Reed Hastings - Building Netflix

Here's an interesting question to think about, if your finance team suddenly had an extra week every month, what would you have them work on? Most CFOs don't know because their finance teams are grinding it out on lost expense reports, invoice coding, and tracking down receipts until the last possible minute. That's exactly the problem that Bramps had out to solve. Looking at the parts of finance, everyone quietly hates and asking why are humans doing any of this? Turns out they don't need to. Bramps AI handles 85% of expense reviews automatically with 99% accuracy, which means your finance team stops being the department that processes stuff and starts being the team that thinks about stuff. Here's the real shift. Companies using ramp aren't just saving time, they're reallocating it. While competitors spend two weeks closing their books, you're already planning next quarter. While they're cleaning up spreadsheets, you're thinking about new pricing strategy, new markets, and where the next dollar of ROI comes from. That difference compounds. Go to ramp.com/invest to try ramp and see how much leverage your team gains when the work you have to do stops getting in the way of the work that you want to do. Investing is hard. It's an apprenticeship industry with messy data, complicated workflows, and decisions that demand judgment. Investing needs specialized AI, and that's why I'm so excited about Rogo. Rogo is an AI platform purpose-filled for Wall Street, not a generic chatbot, but a suite of agents designed around how bankers and investors actually work, from sourcing, diligence, and modeling to turning analysis into deliverables. Finance requires deep domain expertise far beyond your average chatbot. As listeners of this podcast know, every investment firm is unique, with its own thesis, internal notes, templates, and ways of investing. Generic AI can be impressive, but it doesn't actually understand your process, and that's where the advantage lives. For me, three things set Rogo apart. One, it connects directly to your system, so it can work with your actual data, internal, and external. Two, it understands your workflows. How work really happens across a deal or an investment? And three, it runs end to end and produces real outputs in the way that your best people do. A lot of the bull spread sheets, investment memos, diligence materials, and slide decks that match your standards. Rogo is built by a deeply technical AI team with real finance DNA, large language models for finance professionals by finance professionals, and it's already being adopted by some of the most demanding institutions in the world. The teams that get this right early won't just move faster, they'll compound better decisions, train their own AI analyst, and the gap will widen. The Rogo team's vision is distinct. Make the most ambitious investors even better, and make finance an AI native industry. I'm fully bought into that vision, and I think their work will fundamentally reshape investing. Learn more at rogo.ai/invest. If you're a long-time listener of this show, you've heard the same pattern play out across so many great companies. The moment a product finds early traction, the constraints shift from engineering curiosity to enterprise execution. And one of the biggest hurdles, whether you're open AI, cursor, perplexity, or sell, or a brand new startup is identity and access. SSO, SKIM, RBAC, audit logs. These are the capabilities that give enterprises the confidence to adopt your product at scale