon. Two, he starts a new team within Amazon to do just what Tim is suggesting. They build APIs that let any website developer plug into the amazon.com product catalog, do everything you just said, Ben. And the stated goal and mission of this team is to make amazon.com APIs available to developers and quote, let them surprise us with what they build. That same year, you know, this is Amazon, they move fast. They hold a conference for developers in 2002. A total of eight people attend the conference. They announced to the world the launch of this new division within Amazon that is called Amazon Web Services. So to your point here, this is not an important
Starting point is 00:25:49 thing in the world yet. Amazon having a developer conference with eight people there, you look at reInvent now and I think it has 100,000 people who watch the keynote. Very different world. Yes, very different world and very different product. This is called Amazon Web Services, but it is not cloud-based IT infrastructure. It's other developers using the Amazon.com product catalog. And indeed, it lives, Amazon Web Services lives within the Amazon associates program. And that is run by a guy named Colin Breyer, which is very, very fun because Colin goes on to do many things, including recently co-authoring the book working backwards, which is a great book we used for a source in both this episode and the previous episode on amazon.com. But for now, in 2002, Colin technically becomes
Starting point is 00:26:48 the first head of AWS. Wow. And that was just within Amazon Associates at this point, because the whole point in this origin story, the scope of the ambition of AWS was to make available assets of Amazon.com to our affiliates, to Amazon associates, who want to basically fetch images and items from the catalog and have that information passed along when someone purchases something to share some revenue. That was the scope of the ambition based on where it lived in the organization. Now, all of that is absolutely true. There is no element of myth or falsehood to anything in this second origin story here. And now we'll sort of transition from number two to number three together. But what I think is so important about number two, even though it leads to AWS, that is the creation of AWS, but not the AWS we know and love. But it's
Starting point is 00:27:46 this idea of Web 2.0 and APIs that really starts to take hold, at least in Jeff Bezos's mind. And we have not once in this story said the phrase cloud computing or the cloud. We've said web services. And I think people today have heard AWS so many times that they sort of forget that it's a little bit of a misnomer. It's still called Amazon Web Services, but the vast majority of what is happening when customers are paying the ludicrous amount of revenue to Amazon to access AWS is not web services. It is not these restful API endpoints that you use to fetch and post information. Fun sidebar. Do you know the origin of the term cloud as applied to IT infrastructure? Oh, I do not. This is so cool. It started at General Magic. Really? Yeah. How crazy is that? The Apple spin out that invented the iPhone
Starting point is 00:28:46 20 years before the iPhone, as part of what they were doing, they also wanted to have, you know, the internet sort of barely existed. So I don't think they thought of it as the internet, but a distributed, always accessible backend IT infrastructure for all the services that were going to be on the mobile device. And so they started calling what they built for that a cloud infrastructure that the devices could access. General Magic was a pioneer in so many ways. It's amazing. Such a pioneer. Okay, so back now to Amazon. They've launched Amazon web services, web 2.0, you know, blah, blah, blah. Like that's cool, but that's not what anybody is really focused on at Amazon. They're focused on, there are a lot of problems within the company and arguably the biggest
Starting point is 00:29:38 problem is that the code base of amazon.com that shell cap and designed back in 1995 has been, you know, amazing. He made so many great technical decisions that we talked about on the amazon.com episode. He designed it for how websites were built in 1995, which was small teams, not at scale, and monolith software code bases. Everything we talked about in the beginning of the episode. All of Amazon.com at this point, when it's now a multi-billion company, is running on one monolithic software code base. Yeah, I do know after talking to some folks who were early Amazon engineers, around the summertime, they would start looking at what is the server that would be available on the market going into Q4 that is the baddest ass thing we could possibly buy. And they would just
Starting point is 00:30:39 buy the most expensive, souped up server they possibly could from Deck or whoever else. And they would just try to make it through Christmas. Yes, Amazon would do code freezes going into the holidays. And think about this. This is just so far until everything we think about with technology companies now and how things run. And it's all thanks to AWS. You had to do a code freeze heading into the holidays because as you were adding new features and new elements and new teams, and remember Amazon at this point, they've got A9, they're working on search. Lab 126 is just kind of starting up, getting going. They've got all of these teams, huge numbers of engineers and product managers
Starting point is 00:31:22 that are building features, adding features, needing to access various parts of the site. Anytime you add one of those to the monolith software code base, it could break everything. And so you had to do a code freeze. And it gets to a point where, remember, Amazon as a company now is trying to focus on profitability, efficiency. It gets to the point where the company just literally grinds to a halt. There's a lot of good stuff in the Working Backwards book about this, about how hard it became to get anything done and built at Amazon because of this rat nest of complexities involved on the technical and infrastructure side. And as we're articulating problems here that were happening, one of them is, of course,
Starting point is 00:32:09 you're going to tip the server over if you add any additional complexity. The other of which is Amazon is doing the Amazon thing, and they're trying to enter new businesses and new categories. They're trying to grow. And they're trying to grow because the way that they've designed the business, as we mentioned in the last episode, the cashflow.com idea, where they're spending supplier money to grow before they're paying suppliers. Basically, they're investing the float in growth. So they do have to keep growing because they have bills coming due. And so they're continuing to look for new categories to expand into. They're looking
Starting point is 00:32:45 around, they're seeing competition everywhere. So they're just trying to get big fast. So you have the issue of, well, we don't want to commit more code and tip the server over, which of course means you can't launch these new businesses. You can't continue to grow and you can't bring on more customers because more customers is more traffic, which is also going to tip the server over. Let's just take one incredibly illustrative example, the marketplace business. When Amazon figured that out, that was transformative. That was high margin revenue. That was how they competed with eBay. Well, technically to do that, they had to re-architect how the buy button worked on the website.
Starting point is 00:33:30 Now, imagine with a monolithic software codebase, what was involved in that? You just get so slow in your actual software development and therefore slow to ship and therefore slow to innovate because you're afraid of, uh-oh, what did this other team commit to the codebase here? What does that assume? Can I trust the contract that this function had is still true? Or did someone update this function in a way that was tightly coupled to the requirement that they had for their thing? And before you know it, the code is making a bunch of assumptions all over the place. And if you go try to change anything,
Starting point is 00:34:00 it's also brittle that you basically need to talk to people, a bunch of people before you're ever editing code because you might break something. Yes. And this is not just Amazon. This is every internet company. And the first companies to get to this kind of scale were like Amazon. It was this time. There were no internet companies of this scale before. And everybody is realizing you run into this brick wall just from a complexity standpoint when you reach a certain scale. This is a huge problem. Jeff is so focused on this. And not only Jeff, his new assistant at this time is focused on this. His new technical assistant, his shadow, who is at this point in time, Andy Jassy, who was the first. A lot of listeners maybe don't know about this, but anybody familiar with Amazon or
Starting point is 00:34:51 who worked at Amazon knows Jeff's shadow. That's a legendary role to have. Which was a Microsoft thing before. Bill Gates' TA was sort of the blueprint for this. Right. Technical assistant. Exactly. So the reason that Jassy becomes Jeff's first shadow is Jassy, it was a Harvard MBA. He had been a product line launcher. He'd launched music for Amazon. He ended up in the marketing department after that. And then 2000, 2001.com crash, Amazon access the whole marketing department because we're not doing ads anymore. We got to get profitable. And Jazzy was going to get laid off with the whole department, but Jeff liked him. And so Jeff said, I'm going to save Andy. Wow. He's not going to get laid off. I'm going to find something for him to do
Starting point is 00:35:41 while we're figuring this out. Let's take this technical assistant idea from Microsoft. He can come be my shadow and he creates the role for him. And Andy's background is not technical up until this point. He becomes the technical assistant. He's brilliant, but he came in as one of the MBAs who was a category launcher when they were figuring out music and electronics and all these different verticals that they were going into. I can't remember which one Andy launched, but he was the launcher for music for one of those. And I think fairly recently, like within the last five years before this, he had considered a career in the sports industry. Oh yeah, he wanted to be a sportscaster. Yeah, he's like a well-known sports nut, has his basement tricked out as a sports bar,
Starting point is 00:36:24 and almost took that career path. So we're not talking about a distinguished engineer at Amazon who's taking this technical advisor role because they're this technical luminary. It's a really smart guy who's just a very malleable, facile person. Yeah, it was just an excuse to keep Andy in the company and give him a job. But this is now the biggest problem in the company that Jeff is focused on and that Andy's focused on. And this is where all these threads come together. I'm just kind of in awe thinking about this. If I were looking at this problem of my technical infrastructure is ground to a halt, we can't ship anything, communication is so hard in the company.
Starting point is 00:37:09 The natural thing to do, and I think what most companies would do and did try to do at this point in time, is, okay, we got to improve our communication. We need better coordination loops, more communication, tighter communication, more coordination between teams. We need to build out our engineering management discipline here. We need to build out our engineering management discipline here. We need to build out our processes. We're going to get really efficient to be able to solve this complexity challenge. And at Microsoft, when they encountered this problem a decade or two earlier, they invented the program management role.
Starting point is 00:37:38 That was basically the responsibility. It was twofold. It was, there are not enough unicorn people out there who are 10x developers and also unbelievable sort of communicators. And so we'll just hire communication mouthpieces for the 10x developers. We can recruit these four sigma IQ engineer type people, typically terrible communicators.
Starting point is 00:37:59 And so let's just attach a PM to every dev or a PM to every two to five devs. And that way they'll have communication associated with what they're doing. And all the PMs can talk to each other and they can figure out what's happening between these two teams. And then they both go write specs and the engineers write their engineering documents. And then boom, we're off to the races. And the PMs can just keep talking it out to make sure that we're all on the same page.
Starting point is 00:38:22 Now, I don't know this. You may because you were one of these people. That was my job. Yeah. Great. Was the Microsoft PM program, and it was program management, not product management, but was that the origin of the modern Silicon Valley product manager? Well, it is specifically the origin of program management. Microsoft considers product management a marketing function. So it's owned in the marketing org and is much more go-to-market oriented, whereas Microsoft's program manager is in the engineering org. It's on the same comp ladder and same promotion ladder as engineering. That would be a fun, maybe special to do with somebody of like, let's trace the history of
Starting point is 00:39:00 PM in tech in Silicon Valley. And let's be specific about what the P stands for there since it can be very different things. Yeah. Yeah. Okay. So that's what most companies would do. Even incredibly successful, brilliant, smart companies and founders like Microsoft, Bill Gates, et cetera. That is not what Jeff and Andy decides to do. How about less communication? How about less communication? How about no communication? So this is where the Tim O'Reilly Web 2.0 influence comes to play in such a bigger way for Amazon
Starting point is 00:39:37 and for the internet. Jeff has been exposed here, and Andy too as his TA, to this concept of Web 2.0, this concept of APIs. And Jeff just makes this incredible leap and says, we should use APIs internally. And if we make everything a quote unquote hardened interface was the Amazon term for this hardened API interface, we can blow up all of this. We're going to say no communication. You cannot talk to anybody. Everything you do internally must be done via APIs that then anybody else can access whatever they want. They don't have to talk to you. It makes sense. I mean, if you are thinking about your company like an entrepreneurial organization, or perhaps
Starting point is 00:40:30 better put, a group of individual startups all operating in a very nimble entrepreneurial way, well, then you kind of should think about them as separate companies. And if all these startups out there are communicating with each other without a BD person, and they're all just pinging each other's APIs and commerce is flowing and things are getting built, maybe that's the right internal model too for the modern next generation type of company. Academically, thinking around this was in process, but I think Amazon is really the first company that did this in practice. This comes to be called service-oriented architecture. So instead of a monolithic code-based software architecture, service-oriented architecture is this. Every small team, every individual feature is its own architecture, completely separate from everything
Starting point is 00:41:21 else. And it's worth teasing out one is a sort of human cultural thing, which is basically trying to reduce the issue of Metcalfe's law, where every time you introduce a new person, there becomes an N squared relationship to all the people that they could communicate to within the organization. So this is like an exponentially worse issue as more people join the company. So there's sort of this like cultural element that you're talking about there. The services oriented architecture thing is sort of the engineering counterpart to that same mental model of, okay, well, now we actually are going to build each one of these things as a completely separate application that then all interact to create the user facing thing. Yep, the APIs. So there is a legendary, legendary post about this is one of the top all time posts in the
Starting point is 00:42:10 history of the internet. Is this the Steve Yegge? This is the Steve Yegge rant by then Google engineer at the time. This post happened much later, but about this period in time at Amazon, he had been working at Amazon at this time and then moved over to Google later. Shout out to Jeremy Diamond in the acquired Slack for reminding us about this. The funniest thing is the way that this got public, by the way, is he was at Google and they had just launched Google Plus and he meant to post it internally, but it turned into a external Google Plus public thing. And it obviously went viral because if you hear, this person meant to email their own internal organization, and instead they leaked it out on the internet because the product is so poorly designed that this person who was working on the
Starting point is 00:42:54 product could not determine the difference between internal posting and external posting. That is just like catnip. Yeah, the meta story to this post is just as good as the actual post itself. So Steve, in this piece, he starts off and it just illustrates the difference between Google culture and Amazon culture so clearly. He starts off just bashing on Amazon culture like they don't care, but he talks about the hardened interface that that's how Amazon thought about things. He talks about Rick Dalzell. I don't think we mentioned in the previous episode, Rick was an army ranger before going to work at Walmart and that he would just terrorize everybody, all the developers. And he himself was a hardened interface and Amazon is so terrible and Bezos is so terrible and they're
Starting point is 00:43:39 so mean and blah, blah, blah, blah, blah, all this stuff. But it's all just a warm up to the main point of the post, which is where he says, look, Amazon gets everything wrong. We're better at everything at Google. But there's one thing, there's one very, very, very important thing that Amazon kicks our ass in. And it's this. And I think this is like 2010 ish to anchor this time period. Yeah. 2010, 2011. It was whenever Google plus launched. So that feels about right. Steve writes that Jeff and Andy, uh, you know, as part of this sent a memo out to the whole company at Amazon, it was a big mandate and quote Jeff's big mandate when something along these lines, one, all teams will henceforth expose their data
Starting point is 00:44:27 and functionality through service interfaces. Two, teams must communicate with each other through these interfaces. Three, there will be no other form of interprocess communication allowed. No direct linking, no direct reads of another team's data store, no shared memory model, no backdoors whatsoever. The only communication allowed is via service interface calls over the network. Four, it doesn't matter what technology they use. HTTP, Cobra, PubSub, custom protocols, doesn't matter. Bezos doesn't care. Five, all service interfaces without exception must be designed from the ground up to be externizable. That is to say the team must plan and design to be able to expose the interface to developers in the outside world. No exceptions. Six, anyone who doesn't do this will be fired. Seven, thank you. Have a nice day. And then he's like,
Starting point is 00:45:27 of course, for everybody who used to work at Amazon, you know, he didn't say thank you. Have a nice day because he's so mean. And this is crazy at the time. If you think about this sort of edict, I remember building web applications in the late 2000s. And if you told me, and of course, I was writing PHP and querying a MySQL database. And if you told me, oh, yeah, you can't query the MySQL database, even though you have access to it, and even though it's owned by your company, you instead have to use this API to go ping this web service, which has permission to directly interact with the database. I'd be like, what? Are you kidding me? But it'd be so much easier for me to just, and the answer is no, you'll be fired. It's funny, you know, we thought
Starting point is 00:46:02 a lot about in this episode, how do we tell this story for non-technical members of our audience without getting too much in the technical weeds? This is all pretty technical now, but I don't think we can avoid it. This is so important. And the context here is like, let's zoom back out from service-oriented architecture and APIs and all this. What's really going on here? What's really going on here is this is the beginning of focus on what makes your beer taste better. All of this junk we're talking
Starting point is 00:46:33 about, all this technical junk, it's technical junk from the perspective of what actually matters as a business. What matters as a business is the customer experience and new features and customer satisfaction and revenue and profits. And all of this junk was getting in the way. And so this is where Jeff has this realization of none of that makes the beer taste better. So let's standardize, get rid of all communication, API-assize all of it. And then everybody here can spend all of their time just focusing on new features to make the beer taste better on amazon.com. Yep. And the other thing that it is, is a very Amazonian concept of documentation. So of course, they start all these meetings with the six pagers and the PR FAQs where we're not doing
Starting point is 00:47:21 PowerPoint slides. We're just sort of working backwards from this document of what the customer will actually experience. APIs are a heavily documentation oriented way of computing. When I'm hitting your API endpoint, there is a strictly documented set of requirements of things I can send you and ways in which you send information back. Whereas if I'm allowed to communicate directly with your database, you and I in which you send information back. Whereas if I'm allowed to communicate directly with your database, you and I can have a little conversation. You can tell me like, oh, yeah, that field we kind of stopped using for this purpose and started using for this other purpose. So just keep that in mind. There's no keep that in mind in APIs. There's when you hit this thing, you will get that thing back. And so it brings this true precision, hardened belief
Starting point is 00:48:06 in the way in which that thing will respond when I hit it that is documented and you must keep the documentation up to date with the way it actually performs. All right, listeners, our next sponsor is a new friend of the show, Huntress. Huntress is one of the fastest growing and most loved cybersecurity companies today. It's purpose built for small to mid-sized businesses and provides enterprise grade security with the technology, services, and expertise needed to protect you. They offer a revolutionary approach to managed cybersecurity that isn't only about tech, it's about real people providing real defense around the clock.
Starting point is 00:48:44 So how does it work? Well, you probably already know this, but it has become pretty trivial for an entry-level hacker to buy access and data about compromised businesses. This means cybercriminal activity towards small and medium businesses is at an all-time high. So Huntress created a full managed security platform for their customers to guard from these threats. This includes endpoint detection and response, identity threat detection and response, security
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Starting point is 00:49:57 and they rave about it from the hilltops. They were voted by customers in the G2 rankings as the industry leader in endpoint detection and response for the eighth consecutive season and the industry leader in managed detection and response again this summer. Yep. So if you want cutting-edge cybersecurity solutions backed by a 24-7 team of experts who monitor, investigate, and respond to threats with unmatched precision, head on over to huntress.com slash acquired, or click the link in the show notes. Our huge thanks to Huntress. All right, so we're in story number three at this point. One is the apocryphal, got some extra hardware lying around. Two is this idea that Tim O'Reilly brings up Web 2.0 and APIs, and so they start working on the Amazon Associates API. Three is really this idea of, okay, the organization is moving too slow. And a way to speed it up internally, just for our own
Starting point is 00:50:51 step one internal use case, is make it so that the teams communicate with each other via API. But once they start doing that, and obviously before Steve Yigge writes his rant and publishes on the internet, they start realizing, okay, there are parts of this where it may make sense to start being external facing. Because once we get this stuff right, and we've toiled around in the darkness so much trying to get this stuff right, and I don't think it's helping our customers at all. Maybe there are other people out there who are experiencing this same kind of blunt force trauma, just trying to keep their infrastructure up and modern. There's one more small compared to the big ideas, but kind of inevitable as things were going. But one more leap that we should talk about that happens here. Everything we just described so far in AWS origin story number three is related to software engineering and the amazon.com code base. But what AWS is, is abstracted hardware,
Starting point is 00:51:56 IT infrastructure and software too. But the core like S3, EC2, that's IT infrastructure. How do you get from transforming your software architecture to, oh, now I need cloud IT infrastructure? Well, it's kind of the same problem. It's an inevitable outcome. When you transition your software architecture to this service-oriented architecture and no longer a monolithic code base, you know, IT used to centrally plan like we were talking about. We can ship these features at these times and we need a code freeze at that time and we need X capacity and we can forecast that and we can look out into the future. Now with this, you've got all these distributed teams doing God knows what without talking to anybody, IT can't centrally plan anymore.
Starting point is 00:52:47 So what Amazon realizes is they need to do the same thing with IT that they did with software engineering, which is transform it also into an API accessible pool of computing resources versus I'm giving you this server and that's what you got. And you're talking about just internally. If all these teams are hitting each other's APIs internally, then yeah, there has to be some dynamic way that if a whole bunch more load starts coming in and you weren't told about it, you do have to be able to spin up the hardware to handle that. And it's brilliant of
Starting point is 00:53:25 like, well, let's just make that an API too. We can place an API call into IT. They have a pool of computing resources. But much harder than it sounds. Yes. Oh yeah. IT can just become an API. No, no, no, no. This is a multi-year journey for IT at Amazon too. Of course, it wasn't like Bezos just sent the email that Steve Yegi described and everything happened overnight. Yeah. Okay, so what you're telling me then is Bezos gets excited about this. Jassy starts working with him on it.
Starting point is 00:53:58 They're basically translating this idea of the first little nugget that you planted is we should make sure that all of the APIs that we're making available internally, we should sort of like design them in mind as if they could be externally consumed at some point. But you haven't yet told me how does some commercial offering eventually become available
Starting point is 00:54:19 and what is the commercial offering to third-party customers? All right. So we're now in mid-2003. This has been this huge transformative project within Amazon over the last 18 months. Jassy's been working a lot on it as Jeff's TA. And Jeff's like, okay, Andy, it's time for you to go back out into the company. You're done being my TA.
Starting point is 00:54:46 You got to go become a leader of something within the company. It's almost like an echo of Jeff and David Shaw back at D.E. Shaw. They start thinking together like, okay, Andy, what are you going to do? What's a new thing you're going to go lead within Amazon? Yep. Andy's probably happy he didn't leave Amazon, I think. And they come together to this idea of, well, maybe there's an opportunity to take the API-based IT infrastructure that we're developing here and offer it to third parties. So the legend goes,
Starting point is 00:55:24 Andy puts together a six pager. And this is the official Amazon legend. You can read about stuff on aboutamazon.com. Yep. It's in official Amazon documents. You know, everything in Amazon happens in written narratives and six pagers. He writes the six pager. Famously, he has to tinker with the margins and adjust them to fit everything onto six pages. He can't fit financial projections on there. So there's no financial projections in this document. And then he whiteboards them out on the spot in the meeting with the STM and the board where he's proposing this big grand vision to take over Amazon Web Services, relaunch it with this new vision of being cloud IT infrastructure.
Starting point is 00:56:05 In the document, there is an ask, a proposal to hire 57 new people to go pursue this initiative. Andy talks about he's so nervous going into the meeting. This is such a huge career moment. He's asking for 57 people. Nobody asks for 57 people. It's a ballsy move. He's risking everything. And Jeff loves it. Board loves it. The S team loves it. It gets approved. And I think all of that actually happened or happened in some way, shape or form. Andy, literally, we mentioned Colin Breyer, who was running AWS until this point. Andy and Colin swap places. So Andy goes in, takes over AWS. Colin becomes Jeff's next shadow. Oh, I didn't realize that. Andy right away took over the publishing of images via the Amazon Associates API, that sort of fledgling AWS. Either that happened or this is part of the Amazon corporate history, hand-waving, you know, all of it just went smoothly. Colin becomes Jeff Shadow. He then goes on to run IMDB when Amazon
Starting point is 00:57:18 acquires IMDB. And then later, he would leave Amazon team up with Bill Carr, who ran Prime Video. And then they write Working Backwards. And I didn't realize this. This is brilliant. They now have a consulting firm together as part of Working Backwards to help companies implement the Amazon culture. It's great. Perfect.
Starting point is 00:57:38 Freaking brilliant. So back to Andy, he gets approval. He's going to hire 57 people. He recruits Adam Salipsky to come in, join the company. Adam, of course, he gets approval. He's going to hire 57 people. He recruits Adam Salipsky to come in, join the company. Adam, of course, would later leave AWS to become CEO of Tableau and is now back at AWS where he is now CEO of AWS. So I watched every single reInvent keynote to prepare for this, which I will tell you, that is a lot of IT conference keynote watching. And the most
Starting point is 00:58:06 recent one is Adam Selepsky. And it's like 10, 11 years of Jassy up there on stage. And you finally get a different voice. And it's a little bit jarring, especially when you're mainlining them all back to back when it's suddenly not Andy Jassy. But yeah, Adam is the guy now. Yeah. Do you know who else was in that first wave of external recruits who come in to join AWS? I do not. Jeff Lawson. Oh, no way. The CEO of Twilio.
Starting point is 00:58:31 Yes. Wow. Which totally makes sense that Twilio would come out of AWS. Yes, of course. So yeah, I think all of this really happens. Andy does write this doc. He does take over AWS. He absolutely builds and leads AWS from what it was, which was very different into what it is today. But I think there's a little more to the story, too. It's a convenient narrative, and it's also a little bit odd that this sort of idea could come from someone who wasn't in the muck.
Starting point is 00:59:06 Yeah. It's actually a really good interview that Andy does with the Harvard iLab in 2013 that's on YouTube. They're talking about the origin of AWS. I think the topic is intrapreneurship at companies, which, my God, the most disgusting word of all time. But Andy, in the talk, he's like, well, you know, we had to decide, my God, the most disgusting word of all time. But Andy in the talk, he's like, well, we had to decide as part of this vision document and the discussion around it, how do we launch this? Do we pick just one service, one kind of IT primitive and launch with that? Or do we put together a whole bunch of things and launch them all together? And he says what they ended up doing was they got a tiger team
Starting point is 00:59:45 together of the 10 best technical minds inside the company, and they deconstructed all the major web services, web applications of the day, Amazon.com itself, Google, eBay, all the, he doesn't mention them by name, but I assume the other big web services of the time, big web applications, and figured out what you would need to re-architect those services based on this new cloud IT primitive infrastructure. And so they come up with a list, they decide you need storage, you need compute, you need databases, and you need a content distribution network like what Akamai was to be able to recreate any internet service of scale. I love that you say was like what Akamai was. Yeah. Story for another day, perhaps. So they decide, you know what? We can't fulfill
Starting point is 01:00:37 our promise to developers of you can build web applications of scale with us unless we launch with all of those services. So we're going to build them all. And that's why we need 57 people. Andy would later say, this is a great quote, and this is absolutely true. He says, if you believe developers will build applications from scratch using web services as primitive building blocks, then the operating system becomes the internet. And that's so true. That's what AWS is today. So they're going to launch with everything they need to build a whole operating system. And this is where the official narrative just completely falls apart, because that is totally not what happened. Not even a little bit.
Starting point is 01:01:18 Nope. And in fact, I can recall personally using Amazon S3 for something I was working on and there was no EC2. Yes. So unlike myth number one about AWS origins, you couldn't just take excess amazon.com IT capacity and externalize it. They had to go build all this from scratch as external services. It takes a couple of years to do that for everything. And in fairness, you know, maybe in defense of the official narrative, they do start working on all of these suite of services all at once. And it just takes a while to get them all built. That probably is true. But yeah, S3 is the first service to launch by itself in March 2006. And let's talk about it. It was an independently useful thing. So S3, simple storage service, it's a place that is available on the internet. You don't have to
Starting point is 01:02:11 think about where it is. It's in the cloud. And you can dump images there if you're an application developer and then elsewhere from your application or other applications or no applications. If you just want to access the image directly by URL, you can access. And it's not just images, it's anything that you want to store up there. And it's this wonderful, magical, amazing thing where I don't have to buy a server, I don't have to configure a server, I don't have to rack a server, I don't have to think about maintaining a server, and I only pay as I go, and it is insanely cheap. Yeah, S3 launches in March 2006. EC2 launches a few months later in August 2006, I think in beta in August 2006. And what is EC2? EC2 is Elastic Compute Cloud,
Starting point is 01:02:56 which is the compute counterpart to the storage part of AWS in S3. And a simple way to think about EC2 is if you were a web application developer at the time, like I was, and you were writing stuff and you were sort of running it on local host on your computer, and you had previously been deploying it to some server at a data center
Starting point is 01:03:15 that you could tell net to and ping and see it had an IP address, well, you could basically spin up an EC2 instance and treat it kind of like that, except it didn't have persistent storage associated with it. You could think about it like a computer without a hard drive that happens to live in the cloud an EC2 instance and treat it kind of like that, except it didn't have persistent storage associated with it. You could think about it like a computer without a hard drive that happens to live in the cloud and is yours until you stop using it. It's your processor in the cloud. CloudFront,
Starting point is 01:03:34 which is the content delivery network, the CDN, the Akamai part of the puzzle piece, that launches in 2008. And the first major database offering, RDS, the relational database service, doesn't actually launch until 2009. And importantly, RDS, it wasn't like you just start using RDS and now you don't have to use any of the stuff you've been using before. RDS would run the database that you were already using. So I can't remember if it actually launched with Postgres, but assume you're normally self-hosting Postgres on your server, or you have a separate database server that you're used to running that runs Postgres. Well, now you use RDS and it runs Postgres and all your queries work and you can treat it like it's your own database server.
Starting point is 01:04:19 So that's sort of the most obvious crack in the official narrative of the AWS origin, which brings us to the fourth origin story of AWS, the dissenting narrative, if you will. At this point, the compass in story number one was like 180 degrees off, and then in story number two, it got 90 degrees off. We're fine tuning now. Story three is basically right, but probably doesn't just include the full set of people that could have been written into the narrative. And I think story number four is basically right too, but three and four are kind of the same. Success has many fathers. Yes. Concurrently and separately to everything we just said in story number three, Randy Jassy working on Jeff's TA on this big problem, writing the vision doc, the business plan, all that, hiring 57 people. In 2003,
Starting point is 01:05:13 a network engineer at Amazon named Benjamin Black is working on the IT architecture transition that we talked about. And he's working with Chris Pinkham, who is his boss, who in fact oversees all of network engineering within IT at Amazon. And Chris reports to Rick Dalzell, the CIO of Amazon. So the two of them, Benjamin and Chris, they write a six pager about how they actually are going to use that same architecture to sell virtual compute servers as a service to third-party developers. And indeed, Amazon could do that. Now, here's where things get murky, because that document definitely does exist. This idea that most of it is focused on here's how we're going to execute our plan. And also we could sell that infrastructure as a service. Here's where
Starting point is 01:06:30 Ben Black and his blog posts on the subject and then in future interviews he gives with Network World and others are very insistent that they then showed this to Jeff Bezos. The proposal made its way to Jeff Bezos. Yeah, I think first to Rick and then to Jeff. And he greenlit their project. Yes, separately from the rest of AWS. And what I can't tell is, did this before it got in front of Jeff get merged into Andy's proposal and it was sort of greenlit as one big thing? Or were there actually two different concurrent efforts? We're going to tell the story, and then I have some thoughts on all this.
Starting point is 01:07:09 So Chris is actually from South Africa. And right around this same time, he and his family want to move back to South Africa, leave Seattle, move back to Cape town in South Africa. So he goes to Rick, his boss and says, Hey, I'm actually going to leave and move back, move the family back. And Rick is like, Oh no, no, no, no. We're in the middle of this huge architecture transition. This is a key moment in the company. You are a super valuable person at the company. What if we do the same thing we're doing in Palo Alto with a nine and Lab 126? We'll set up a new Amazon subsidiary in Cape Town, South Africa that you can lead, and then we can retain your talents and we can figure out what that new subsidiary will do. So Chris is like, oh, okay,
Starting point is 01:08:00 that sounds good. Chris and Rick start thinking about this and they decide, well, we just had this idea, Benjamin and I, in that paper we wrote about selling virtualized servers to third parties. What if we work on that at the new subsidiary? So they do. Benjamin doesn't come along. But Chris and a really, really great engineer named Chris Brown. And from what I can tell, this is where Ben Black's involvement ends, where he was part of pitching the idea, but is not actually a part of building the thing that they're going to build in South Africa. Yep. So Chris and Chris go off to South Africa. They start working independently on this compute server idea, and they do. That becomes EC2. It's that team in South Africa that builds EC2. Bradstone writes in the Everything Store, quote, EC2 was born in isolation with Pinkham talking to his colleagues
Starting point is 01:08:55 in Seattle only sporadically, at least for the first year. Pinkham later said that the solitude was beneficial as it offered a comfortable distance from Amazon's intrusive CEO. Quote from Pinkham, I spent most of my time trying to hide from Bezos. Pinkham says, he was a fun guy to talk to, but you did not want to be his pet project. He would love it to distraction. Hilarious. You can start to see even in these very public, reasonably nice quotes that there's enough tension between Chris Pinkham and the Bezos-Jassy leadership that even in the official Amazon things that they put out about the development in South Africa, like Chris Pinkham's name is sort of nowhere to be found even in this South Africa
Starting point is 01:09:39 specific blog post about the history of EC2. there's clearly chafing between Chris and the leadership. Yep. In Andy Jassy's infamous one-star review of the Everything Store on Amazon.com, in one of the several passages where he talks about how Brad had it all wrong, here's a quote from Andy. The vision document proposing the AWS business and outlining the initial set of services for AWS, including our compute service EC2, was finished and presented to the executive team in September 2003. I wrote the document and was lucky to have the help of several people in putting it together. This was about a year before Chris Pinkham moved to South Africa to build the initial version of EC2. Chris played
Starting point is 01:10:26 an integral role in the definition, team building, and product building of EC2, despite leaving before EC2 was launched. So clearly there's some bad blood here, but my thoughts. I want your thoughts too. I just find this whole thing ridiculous because A, of course it doesn't matter. But the most ridiculous thing is that what I think actually happened here, which is there were multiple teams working on multiple related things within the company. That's how Amazon prides itself on running. Decentralized innovation. That was the whole point of this whole freaking exercise was decentralized, let teams innovate. What's Jeff's invent and wander, you know, is the kind of mantra of him and the company.
Starting point is 01:11:11 I think that's what actually happened. The official version now of the AWS history of it was all centrally planned. It was all in that 2003 document. That just seems sort of silly to me and counterproductive. Yeah, I agree. The other thing that becomes clear is it's really not about the idea. It's about the execution. And I know this is a trope. So to make it a little bit more specific, it can be about the idea if you define the idea as the hundreds of micro ideas that comprise the main idea. But if you're saying the idea is something articulatable in a sentence, well, that's pretty much worthless. And maybe even in a vision doc, it's about the thousands of micro decisions you make while
Starting point is 01:11:57 executing it and actually doing the work to execute it that sort of ends up mattering. But history is written by the victors, so we're seeing some of that play out here. The other thing that's very clear is Andy Jassy is just a brilliant strategist and fantastic leader. And so of course, someone like him in the organization would end up actually running it. So I don't even know why there's dispute over, well, it was my idea. It's like, well, who cares? Who's going to end up turning this thing into a world-changing business? You know, you had that great playbook theme and takeaway from the Amazon.com episode that I think you posted as a clip on Twitter and LinkedIn that went so viral and people who were original Amazon employees loved it, which was your idea
Starting point is 01:12:39 that Amazon was a pathfinding algorithm. Yeah, it was brute forcing its way through a maze to eventually find the correct way by just gathering data, launch stuff, gather data, tear it down, start again. Yep, go through the maze, hit a dead end, backtrack a step or two, go take another path. And I think that actually is also how AWS launched. Early on, but I want to get to that in my playbook
Starting point is 01:13:04 because I think it actually contrasts that in some ways. Ooh, okay, fun, fun, fun, fun. All right, so it launches. Last thing to highlight here is the importance of the primitives. I don't know how intentional it was in the moment, but it became something that later on would become hugely important to them,
Starting point is 01:13:20 which is that they truly were unopinionated about this as a platform. They said, we're going to launch with primitives. It's the most basic story. That's the most basic compute. It's the most basic way to host your databases. It's the most basic CDN. And we can't wait to see what developers build in an innovative way with our absolute bare bones architecture that would go on to be called infrastructure as a service, as sort of a category. And they, again, I do not know
Starting point is 01:13:50 if it was an intentional thing or not when they were first launching it, but they did not say, let's try and build a new OS, a new programming paradigm. No, no, no, no, no. We're just going to give you super basic building blocks and you run with it.
Starting point is 01:14:05 So all that's on the technical side. We've been spending a lot of time there. We've alluded to this, but let's talk about what a radical innovation this was on the business and market side. I've got a great quote here. So when S3 launched, probably at the same time that you were playing around with it, a truly world-class, fantastic engineer at Microsoft at the time by the name of James Hamilton, who's now an S team member and SVP distinguished engineer at Amazon because of what he saw with AWS. He wrote on his personal blog about trying out S3 when it launched with a personal project. So here's a quote from him. What was even more disruptive was a credit card was all that was needed to provision storage. There was no required proposal for financial approval. There was no RFP, no vendor selection process, no vendor negotiation, and no data center space needed to be found. I could just sign up and start working. From deciding to write the app to it being up and
Starting point is 01:15:11 running on the internet was measured in days, and after debugging and testing extensively, the end of the month rolled around and I got my visa bill. Of course, I knew abstractly that S3 was disruptively priced. But when I saw that my bill for the entire development and test of this application was $3.08, it just seemed wrong. Once development was complete, I was still storing all the test data in S3. So the following month, I got a bill for $0.07. So no joke, David, every month I get a bill from AWS for like 71 cents. And I have no idea what old project it was for. But it's one of these things where it's like, it's priced so dynamically. If it was a big successful project holding a lot of data, then you know, it would be expensive. They actually have pretty good margins on S3 and on bandwidth and some of these things. dynamically. If it was a big successful project holding a lot of data, then it would be expensive.
Starting point is 01:16:09 They actually have pretty good margins on S3 and on bandwidth and some of these things. But because it was an abandoned project for which I do not know what the email address to log into AWS is from whatever team I was working on, I kind of just don't care. Could you imagine back in 2006, let alone even probably today, Oracle or Microsoft or IBM or HP or you name it? They all have six, seven and eight figure contracts. There's no way that they're going to invest in, hey, let's let people pay with a credit card and service this tiny little market. And we'll charge you $3.08. This was unbelievably world-changing, truly world-changing. This is how Dropbox, Instagram, Airbnb, Uber, Zynga, all of these companies get started. I remember being at all these startup weekends and all these hackathons where the audience, the family members who came, the venture capitalists who came to be the judges. It was blowing the audience's mind how fast people could stand something up in 48 hours
Starting point is 01:17:10 because suddenly you didn't have to spend $5 million in three months figuring out what data center you were going to put something in. You actually could just have an idea and get it out there within two days. This birthed that movement. We all lived it. Rover.com that, you know, we were all in various ways part of, adjacent to, next to our great friend and mentor, Greg Gottesman. He was a VC. He wasn't technical. You know, it got built in a weekend. Yeah. Phil Kimmy. Phil, our buddy, built it. Yep. Amazon, of course, embraces this. In fall of 2007, they start the AWS Startup Challenge and they host it first in September 2007. They didn't win, but do you know who was part, a contestant in that very first AWS Startup Challenge? Is it like Teach Street? Like it's going to be some Amazon Inside Baseball?
Starting point is 01:18:01 Oh, even better. Justin.tv. No way. Which of course would pivot into Twitch. Which Amazon would then buy. Of course, Amazon would then buy. Wow. For like the better part of a billion dollars, right? Yep. I don't have a good sense of how Twitch is doing now. I assume Amazon got a good deal on that almost no matter what. We got to find the right way to revisit that. For sure. But that is a great use case. Like Justin TV early, I mean, they were using a lot of bandwidth to stream video. They were using a lot of S3 to store. It was a great use case. And man, did Amazon embrace this sort of thing? This is probably one of the biggest keys to success or sort of playbook themes for why AWS became successful. They realized how perfect this was
Starting point is 01:18:48 for startups. They realized how hard it would be for large enterprises to just wholesale move over. They realized that was not going to be the first beachhead market. But for startups who were building something from scratch, who could go on to become 50 plus billion dollar companies. My God, let's get them on AWS. And the blitz was so impressive. I mean, I remember the first time I met Dave Chappelle, who was doing developer evangelism for AWS early with Jeff Barr and so many other folks there. It was just a breath of fresh air where every happy hour you went to, there were AWS people who were giving you tons of free credits, who were helping introduce you to other people for your startup. They all thought about themselves
Starting point is 01:19:30 as active participants in the startup community. So it just became this obvious default that you would build on AWS because it felt so ingrained with how you make startups as you start an AWS account for the thing that you're going to build. There's a famous Andy Jassy refrain that you hear with how you make startups as you start an AWS account for the thing that you're going to build. There's a famous Andy Jassy refrain that you hear at basically every reInvent where he talks about, first, there were the enterprise cloud doubters
Starting point is 01:19:56 who said, oh, maybe this is good for startups, but it's no good for line of business applications. It's no good for mission-critical applications. And oh, maybe it'll be good for my test environment applications. It's no good for mission critical applications. And oh, maybe it'll be good for my test environment or my dev environment, but I won't be able to run enterprise grade stuff there. I think his line is, at first it was that nobody thought you could run a real application. It was only like what James was building, like a personal test project. And then it was like, oh, well, you can run in AWS, but real enterprises wouldn't do that. And then it was like, well, as a real enterprise, we can run non-differentiated,
Starting point is 01:20:32 non-mission critical stuff in AWS, but we're not going to put our mission critical stuff in AWS. That's going to be on-prem. And then it was like, oh my God, take my money. Right. So I think there's this interesting, obvious first beachhead of customers that are startups. But when you think about the enterprise adoption and how eventually now, you know, your bank's application is on AWS and everything is moving to the cloud or $120 billion a year of revenue has already moved to the cloud of at least Microsoft, Amazon, or Google. So there's these sort of three prepositions of the cloud. There's people building on the cloud, which to me, that's lift and shift. And that's really like a phrase that the cloud industry uses for, hey, you were running some local databases, you had some local storage,
Starting point is 01:21:21 you basically had your data center, and you just want to lift that up and shift it over and drop it at Amazon's data center. And you're not going to take advantage of any cool stuff. You're just going to now run your stuff in Amazon. So the benefit that you get of that is you only pay for what you use. You don't have to pay the big upfront costs and you don't have to maintain it yourself. But otherwise, exactly the same thing. Jassy actually at the first reInvent in 2012, as part of his presentation, he has a great slide on this where he talks about the six reasons AWS wins versus traditional infrastructure for enterprises. And it's exactly what you said. It's one, you're trading CapEx for OpEx, which is great. You can take all that expense in every income statement every year as opposed to capitalizing it. Two, you're getting lower OPEX than you could on your own thanks to AWS's economies of scale. They're getting better deals on their servers, so they're passing those along to you. Yep. Three, you don't have to guess on infrastructure capacity ahead of time. AWS is elastic. As you need more, it scales up. As you need less, it scales down. And that's actually four. It can scale down when projects don't work. You're not stuck with legacy leftover infrastructure from things that don't work.
Starting point is 01:22:36 Five, engineers can focus on writing code, not installing infrastructure, focus on what makes your beer taste better. And then six was you're instantly global on AWS versus when you run your own on-prem data centers, you're like wherever your data centers are. Which sounds nice. It's not quite true. It's not one global availability zone. Actually, interesting point. That was the original premise. They thought they were going to abstract that away and you were going to imagine sort of a global S3 data center. And when you deployed it, it just went to all of the data centers. And then they quickly realized we're going to have so much traffic from so many customers that we're going to consume WAN. We're going to consume the internet's bandwidth, replicating unnecessarily.
Starting point is 01:23:17 And so there is, you do not run globally by default in every single... Anyway, yes. And so then there's this step two, which is building in the cloud. And that's taking advantage of using things like the relational database service, that RDS, that very early thing that they launched, which is, hey, this isn't just your exact same code and your exact same infrastructure, but in our data center and build differently. You're actually taking advantage of a cloud native service. And then there's building for the cloud, and that's the future. And that's things like Lambda and DynamoDB. And if you think about Lambda,
Starting point is 01:23:50 for folks who have not done this or heard of the serverless movement, it's this idea that you don't even need to reserve an EC2 instance or deploy code to it. You just write your code, and then when you want to call it, a thing just spins up for a few milliseconds, runs your code and spins down. And you were never aware of its IP address or where in the world at
Starting point is 01:24:11 what you just know that your code executed. And so that's really like building for the cloud. You're completely architecting your application differently to take advantage of this very different world of computing the cloud offers. If we rewind to origin stories number two and three of the big monolith software problem and that all the engineers and product teams in Amazon and every other internet company were spending all their time focused on not making their beer taste better,
Starting point is 01:24:41 undifferentiated heavy IT lifting in the beginning, really what happened is probably development teams in those days were spending like 70% of their time on infrastructure and setup and 30% of their time on software development. And then AWS shifted it to, okay, spend 70% of your time on software development and 30% of your time on worrying about our APIs and your infrastructure. This for the cloud, you know, Lambda, everything is like, that's taking it down to zero. Right. That's the goal, at least. I think all this stuff sounds better in principle than it actually ends up in practice. But yeah, that's the idea. Now, AWS, in its earliest days, let's call it the first couple of years, was really startup-focused.
Starting point is 01:25:27 New applications from whole cloth that want to use our infrastructure-as-a-service primitive building blocks. And they very quickly realized, well, if we're doing infrastructure-as-a-service, it also does enable this lift and shift thing. So as long as we work like hell to satisfy the compliance requirements and availability requirements and uptime and all this stuff, replication requirements of enterprises. Get SOC 2 audited with Fanta. There you go. Perfect. So very quickly, AWS could serve these two markets of startups and the lift and shift
Starting point is 01:25:57 enterprise. Now, another way you could have designed this is instead of doing this infrastructure as a service and these primitives, you could say, let's think about the far future, the lambdas of the world. And we're imagining now in 2006, why don't we just build that sort of stuff to start? Let's change the development paradigm. Let's build the platform of the future, that platform will live in the cloud. That platform is not Windows of the past or the App Store of the current day, where it was just sort of coming. That platform of the cloud, why don't we start writing the brand new paradigm today? And there are a couple other big tech companies that took that approach at first that were completely wrong. And the unfortunate thing
Starting point is 01:26:46 for Microsoft and for Google, who really started at this platform as a service layer, was you basically didn't get the startups because you didn't have a mature platform yet that people were excited to build on and understood how to build for, but you also didn't get the enterprises because there was no ability to lift and shift. And so if you were creating a platform as a service in the late 2000s, you're really a decade early and you're building for a market that doesn't yet exist. Okay, so let's talk about what happens because this is just, man, Amazon ran the table on maybe the most important market of all time. For like the first five years with nobody competing with them.
Starting point is 01:27:27 It's incredible. So 2006 is when the first services launch. 2007, 2008, that's when these startups are getting started. Airbnb, Uber, Instagram and the like. And they're becoming big, but they're not yet at the scale that they are today. 2009, Netflix becomes a customer. And how crazy is this? They had already built
Starting point is 01:27:47 their own in the last like three years, basically cloud internally in order to stream video, which was originally, I think, streamed through Silverlight. They had this big partnership with Microsoft. That's right. Oh my God, that was so terrible. Yes. I think you had to use IE to view it. It was bad. But they had just invested a bunch and then did an about face and said, oh, we were wrong. Actually, we're going to use AWS instead. We're moving all of it to AWS. And I believe Netflix is still to this day, I think, 100% on AWS. I don't know about 100%, but yes, they're still an enormous customer. Reed Hastings was actually the very first guest interviewed on stage at the first reInvent in 2012.
Starting point is 01:28:28 I think in that interview, if it wasn't that one, it's another one around that time. He talks about people say, Reed, you compete with Amazon.com. Aren't you worried about being on AWS? And he's like, no, I'm not worried at all about being on AWS. It is legitimately the smart infrastructure decision for us to make. Which that was such a feather in Amazon's cap. They've had two big feathers in their cap. There's that one and the CIA one, like it's secure enough for the CIA to use, so it should be secure enough for you. And that was a few years later. But the Netflix one, I mean, a lot of people were afraid to use AWS early on because they felt like they didn't want to do business with Amazon if they were a retailer, like they didn't want to do business with Amazon if they were a retailer, or they didn't want to do business with Amazon if they were in video, or any of these things that Amazon was competing on. And Reed getting up on stage and saying this
Starting point is 01:29:14 matter-of-factly and so forcefully was him saying, you can trust that AWS is different than Amazon. Okay, so why is Reed and Netflix making this decision? Why then do a bunch of other customers do this? And Microsoft, let's put Google to the side for a minute, but IBM, you know, Oracle, all these legacy technology companies, why are they asleep at the wheel here? It's a disruptive pricing model. And let's not loop them together, because I actually think it's worth analyzing each company failed to claim this opportunity for unique reasons. Okay. So the first couple it's worth analyzing. I think what you're pointing out is these old server companies. So the IBMs and Oracle on the database side that made these ridiculous gross margins, and they sold you this complete proprietary solution.
Starting point is 01:30:08 Yeah, 80% gross margins. Totally. And they would sell that to you, and they would install it in your data center, and eventually they would hand wave and call something cloud. Private cloud. Private cloud. They might do it in their data center, they might do it in yours, but it's effectively the same thing, and it's sold on a license basis that comes with auditing. Amazon has this ability to literally meter your usage and then charge you exactly what you need to be charged. Whereas this old model of buying a bunch of Oracle licenses and deploying them on the servers in your data center, you just get these
Starting point is 01:30:42 audits every once in a while that were like, okay, cool, well, we sold you the license and you bought this many licenses. We'll show up and make sure that you aren't misusing this thing. So they weren't going to change that business model. I mean, it was a license to print money. Amazon targeted gross margins and operating margins for AWS in the 20 to 40% range. Which felt like a 10x and a 20x for them, but was unattractive to the traditional. Right. This is the perspective. Amazon.com is operating on like a 2% operating margin basis. For Amazon, they're like, oh shoot, we get 10 to 20x our margin basis with this new business. Awesome. But that's still less than half of the margin that
Starting point is 01:31:26 the old school guys are getting. And the old school guys are certainly fat and happy on their operations. Whereas Amazon knows how to run everything they've ever run as this unbelievable lean machine because they're so COGS sensitive on everything. So here's another thing, though. You mentioned, call it the Oracles, the IBMs, whoever, they'd come install this software on computers for you or in their data centers, call it private cloud, whatever. They'd install Oracle Database version 19. And then two years later, you're paying your maintenance costs. You're going to pay an upgrade cost to go to Oracle Database version 20. And then you're going to go a couple of years later to version 21.
Starting point is 01:32:07 And you're going to pay a bunch of money every time you migrate. Right. Why would you give up this annuity that you have? Right. Well, cloud infrastructure, it's always up to date. There is no version. Whatever you're using, you're using the latest stuff because it's always. and then even more than that, Amazon gets to constantly iterate versus doing these Windows XP every four years, we're going to ship a big update. No, no, it's just constantly changing. Yep. Okay, so that's super old guard that IBM's and Oracle's, which is very funny. When you watch all these keynotes. I wonder if anyone's ever watched them all mainlined like I did, because I have this unique perspective seeing them all so close to each other.
Starting point is 01:32:45 They used to, on stage, refer to IBM and Oracle in a tongue-in-cheek way. They would refer to a New York company, and it would be IBM's logo, but it would say New York company. And Oracle, they would go as far as to say San Francisco company, and then they might make a reference to a super super yacht or like sailing or something to like really drive the point home. Around 2016, 17, they totally did an about phase and they just start directly attacking them. And they start directly attacking Microsoft too. Because I think Microsoft went from in the early days, someone where Amazon looked at them more as a partner,
Starting point is 01:33:21 like we're happy to run Microsoft stuff on your AWS instances. And now that Azure has actually been an extremely viable competitor and made a big, big comeback. They're the best competitor to AWS by far. Amazon now loves attacking SQL Server licenses and stuff like that, that Microsoft, of course, comes in and audits just like the old guard for. So let's look at Microsoft, though. Let's think back to the mid-2000s, because this really should have been their business to take. They should have figured this out. But there were essentially two problems going on at Microsoft.
Starting point is 01:33:55 One is that the Windows group just had too much power. And between them and the Windows server people and the SQL server people, the goal of those groups was to get customers to do more with this idea that people thought was going to be big for a while of PCs taking over the data center and PC operating systems becoming the data center operating system. And really the goal was sell more Windows Server licenses. And that was a great business. So anything that looked too much like that within Microsoft got gobbled up in an internal power struggle because it could look like it would cannibalize that thing. This was probably happening when you were there, right? Yes. It was sort of over by the
Starting point is 01:34:31 time I was there. 2012 is when I arrived. But they did eventually realize that they had to make a big bet on Azure and totally separate from Windows Server. And so this, we should give Balmer credit because he did see this. So they replaced the leader of that organization at the time of Windows Server and tools business with Satya, who would eventually, of course, become CEO and then really double down on the cloud strategy. But they realized, okay, Azure needs to be a thing that's kept separate and has CEO sponsorship and can sort of escape the Windows Server thing. But their second problem is what we were talking about earlier. They launched this thing called Azure Cloud Services, which they've now basically deprecated, which was a platform as a service
Starting point is 01:35:15 approach. Microsoft had the golden goose. They had all the IT relationships. What they should have done is gone to everyone that was using Windows Server and say, great news. We have primitives in a data center that you can lift and shift to, much like how Azure works today. You can trust us. You already pay us. We'll make this a part of your enterprise agreement. But Microsoft got clever and they thought, you know what? The Win32 runtime, the.NET platform, we're a great platform company. Developers want to build for the things that we make. So let's make the next generation set of APIs and platforms for building great cloud applications. And they just totally did not recognize the magical thing they had in front of them, which was all the customers and all the
Starting point is 01:36:00 distribution, who over the next five years would slowly dribble out and start their new stuff on AWS while Microsoft was still figuring out its strategy. They got caught in that middle of people building brand new apps, didn't know how to build for their platforms, and they didn't want the lock-in. That's still a big thing in cloud. Oh, don't get locked in. You want to be multi-cloud. And they didn't make it easy for their existing customers to lift and shift. So Microsoft, while they're in a great place now and have figured out an interesting strategy, and we can talk about kind of the bear and bull later, they just had five years of watching pitches go by. Yeah. Oh, it was such a whiff. Okay. We talked about Oracle and I want to come back to Oracle in a minute. We talked about Microsoft. What about Google? So Google's the third place.
Starting point is 01:36:46 Amazon's got 35, maybe 40%. Microsoft's got 20 to 22%. Google's somewhere around 10%. Which that Microsoft having 22%. Very impressive. That's an enormous win. Totally. Here's my sort of take on Google. They accidentally became a business. They launched as a project, and then they figured out this business that became unbelievably cash generative immediately. The nature of their business being search and feeding all the data directly in to make the results better is that they instantly became a consumer-sponsored monopoly. Totally legally done competitions just a click away, but they're the best experience.
Starting point is 01:37:26 So they just have these unbelievable reinforcing effects of becoming a monopoly. So they're a super high gross margin monopoly in the biggest market in the world, which is people wanting to use the internet.
Starting point is 01:37:39 And they're the front door to the internet. So their entire existence, it's not that it's been easy because it's been a computer science challenge. It's been very academic. And they've never had to go into a hard business. I don't know what Google's advertising margins are, but that business probably runs at, I guess it depends if you put sales above the line or below the line, but 80% gross margins. A 30% gross margin business is not particularly attractive to them,
Starting point is 01:38:03 nor are they good at sales. I know they're getting better, but the narrative at the time was they made this G Suite thing, which at the time was called Google Apps, but no one would buy it. So they ended up giving basically all of it away for free to consumers forever. Google Docs and Gmail and everything. It was the best thing to use, and they couldn't figure out any way to sell it to enterprises. So they didn't have the competency of enterprise sales the way that Microsoft did. They didn't have the ability like Amazon to operate in these really hard businesses, eking out every last dollar. And so it just kind of looked unattractive. Meanwhile,
Starting point is 01:38:39 they actually had the best technology for it. They actually operated these big data centers and this really novel way of networking all the computers together in order to pull off search. And they were sort of inventing machine learning before machine learning. So a huge value prop of the cloud now is all your data's in the cloud.
Starting point is 01:38:58 And that way you can use a bunch of stuff that Google invented, TensorFlow, Kubernetes, to run your stuff in the cloud. This also was kind of theirs to win, but they didn't have the sales and marketing muscle, and they didn't, I don't think, have the iron gut that Amazon had to go do something, kind of grind it out and hard. Well, I think they also made the mistake that you were originally talking about. I thought you were talking about Google, and then you said it was Microsoft, too, of building too far in the future.
Starting point is 01:39:28 I think Google made that mistake, too. Yep, that's totally true. I mean, the first foray was Google App Engine, which was in no way infrastructure as a service. It was not primitives. It was, I think you can write in Python or Java, and it was a specific API surface for GAE, and you can make App Engine apps. And it was all abstracted away from you. It was kind of the same Microsoft thing. If we're going to get really clever and build you a platform of the future, but Google, per the Steve Yege rant, is not at all a platform company. And so they didn't really know how to build it. They didn't know how to sell it. They didn't know how to identify a market for it. They didn't know how to support developers in it at the time. And so that sort of fell on its face. And what is GCP? Google Cloud Platform is now a very viable player in this race, but that's not where they started. thing. But one thing that really came up in the research and from talking to people and friends at AWS and Amazon, Amazon and AWS deserve so much credit for overcoming one of the hurdles that you just said Google had, which was Google didn't know how to do sales.
Starting point is 01:40:38 Amazon didn't know how to do enterprise sales either. That's a great point. And when AWS started, like we talked about, the obvious core product market fit and first set of customers was startups. Well, they don't want enterprise sales. They just want to pay with a credit card online. And so Amazon didn't have to figure it out, but they then did also figure it out and serve enterprises and governments and government agencies and big institutions and did the lift and shift thing and then brought those big enterprises along. And I think it started with
Starting point is 01:41:10 academia. Their first big contracts were with universities doing research and running effectively like their supercomputer loads on AWS. Yeah. NASA was famously a customer starting in 2009. Yes, that's right. They did the data streaming and then the video distribution of the Mars landing, right? Yep, that's right. That's right. That was the first big thing. But working with NASA and the academic community on like, how do we fit in with institutions, I think taught them some of that enterprise muscle.
Starting point is 01:41:40 You know, those folks don't want to pay with a credit card. Right. So you got to do contracts. You got to do billing. You got to do billing. You got to do discounts. You need a sales force. You need all this stuff. You need to do a big conference like reInvent.
Starting point is 01:41:51 They had to have poached a bunch of Oracle salespeople because the Amazon sales machine is a lot like the Oracle sales machine of old. Yep. Okay. Let's talk about Oracle. One of the things that I think to most people was to me before doing the research here is vastly underappreciated about AWS is, you know, people think about EC2 and S3 and it's like infrastructure as a service and compute and storage and, you know, networking and all that.
Starting point is 01:42:20 True. Amazon doesn't report this, but if you Google estimates of what the most popular AWS services are, the most used ones, EC2, S3, they're juggernauts. But numbers three, four, and five are all databases. AWS is a huge database business. They have taken so much share from Oracle. And while it's all related, it's infrastructure, it's also a different kind of business from infrastructure. Famously, AWS Redshift. Why is it called Redshift? Ooh, yes. So for people who don't know this, there's an official Amazon talk track, and then there is a real talk track. So the official Amazon talk track,
Starting point is 01:43:05 do you know this one, David? Oh, that it's like a Doppler effect or something like that? Yeah, it's physics related. I think Amazon actually used Doppler as a codename for Alexa. And of course, one of their buildings in Seattle is that, you know, when the sound waves like get bunched up or spread out, like when a siren goes by, it's the Doppler effect. And Redshift is the light equivalent. It's like a star moving away from you. But there's another part of the story here. Shift away from Big Red. Yeah, which is Oracle. So yeah, the database market is freaking huge. There's two properties
Starting point is 01:43:40 of the database market that people just don't think about but are incredible. One, the global market size for database software is $100 billion and it is growing at 10% per year because everything you do with computing, you need to store it in a database. You need databases and you can't get away from them. It's big and it's growing fast. Two, database software may be the stickiest software of all time. Especially at the scale that people are producing data now. It's actually worth contextualizing this a little bit. So there's all these stats all the time, which are something like last year, more data was produced and stored than in the entire decade before and in the entire century before that. And that's not the exact stat, but there's 11 different variants of it, which we all sort of intuitively know because we're storing data on our phones.
Starting point is 01:44:31 But when you have two things exponentially growing, it's hard to intuit the difference between those two things. And so we sort of know this about data. We also know this about the internet. Like when you talk about dial-up back in the day, and then when people got their first cable or T1 line, and meanwhile, I'm here podcasting, and David, I'm seeing you in gigabit down directly into my computer, and it's unbelievable. So you think, wow, these two things have the same phenomena, except that they're actually moving at very different rates. The internet has not gotten faster at the rate that data storage has increased.
Starting point is 01:45:09 So this is most illustrated in some of the AWS reInvent talks. They're like, hey, a lot of you want to shift to the cloud, but you have a petabyte of data, or some of you have an exabyte of data in your data center. So what do we do about that? And they first released this thing that was a 100 terabyte, super secure thing they would ship to your office called the Snowball. And you'd plug it in, it would automatically get all your data. It had a Kindle on it. So it would actually display a custom shipping thing, and you could track it all the way back and
Starting point is 01:45:45 it would arrive in the Amazon data center and they would automate it. It was like tamper proof, bullet proof is the amazing thing. And they've released a few other generations of them now. There's even some with compute on them for field applications. And then the curves kept going. The internet kept getting a little bit faster, but our data storage kept getting a lot more significant. And there's some stat that Andy gives on stage in a keynote in 2016, 17, somewhere in there, where they announced Amazon Snowmobile. And he's like, hey, because all of us are sitting here on computers that have a terabyte or two terabytes or four terabyte hard drive, you're like, 100 terabytes is not that meaningful.
Starting point is 01:46:19 And so then they're like, we will send a snowmobile to your data center, which is a semi-truck full of snowballs effectively so that you can get the data to us. And even with this solution, this never underestimate the bandwidth of a semi-truck moving down the highway, this type of solution, it can still take six months to migrate all of your data into the cloud, whereas it would have taken you years and years and years and years, I don't know, the better part of a century to actually upload it over the wide area network, over the internet. And so that, I think, illustrates pretty heavily your point about once you decide to put all of your enterprise data into a database hosted in some specific vendor's cloud, there's pretty meaningful lock in there. There
Starting point is 01:47:05 are very practical concerns with moving. Oh, I can do you one better on an example. Amazon.com used Oracle databases when onto AWS products until 2019. Oh my God. 13 years after AWS launched. That is insane. It took that long for Amazon itself to migrate off of Oracle. Meanwhile, by that point, Amazon had eight different database solutions for other companies to use and had invented three of them.
Starting point is 01:47:46 There's open source ones they host for you, but they also created DynamoDB and they invented new database technologies that are compatible with other relational databases, but way faster, way more performant. And it's still hard to migrate within the company. Amazing. You know, you just play that forward
Starting point is 01:48:03 and you're like, wow, okay, A, there's still so much revenue that's going to shift to AWS. And B, it's going to be so sticky, so sticky. One of the most amazing stats that one of our friends pointed out to us that I tweeted about this and I posted it on LinkedIn. It's just crazy. AWS today is on an $80 billion revenue run rate, 8-0. That is not the most crazy, impressive, defensible thing about AWS. If you go look in the financials in the 10Q, the latest 10Q from Amazon, they have to report the AWS revenue backlog. Basically revenue that's contracted but not recognized yet. These are contracts mostly with big enterprises of revenue they've signed deals
Starting point is 01:48:54 for but that is not yet recognized. It's going to be recognized in future quarters. That backlog of committed contractual signed revenue is over $100 billion. I don't even know what to say about that. There's a lot more storage and compute not on the cloud than currently in the cloud. So Amazon could shut down all sales efforts, stop growing, literally turn off the lights in terms of new business today, and they still have $100 billion more business that is contractually coming their way. It's insane. Crazy. It's crazy. So David, you mentioned they're on a, what is it? $70, $80 billion run rate right now?
Starting point is 01:49:38 $80, $80. Well, in 2014, Jeff Bezos wrote a memo, the annual memo that comes out to letter to shareholders, and said that, quote, I believe that AWS is market size unconstrained. That was the point at which it was a year before they broke out AWS's financials, and I think it was a $6 billion run rate business. When the quote unquote AWS IPO, which I think Ben Thompson coined that term, happened in 2015. That was when they reported Q1 2015 earnings. At that point in time, AWS was a $6 billion revenue run rate. So it was probably like a $4 billion business when Bezos is like, wow, this thing, I think it's unconstrained. It's nuts. I mean, the real story here is Amazon discovered a new unregulated public utility that they could generate enormous margins on. Well, enormous for Amazon margins.
Starting point is 01:50:41 Okay, but in enormous raw dollar margins, absolute dollar margins, this is a business that they can generate billions and billions of dollars in profits by operating and is effectively a public utility. The market size is, I think I said 120 billion earlier, but I think that's being conservative and growing at 30% per year with no end in sight of this thing continuing to compound at that rate. You know, I always used to think about and talk about the megatrend of our lifetimes is the internet. Believe in the internet. That's the bedrock of modern life. And AWS is what powers the internet. That's true. What I've realized here, it's more than the internet. It is anything
Starting point is 01:51:19 that a computer could touch. AWS takes a tax on that, essentially. Now, to bring it full circle, anything a computer could touch is the internet. It only gets one and the same these days. Jeff, it's a crazy statement, but I think he's right. It's market size unconstrained. It certainly was in 2014, and I wonder if you could even make it now. Yeah. So, okay. The AWS IPO happens in 2015. IPO, quote unquote, $6 billion revenue run rate for AWS, 70% annual growth rate. That's right. It was still growing like crazy then. I think now it's growing like 30 to 35%, but then it was nuts. 30 to 35% growth on $80 billion. It's nuts. Yeah, 19.2% operating margin. When that happens, Amazon stock jumps 15%. When that earnings release comes out, it should have jumped like 500% and does over the next year or two. What an idiot I was for not buying
Starting point is 01:52:18 the day that it jumped that percent. Isn't that the funniest thing about all this is you look at it and you're like, well, now the stock's expensive. No, the stock was still very cheap. Very cheap, very cheap. 2016. This is interesting. Andy Jassy was not technically the CEO of Amazon Web Services. Senior vice president of AWS. Yep. Until 2016. 2016, they restructure corporately jeff bezos becomes ceo of the whole company jassy becomes ceo of aws and jeff wilkie becomes ceo of everything else amazon retail that year aws does 12 billion dollars in revenue over 50 of the company's operating profits, which as we said, they do every year, 17 billion in revenue the next year, then 25, 45 in 2020, 62 last year, but $80 billion run rate. And there's today
Starting point is 01:53:16 sitting on a hundred billion dollar backlog that's coming rain or shine. Just freaking unbelievable. Yep. July 5th, 2021, Jeff Bezos retires. Isn't that crazy? That was only a year ago. It feels like longer. I know. Yeah. Crazy. They announced it before then, but that's when it actually happened. Andy Jassy becomes CEO of all of Amazon. Adam Slipsky becomes CEO of Amazon Web Services. I think this know if they worked with SpaceX or somebody or maybe Blue Origin and they sent some snowballs up to the space station and they lifted and shifted out of the space station. We've said it before, but AWS has about a 39% market share of the cloud, Azure 21%, Alibaba 10%. They're the dominant player in China, which that's an interesting story in and of itself that similar to Amazon, like it was
Starting point is 01:54:25 Alibaba that became the dominant cloud player in China. Be fun to dig into how that happened and Google about 7%. Yep. It's pretty interesting to look at all the ways they're pressing their advantages to 2015 that year they broke out finances. They also bought Annapurna labs, this Israeli company, and they started custom designing chips, which we've seen in both their training chips. They've done custom, I think they're called Trainium. And then they have inference chips, which are also some crazy name like Infuron or Inf... I can't remember exactly, but they have custom machine learning chips. Do you know who makes those chips?
Starting point is 01:55:01 TSMC. Of course. Big TSMC customer. Huh. Yeah. The other thing is that in many ways, it's the embrace extend strategy that Microsoft ran, where first they have RDS and they're like, you can run anything in RDS. And then they start doing things like launching Amazon Aurora, which is a direct attack at Oracle and a proprietary database software that they own and control. And they're like, but it's so fast and
Starting point is 01:55:25 it's so performant, it's compatible. Oh, and by the way, we generate much better margins on it. It's all these things that they used to attack Oracle for. And they're like, well, look, now that we have all the customers, why don't we do some proprietary databases too? And we can generate more margins on those. And there are ways that they generate huge margins, like bandwidth. AWS makes 90 plus percent gross margins on their bandwidth charges. There are many ways where, yes, cloud is still objectively better than the old way that the licenses were structured, the old way of storing on-prem, the old way of hiring all your own IT people. But also Amazon is starting to feel themselves on the lead that
Starting point is 01:56:02 they've generated and run some of the same playbook. The other thing, so then the question becomes like, okay, well, why machine learning? Because it's so clear that compute is this massive pillar of the business. Databases has sort of been stood up as not quite as important, but definitely more important from a stickiness perspective. Every year they announce some new database thing when they're on stage. Machine learning, they've announced SageMaker, they've broken out the keynote. So now there's a custom ML keynote. They have a whole bunch of cloud-hosted ML offerings. They run TensorFlow, which is funny because that's a thing that Google created. They have their own container service. They also have their own Elastic Kubernetes
Starting point is 01:56:39 service. So they sort of have to serve customers because customers want Kubernetes, but they're trying to get you to use their own custom ECS Amazon container service. And what's becoming clearer to me is the machine learning capabilities that Amazon has need to be good, but they actually don't need to be as good as Google's. Because here's sort of the strategy with machine learning. You're going to use whatever ML is available with where your data is, because running machine learning near your data is the most important thing. So once you've picked Amazon to be your storage vendor, and you've sent semi-trucks full of your data into their data centers, you're not shopping around for, oh, where should I run my ML? You're going to run your ML on AWS. And so they can't fall
Starting point is 01:57:32 crazy behind here. But I think this is one way that even though Google should be best positioned to have better ML offerings than anyone else, it kind of doesn't matter if they're not the place where customers are storing their data. Okay. Well, one last element of the story before we transition to analysis. I don't think we can call this a coda because they failed. It's not a coda because they didn't do it. It's a work in progress. A work in progress. I think justifiably so. This has been an AWS love fest. We've heaped so much praise on them. It's like they've done everything right. It's amazing. There's one thing they missed. Ben, do you want to tell us about it? Data warehouses. How is Snowflake its own $50 billion company? Unbelievable.
Starting point is 01:58:23 It stores data in AWS and other public clouds, and it is its own $50 billion company. Unbelievable. It stores data in AWS and other public clouds, and it is its own $50 billion company. And what Amazon would tell you is we have Redshift, and it's one of the fastest growing Amazon services ever, and it's doing really well. But you know, the databases team at Amazon, that whole org has to be very, very unhappy that Snowflake managed to, I mean, run the gauntlet on the data warehouse market. It's crazy that AWS did not do this. It's probably AWS's biggest failure. And the question is why?
Starting point is 01:58:58 And I think there's a few areas. One is just big company stuff. I think before launching something, when you're at Amazon scale, and now that they are the trusted partner of all these IT departments, you've got these security things, operational things, SLA guarantees that they're fully committed to. And I think it hamstrings your ability to really streamline a product, be opinionated, and get something to market that's both fast and intuitive and built for the user. I think Redshift requires a lot of customization,
Starting point is 01:59:34 whereas Snowflake is awesome for developers out of the box. And it's funny that the playbook that Snowflake ran is pretty similar to the playbook that AWS ran when they were just S3 and EC2 serving individual developers. So there's a little bit of like, they're a victim of their own success on this front. The other one is, Ben Thompson pointed this out in a piece that we'll link to in the show notes. It's right there in the name. They're fighting Oracle. They're fighting the last battle with Redshift. It's, hey, take your Oracle-style data warehouse
Starting point is 02:00:07 and basically do that in the cloud rather than lots and lots of Snowflake customers never would have become Oracle customers. It was a different customer segment with a different set of needs. I mean, it's just a fantastic product. And that's not really who Amazon was serving. And there's new leadership there now,
Starting point is 02:00:24 and they're getting the house in order. And I think they recognize this, but this was a whiff. Probably not a whiff on the order of... Microsoft and Google whiffing on cloud. Yeah. It's an order of magnitude or two smaller. Yes. So AWS, we're going to do analysis now, do grading. There's no way this isn't going to be a very high grade, but if there's no way this isn't going to be a very high grade but like if there's a black mark this is it the other thing where they're sort of a victim of their own success is the amazon two pizza team thing led them to launch all these different
Starting point is 02:00:56 services rather than having a cohesive product strategy aws has kind of been alphabet soup and i haven't logged into the AWS dashboard in a while, but it used to just be so overwhelming. So many amorphous logos that all kind of feel like the same thing where it's hard to disambiguate between two things. And I think Amazon realizes this because their keynotes now seem to be much more about pitching these vertical solutions. Like here's this thing for this industry. Here's a vertical solution, here's case studies of other people in your industry, rather than first presenting you with, we have 476 services. And I think that in the keynotes, they've also really dialed back on what used to be the drumbeat of the keynote, which is,
Starting point is 02:01:39 we launched what we consider to be 74 significant features this year, and we're excited to tell you all about them. I think that one for a long time, and now it's created so much confusion for customers that that's actually like the bull case for a Google who is sort of a newer entrant who's coming in with a more cohesive product strategy and can help customers really understand what they should be doing rather than being like, hey, there's no guardrails, good luck. And AWS keeps launching even more new services now to provide those guardrails and say, well, if you use whatever, whatever manager, then you can't get yourself into too much trouble. And it's like, oh, cool, a 13th standards body. They definitely have a little bit of that cleanup
Starting point is 02:02:19 effort going on now. But hey, they got market leadership and they make far more revenue and far more operating income than anyone else. So it's hard to argue with. We want to thank our longtime friend of the show, Vanta, the leading trust management platform. Vanta, of course, automates your security reviews and compliance efforts. So frameworks like SOC2, ISO 27001, GDPR, and HIPAA compliance and monitoring, Vanta takes care of these otherwise incredibly time and resource draining efforts for your organization and makes them fast and simple. Yep, Vanta is the perfect example of the quote that we talk about all the time here on Acquired, Jeff Bezos, his idea that a company should only focus on what actually makes your beer
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Starting point is 02:04:10 And thanks to friend of the show, Christina, Vanta's CEO, all acquired listeners get $1,000 of free credit. Vanta.com slash acquired. Well, should we transition to analysis? more profitable than their closest competitor and do so sustainably. So they can sort of build enterprise value and be sustainably more profitable than their nearest competitor. David, when AWS broke out their financials, they were at, did you say 19%, 18, 19% operating margins? 19%. Now they're at 30%. They've gotten more profitable when the landscape got more competitive. Yeah, how did that happen? So there's something going on there. So there's a couple of things. Moore's Law is in their favor
Starting point is 02:05:13 of all their cogs getting materially cheaper over time. And if I had to guess, I think they're not discounting for customers as fast as they're realizing both economies of scale and legitimately just costs coming down from Moore's Law. But I think actually what's going on here is it comes all the way full circle that Amazon is offering platform as a service offerings at this point and telling customers, hey, you could just keep using our primitive building blocks, but actually what you should be doing to take advantage of the full power of the cloud to run these Lambda functions or to take advantage of these proprietary databases that are way faster
Starting point is 02:05:56 is to pay us a little bit more margin and take advantage of cloud-native things. And it's like, ah, the old tricks are the new tricks. Now you're the incumbent and you're finding a way to do margin expansion. And the mindset a decade ago, or almost two decades ago at this point of, oh, we need to create the platform of the future was right, but you needed to do infrastructure as a service as a stepping stone to get there. And it turns out that Amazon did that and generated their 18% operating margins. And now here they are in a more of a platform as a service world with customer lock-in generating 30% margins. It's funny. I'm looking at the list of seven
Starting point is 02:06:38 powers here, which are for folks who are new, counter-positioning, scale economies, switching costs, network economies, process power, branding, and cornered resource. And I'm like, check, check, check, check, check, check. So early on in the takeoff phase, counterpositioning all over the place. All over the place. It was just straight up a business that the incumbents would never have done because it would have cannibalized themselves. Scale economies, this is probably the single greatest scale economies business of all time. I was trying to explore this idea of why now? Why did cloud happen in the late 2000s?
Starting point is 02:07:13 And one answer is mobile, because as the computing devices get smaller, it requires more of the computing to be done in the cloud. So that sort of definitely accelerated this trend. But the other one is Amazon was kind of the first company to ever try and build data centers at this scale because they needed them to run the largest web application, amazon.com. And cloud is not profitable unless you run it at absolute massive scale. And so I think other people maybe evaluated this business model in theory, but Amazon was the one that was practically in a position to do it and actually realize the scale economies, or I should say economies of scale, that would lead to the scale economy's power. Yep. Well, and it continues to feed itself now of because Amazon's the biggest,
Starting point is 02:08:10 they have the most surface area over which to spread out their CapEx and infrastructure costs. And so thus they can charge the lowest prices at similar or higher profit margins than their competitors. It's amazing. Then you layer on the switching costs. Once people are semi-trucking their data into your data centers, there is very real switching costs. I mean, Amazon.com took 13 years to offload off of Oracle onto AWS. Yep. If that's not switching costs in this industry, I don't know what is. Branding is very clear. I mean, by being the leader at this point, they're just winning. I mean, even if people want to do the multi-cloud thing, they're basically like, cool, do Amazon and one of the others. Their market leadership position, and when they say things like, this is the fastest
Starting point is 02:08:51 growing Amazon service ever, they're reinforcing this idea of everyone else's, eh, and everything we launch, customers love. And I do think people are totally willing to pay up at this point because they just view it as, this will cost us less in the long term than if we make the wrong technology choice and then need to move again. Well, there's also the competitors. You know, at this point, probably with Microsoft and Google, you can feel more safe. But for the longest time, their strategies were all over the place. So as a customer, I don't have any trust that I can build on your cloud strategy and it's not going to completely change in the next several years. Totally, totally agree.
Starting point is 02:09:30 Whereas Amazon has just been like consistent. Yep. I will say, I think a tailwind for Microsoft has been multi-cloud. This idea that, hey, you don't want vendor lock-in, so you really should have some redundancy or spread out your infrastructure across multiple cloud providers. And I think enterprises over the last five, eight years really bought that narrative hook, line, and sinker. It's a reasonable narrative. And so what has sort of happened is, and I remember there's a parallel to mobile development here. When I was an iPhone developer, people were telling me, use PhoneGap. And I'm like, why? Then I won't get to use any of the cool stuff that iOS lets you do, like the latest APIs and the lowest level hardware
Starting point is 02:10:10 features. And they're like, yeah, but then you don't need to write an Android app too, so your development costs are lower. And I'd be like, well, but I'll make an app no one wants to use. So sure, my costs will be lower, but I won't get to make an actually interesting application. And I think there's some argument here in multi-cloud where it's like, okay, cool, you're going to use everyone's infrastructure as a service. But we're far enough in the development of cloud now where these vendors are doing
Starting point is 02:10:34 actually interesting platform as a service things. So you do want to take advantage of that. And this is the Amazon argument, which they've argued in the last two keynotes that they started showing up magically in 2021 in keynotes, where they're realizing, oh crap, multi-cloud is making it so that a bunch of the revenue that could be coming to us is going mostly to Microsoft, but a little bit to Google as people diversify this space. And really what we want to do is convince people, actually, you'll save money because you'll have less complexity to manage with multi-cloud and
Starting point is 02:11:06 you'll get the functionality of all the cool things that we're launching which require all the tight integration so again the thing that they were fighting against when they first launch now that they're the big incumbent they're running the playbook yeah of course that's how it works cycle of life i have a slight sidebar question. We talked about all the other big technology companies that whiffed on cloud. We didn't talk about Apple at all. Did they whiff on this too? Or is this something that's just like, this is not Apple? It's a good question. I mean, it's not Apple the way I think of Apple. And in fact, I even think iCloud's back end is
Starting point is 02:11:45 Azure, or at least for a long time was Azure. It was AWS. There was like a 2016 maybe New York Times article that came out where they reported that it was AWS and Apple got very upset about it. I bet. I mean, Apple basically doesn't serve enterprises. And I know they sell laptops and phones to companies in bulk, and they have an enterprise relationship manager for companies. But this is not Apple's wheelhouse. That said, Tim Cook's Apple is very different than the Apple that I sort of hold in my head. And Tim Cook's Apple is wherever there is durable, high margin revenue. And so this actually is Tim Cook's wheelhouse. I think if he had the sales force to go after this, I think he would do it.
Starting point is 02:12:31 So I totally agree. Apple's a consumer technology company. Yeah, maybe they should be running their own iCloud data centers. I don't know, probably not. But developers are so important to Apple. They are so and should be so close and in touch with developers. And Apple has had its own drawbacks of a high margin business model recently in a monopoly with their developer relationships. You know, mobile, like you said, was the first beachhead for the cloud. Should Apple have been offering something for developers there too? I don't know. It didn't happen, so it doesn't matter. They have spun up something where you can sort of build your applications in the cloud now, but I assume it's all just white labeled AWS or Microsoft.
Starting point is 02:13:13 Yeah. I mean, you never know with Apple, but I think the ship has sailed. Yeah. I do know Facebook uses AWS. Interesting. So Facebook has their own first party data centers that they operate because they're obviously at such massive scale where that makes sense. But then they also use AWS for some stuff. I'm trying to think about does AWS have network economy power? I don't think so. I don't either. I don't think I care if you use AWS. No, it's indirect. It shows up in scale economies because my stuff gets cheaper because you use it.
Starting point is 02:13:54 I think that's the only of the sort of like the big five of the seven powers, you know, so not including process power and coordinate resource, which are kind of esoteric special cases. I think network economies is the only one that AWS doesn't have, but it indexes off the charts on the other four, counter-positioning, scale economies, switching costs, and branding. Yep. Okay. Well, we talked a little bit about what would have happened otherwise with Apple. We talked about it as we went along with the other big technology companies. Should we move on to Playbook?
Starting point is 02:14:23 Yeah, let's do it. My first thing to highlight in Playbook is a perfect transition from the seven powers, because I do think this is actually the best scale economy business of all time, because the fixed costs are so enormous. You amortize them across a huge customer base, you're rewarded for that massive scale, and for making these ungodly large investments. For the first time, they just invested so much in building out new data centers for AWS, they actually took Amazon cash flow negative. Their free cash flow is massively negative over the last 12 months because of these continued, unbelievably large investments. I think this is a business that would have taken enormous scale to get to profitability at all. But now that they have it,
Starting point is 02:15:14 it's one of these sort of self-fulfilling prophecies where now that they're massively the market leader, they just kind of have to keep going. And there could be a self-inflicted wound or like soccer people call it an own goal. But once you have this scale economy's power going, I just think it's pretty hard to drop the ball at this point. I mean, look, we've alluded to this for years on Acquired. We've talked about it a lot on this episode. AWS is a utility company. Think about what a utility company is. It's exactly what you described. It's the ultimate scale economy business. It is something that requires so much capex that society as a whole decides that there should be a centralized provider of this. In most other utility cases, they are regulated by the government about
Starting point is 02:16:00 how much profit margin they can take because otherwise they could take massively exorbitant profits and extort customers. And AWS happens to be an unregulated utility for the internet, which is maybe the biggest market of all time. Well put. So here's the interesting point I want to make on that. There's that common refrain of like, wow, I can't believe Amazon, the e-commerce company, became the cloud company. From this perspective, this is exactly the same thing that the Amazon.com retail business was. An ungodly amount of investment in the fulfillment network globally in order to sell stuff to a big group of customers in a massively amortized way. It's just a data center instead of a fulfillment center. So it's like they had the right mindset for this business.
Starting point is 02:16:47 It's actually a very similar business at scale. Yes. Another one that I had is price cuts. This is not something we talked about in history and facts, but I do think it's worth calling out. By 2012, and keep in mind, they had very little competition up to this point. They had already done 23 price
Starting point is 02:17:05 reductions across the board for all of their services. By 2013, they had done 40. By 2015, they had done 51. So they were proactively, without competitive pressure, reducing prices. And so the question sort of is, why? Well, it reminded me of TSMC. So speaking of Hamilton and Seven Powers, in our conversation with him and Chen Yi, he pointed out that it made sense for TSMC to proactively lower prices for customers in order to win business. And what you're essentially doing there is you're giving up current day profit dollars to gain something in the future. So that's kind of the obvious part.
Starting point is 02:17:44 The less obvious part in the TSMC case is that since the cost to build out a new chip fab are so large and so lumpy, like $10 billion all at once, it's super advantageous to have that predictability of customer orders. And on top of that, there's a finite number of the machines available to manufacture those high-end chips, the ones that ASML makes. So it sort of pays doubly to be able to know for sure you can be one of the few to get those. Well, AWS sort of has the same thing going on where it's the ASML machines are much more scarce than the servers that AWS is buying. But it's unbelievably helpful for AWS to win market share so they can do their thing and invest more in building out more data centers to kind of keep that thing going. So that proactive price drops works
Starting point is 02:18:32 not quite as well as it does for TSMC, but they get rewarded for it for sure. Yeah, this was such a good point from Hamilton. The strategy is not just to win business. It's to be able to feel confident about building out ahead of the curve on infrastructure. Yes. To enable scale economies. Yes. Or further drive scale economies. So then here's a sort of thing that is unfortunate about AWS relative to the Amazon.com business. Speaking of building out infrastructure, we talked about float in the Amazon.com business. Speaking of building out infrastructure, we talked about float in the Amazon.com business. Customer makes an order,
Starting point is 02:19:09 customer pays immediately, Amazon gets net 60 or so to pay a supplier. It's the opposite in cloud. Right. This is why they have $100 billion revenue backlog. From this dimension, that's a terrible thing. Amazon doesn't get this money up front. Their whole thing to customers is you don't have to pay up front to install servers. There are reserved instances, but there are sort of ways that they try to get a little bit more upfront cash. But they have to go build these whole data centers, buying all this real estate, buying all the servers or leasing, however they sort of structure them.
Starting point is 02:19:43 And so they've had to get creative with capital leases on the data centers instead of buying them up front so that they can make the data centers effectively pay as you go, just like their revenue is pay as you go. So they don't get the incredible business model, the negative cash conversion cycle thing that they have in the retail business in AWS. And I think that's important to understand that while this business is much higher margin, their effective cost of capital is higher. Well, I guess Amazon stock price, I don't think dropped that much, but people freaked out this past quarter when Amazon reported the hugely negative cash flow.
Starting point is 02:20:20 Right. And this is why. Right. And that is also why you shouldn't be like that worried about it. But compared to their retail business that has a negative cash cycle, this is a less attractive element of the AWS business model. Yep. All right. Another one I had is I was reading from friends of the show Tegas. They had this great transcript that I was reading from a former AWS business development person
Starting point is 02:20:43 on kind of the obsession around multi-cloud. And it got me thinking a lot around multi-cloud. And the evolution of what cloud means has completely changed. When cloud first started, it meant use these primitive building blocks in our data center, our being Amazon, and pay as you go. And what it has evolved to mean is use our cloud services, which exist now at a higher level of abstraction, and some of which are proprietary. And it doesn't
Starting point is 02:21:15 actually have to be in our data center. And so the interesting thing about where multi-cloud and hybrid cloud is going, multi-cloud being, you know, Amazon and Microsoft, and hybrid cloud is going, multi-cloud being Amazon and Microsoft, and hybrid cloud being this sort of in your data center and in our data center. In the most recent AWS keynote, they announced a bunch of services, which are AWS cloud services that run in your data center, where Amazon employees come and install servers and maintain servers in your data center. It's the old Oracle business model all over again. And they're like, well, it's as great because you get access to Lambda right there on-prem. I mean, in the cloud. And you're like, sorry, what? How is it in the cloud if it's...
Starting point is 02:21:56 They're like, yeah, yeah, because it's AWS Lambda. So it's cloud because it's Lambda, but it's in your data center. It's in the cloud. I'm like, what do these words even mean anymore? It was funny reading this transcript really made me start to contemplate what is cloud even now, because it also exists in multiple clouds and your data center. And so it really actually ends up being about the set of proprietary services that you're building your application on rather than where it's running. I guess these days, you know, it means kind of back to the beginning of the episode. It means your IT infrastructure, you are calling via an API. Right.
Starting point is 02:22:35 I think that's what cloud means. Yep. Someone's going to finish this episode and be like, well, I thought I knew what the cloud was. And then Ben and David talked for three hours and now I don't know what it is anymore. Yeah. You know it when you see it. Yep. All right, another one. Make something people want.
Starting point is 02:22:50 This is the YC slogan, but this is exactly what Amazon did. I think Microsoft and Google both wanted to build something that they thought would be an amazing business model and something that was very clever to them as technologists. And what Amazon decided to do is figure out what startups wanted
Starting point is 02:23:05 to build on, figure out what IT managers wanted to lift and shift to, and just build that. And it's boring, but it comes through in all these keynotes. I mean, every single thing has a customer use case attached to it, a customer use case that drove them to develop it. And it's funny how they refuse to do things. For the longest time, people were like, why aren't you doing anything in blockchain? And Andy Jassy's comment on stages he's like we don't really understand the customer use case yet and this was in like 2015 or 16 this is six years before the recent buzz around web3 use cases and i just think they're so focused on that as the very first question you have to ask before investing a single dollar of engineering resources.
Starting point is 02:23:46 It's just very impressive. Whereas in that same time frame, didn't Microsoft have those ads with Common? Blockchain in the cloud on Microsoft. You know what IBM was doing? Like a corporate blockchain. Yeah. So they eventually did roll something out that was like, this isn't a blockchain, but we think it accomplishes the same thing that you people who are asking for blockchain-based enterprise infrastructure
Starting point is 02:24:11 are asking for. Interesting. Okay, my next one is about asymmetric upside. And this is another Bezos letter that I'm going to quote from 2015, where he says, given a 10% chance of 100 times payoff, you should make that bet every time. But you're still going to be wrong nine times out of 10. We all know that if you swing for the fences, you're going to strike out a lot, but you're also going to hit some home runs. The difference between baseball and business, however, is that a baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can ever get is four. In business, every once in a while, when you step up to the plate, you can score a thousand runs. This long-tail distribution
Starting point is 02:24:55 of returns is why it's important to be bold. Big winners pay for so many experiments. Market-sized, unconstrained. Market-sized, unconstrained. I think that's got to be like a catchphrase on Acquired that we should incorporate. Oh, for sure. Let's print it on some merch. But yeah, this is the year after he makes the market-sized, unconstrained comment about AWS. I just think it's such a perfect illustration. A lot of people make fun of certain venture capital investments, And I'm kind of only interested in the ones people are making fun of, because that's the whole point of venture capital
Starting point is 02:25:29 is seeking these crazy asymmetric long tail returns. And I think Jeff Bezos got that better than most VCs do. He's a phenomenal high beta capital allocator. And so in running a company, I mean, he was also a very good operational CEO and also like an actual genius. So like all of these things, there's lots to say about Jeff Bezos. He's absolutely a genius. He's absolutely a brilliant operator. But maybe even more than these things, he just gets capital allocation. And that's why I think Amazon is effectively the highest performing venture returns in history. AWS is a venture bet in their portfolio that they own 100% of. Also that quote, what did he say? In baseball, you have truncated returns. A truncated outcome distribution.
Starting point is 02:26:18 Truncated outcome distribution. That's the most Jeff Bezos thing ever. Right. I'm sure that Aaron Judge is thinking that when he goes to the place like, oh, if only I didn't have a truncated outcome distribution. Oh, so great. Which also reminds me, sidebar, because we're deep in the episode here, watching the reInvent keynote with Reed Hastings. Yep.
Starting point is 02:26:41 It's been so long since we did our two Netflix series. Yeah, we need a part three. When was that? That was years ago, but I think they're still really good. Be fun to go back and re-listen to them. Reed Hastings is a huge nerd. Oh, yeah. A huge nerd. I mean, he started his career doing like a data storage company. Yes. I think of him now as like, oh, Reed Hastings, CEO and founder of Netflix.
Starting point is 02:27:04 He's a business guy. Like, no, kind of like Bezos. No, he's like a true geek. He's an engineer and his engineering project is his company. Yes. Yeah. And I mean that in the highest possible compliment. Those people are the people you could listen to talk forever because they speak with such
Starting point is 02:27:21 precision about their strategy because it's actually thought through to a layer deeper than the platitudinal stuff you normally hear. Yep. All right, so here's my last one. And you brought it up earlier in the episode, and I wanted to save it to the end of playbook, because I think it contrasts my takeaway from the last episode. So I used this analogy that Amazon would quickly spin something up,
Starting point is 02:27:42 learn from it, and if it wasn't the right thing, kill it and take the learnings to do the next thing. And I think I called it brute force maze finding or pathfinding. Well, AWS is different. They don't really have a Fire Phone or a Zshops. And the biggest reason for this is when you launch a service for enterprise customers,
Starting point is 02:28:00 it is really hard to kill it. You burn customer trust. And actually, if you think about what's the bigger risk, burning the trust and losing that customer and all their future revenue, or having to maintain kind of a crappy service that didn't work, you just maintain the service. Right. Such a good point. There's stuff that didn't live up to the full potential, like all the productivity applications they've ever tried, WorkMail.
Starting point is 02:28:29 Chime, their IoT offering, Greengrass. I think IoT just didn't pan out the way that everyone sort of wanted it to. They launched something in 2013 called AppStream to run mobile apps in the cloud. But the commitment to maintaining these things is just completely different at AWS than in the consumer business. And the biggest illustration is SimpleDB. So DynamoDB comes out, it's way more performant, it has sort of a similar job to be done. And SimpleDB had all kinds of cost issues for Amazon, but there were customers using it, so they kept it up. I think one of those customers was even Netflix, and they just didn't want to deprecate something that customers were using. Yeah. And this is why, you know, you'd log onto the AWS product page and there's 200 services there. Such a good point.
Starting point is 02:29:15 You can't like, it's not worth it to them to kill anything. Yep. All right. Grading. Do we even really need to discuss this? I mean, we could be like, okay, plus we're done. Here's probably the most interesting way to think about. And actually, I'm going to stretch this out from just AWS and talk about all of Amazon. Ooh, okay, great. To sort of evaluate it going forward. What is a market cap? Well, market cap... Market cap, unconstrained. What is value? What is money? So what is market cap?
Starting point is 02:29:42 Market cap is the sum of all future cash flows discounted to the present day at some discount rate. And you know, the long term, the market is a weighing machine, even if the short term, it's a voting machine. Thank you to Warren Buffett. So Amazon has a $1.5 trillion market cap. And they had like a five-year run where they generated some cash, and then the pandemic hit, and they made a bunch of reinvestments, and now they're certainly not generating cash. And up until 2015, they broke even. They know how to do one thing really, really, really well, which is reinvest every single dollar into growing. And I'm very curious what this business looks like when they stop doing that. At some point, will they see when they're actually saturating all their total addressable
Starting point is 02:30:38 markets and ease back on growth so that they can generate the maybe hundreds of billions of dollars in profits per year they need to justify this market cap. If you're worth $1.5 trillion, it does suppose that you're spitting off like $100 billion a year or somewhere on that order of cash, which we've never seen them do or come close to doing. So either they need to continue operating the way that they have and continue finding more AWSs, or at some point they need to realize, oh, there's the edge of the TAM. Let's start generating a ton of cash, even though we've never known how to do that before. Hmm. I think on the last episode, I said, if, but of course, when we get to interview Jeff Bezos,
Starting point is 02:31:30 the question I really want to ask him is, is it still day one? Is it day two? Why did you retire? All that stuff. But you raise an interesting point. Amazon as a company, as a whole, is just sort of architected.
Starting point is 02:31:43 And Jeff would say, I told you guys all along, is architected to always be a day one company in that it needs to always keep growing. Yes. So at some point that bumps up against the GDP of the world, right? You can't actually do that indefinitely unless the GDP of the world keeps growing at a faster rate than Amazon's growth, which is definitely not true. Amazon's a much higher growth company than the world's GDP. So maybe this is like a, well, at some point, a billion years from now, we're all dead and the earth gets absorbed by the sun anyway, so don't project out this far. But I am curious, if you held Amazon indefinitely until the company no longer existed, which it will at some point, will you actually realize one and a half trillion dollars of value? Yeah, that's a good point.
Starting point is 02:32:35 Maybe this is part of Jeff stepping back and Andy Jassy becoming CEO of the whole company. Is to actually figure out how to do that. Yeah. I mean, I can imagine that that's a challenge that I'm totally projecting here into Jeff Bezos's mind, always a dangerous thing to do, in part because it's so much more expansive than anybody who would try to project into it. But I bet that's not something he's personally very interested in figuring out. Right. I think it's a great point. And I should say, I mean, I think in the 12 months leading up to June of 2020, they generated $27 billion of free cash flow. They
Starting point is 02:33:12 know how to generate cash. I sort of thought they were on the path starting, I think in like 2015, 16 is when they really started actually becoming free cash flow positive and growing that year over year. And that just stopped when the pandemic hit. So maybe we're in some temporary anomaly that they'll go back to the 2019 mode here shortly. Or maybe the anomaly was the last five years before COVID. Well, Andy, I think has said on recent earning calls, hey, we're going to be moving back towards profitability. We know how to do this. Don't freak out. Yeah. And that's the exact opposite message of what Jeff Bezos said in the 2020 letter right when COVID hit. Didn't he say like, buckle your seatbelt?
Starting point is 02:33:54 Yeah. He said, if you're a share owner in Amazon, you may want to take a seat. Oh, great. Yeah. He's such a cowboy. Like we talked about, you know, he wears the cowboy boots. Truly. Anyway, that's sort of a thought experiment exercise. he's such a cowboy like we talked about, he wears the cowboy boots truly anyway, that's sort of a thought experiment exercise, but to actually grade it I mean, it was an
Starting point is 02:34:12 activity of new market creation that just completely worked and invented one of the biggest markets of all time and then became the leader in that and managed to have no competition for the first five years and then stave off everyone coming after them basically permanently. They own just little enough of this market that it's not of regulatory concern. Like if they owned 80% of cloud,
Starting point is 02:34:36 it probably would be worse for them long term. Oh, here's a question. Was Amazon strategic in letting Microsoft back in the game? No, I don't think so. I think that's too difficult of a future to see to cannibalize current day. I'm sure they're worried about antitrust and regulation. Yeah. I mean, it's the same way that Google looks at Bing, I'm sure, which is like, whew, thank God that exists. All right. What's your grade? It's an A plus, but grading is a silly exercise. I almost want to cut it from these types of episodes.
Starting point is 02:35:09 But I do think the interesting question is that I do want to continue to ponder for a while is, if you held Amazon ad infinitum and you owned 100% of the company, would you ever be profitable on your business to buy it for a trillion and a half dollars? It's the Warren Buffett, Ben Graham, a stock is a piece of a business. If you were able to buy the whole company of amazon.com for $1.5 trillion, is that a good use of capital? Yeah. Great question. I think it probably is.
Starting point is 02:35:41 That's where I thought you were going. I'm a little biased here, but come on. Yeah. A plus for me. Get out of here. This division of this company has $100 billion of contracted revenue. A plus. We're done. David thinks this stock's cheap.
Starting point is 02:35:55 Yeah. Carvouts. What you got? Yes. Carvouts. Mine is a very enjoyable show that I watched on Disney+. It's a Marvel show called Moon Knight. And I would say it's not the best show that I've seen on Disney Plus, but it is the best acting that I have seen in any of the Marvel Cinematic Universe shows.
Starting point is 02:36:18 Ah, nice. I still think Loki is probably the best written. And what was the one with the Scarlet Witch? Oh, WandaVision. WandaVision. Also very good. That was good. Fantastic writing. I would say this is like almost to those calibers, but definitely a notch below. But Oscar Isaac playing the lead role is some of the best acting I've seen in any TV or movie ever.
Starting point is 02:36:48 And the writing is entertaining enough where you can just sit there and enjoy his performance in a way that feels Broadway-level theatrical. I did not appreciate him as an actor until this. Wait, is he? Poe Dameron. Yeah, that's what I was going to say. I was like, he's done other Disney Star Wars stuff. He's also done some other crazy roles. I think he's in Ex Machina.
Starting point is 02:37:07 Ah. Have you watched any of the new Star Wars stuff? I just finished Obi-Wan Kenobi and was deeply unenthused. Bummer. I enjoyed it. As a Star Wars fan, just more Star Wars is awesome. And getting to see Obi-Wan in a different age is awesome. But I think they took away
Starting point is 02:37:25 from the gravitas of his character, I guess, okay, spoiler alert. Please stop this if you've not seen Obi-Wan Kenobi. It's going to be spoilery where I'm not going to tell you the end of the series, but I'm going to tell you
Starting point is 02:37:37 what the series is about. It's about the period of time between when he arrives on Tatooine at the end of episode three, but before A New Hope. And in A New Hope, there's all this great gravitas given to this idea that, like, wow, he came here and has been, like, living in a cave marooned and away from all this stuff forever since we last saw him. Yeah. He's the old hermit Ben, right? Right. He brings Luke to Tatooine, and then that's his responsibility. And this is, like, all this stuff forever since we last saw him. Yeah, he's the old hermit Ben, right? Right.
Starting point is 02:38:08 He brings Luke to Tatooine and then that's his responsibility. And this is like a whole galactic adventure that takes place. He's like Han Solo. Where he leaves Tatooine and comes back. And I won't spoil things too much, with very, very major characters where Obi-Wan has interactions with them and big material fights that totally would change the character dynamic and the level of import put on his character on Tatooine
Starting point is 02:38:32 in a way where it feels like it cheapened the canon to date by this existing. I have not watched any of the new stuff, but man, I feel like Lucasfilm just needs a new start. Doesn't feel like it's going in a good direction. The IP also doesn't really lend itself well to serials. I don't know. Maybe that's not true. I did really like The Mandalorian. Yeah. And then I liked when Boba Fett tried to become The Mandalorian by being like, ooh, Boba Fett's not that good. Let's just kind of make it the Mandalorian again. Well, that could be an episode for another day.
Starting point is 02:39:09 Moon Knight, Oscar Isaac. Go watch it. Awesome. My carve-out is one that if you are listening to this now, I'm pretty sure you're going to love this. I have a high degree of confidence in the affinity overlap between people listening right now and the carve out that I'm about to say, which is Lex Friedman's five and a half hour interview with John Carmack. It's so good. It's so good. It's awesome. Carmack's just a legend. I'm an hour in and it's great. It's so, so good. It's awesome. Carmack's just a legend. I'm an hour in and it's great. It's so, so good. Especially having, not knowing that that was coming,
Starting point is 02:39:53 having just recently listened to the audiobook of Masters of Doom. I was made for you. It's perfect. Ah, I'm just in heaven. In heaven. Reading Masters of Doom and now listening to this episode, this interview with Carmack, makes me actually want to go either talk to or find out more from Romero, John Romero, and hear how he thinks about things and
Starting point is 02:40:12 his history of id. Because Carmack actually says in the beginning of the interview with Lex, John Romero is better at talking about the history of id and being kind of the keeper of that than I am. They have a nice moment kind of halfway through the interview with lex where he talks about the relationship with romero and became super strained and then blew up and when it blew up but i think they've been kind of reconciled and it's nice anyway the whole thing carmack is he's just one of those people that operates on a different level than most of humanity, at least in the technical realm. And it's very interesting that he did VR and he was at Oculus and part of Facebook and Meta. And the thing that he's working on now is AI, and in particular, artificial general intelligence.
Starting point is 02:41:01 It's a great interview. Sweet. Can't wait to finish it. All right, listeners. Well, thank you so much to Fundrise, Pilot, and NZS Capital. Links for all three of those are available in the show notes, as well as a link to register for our NZS Talkback, which the first one was super fun and can't wait to do a second one with them on this white paper as well. After you finish this episode, come discuss it with all of us. 13,000 strong now in the Acquired Slack community at acquired.fm slash slack. Pick yourselves up a sweet shirt or tank or hoodie or crew neck or onesie at acquired.fm slash store, you can totally become an acquired LP and get early access to our LP episodes at acquired.fm slash LP or just get them when
Starting point is 02:41:54 they're public. Search the podcast player of your choice for acquired LP show and our latest episode will be live there soon with Nat Manning of Kindergarten Ventures fame and of Kettle as well. Honestly, reinsurance is fascinating and I never would have thought I would have said that. As is enterprise IT infrastructure. Amen. All right, listeners, have a good one.
Starting point is 02:42:20 See you next time. We'll see you next time. Is it you? Is it you? Is it next time who got the truth is it you is it you is it you who got the truth now

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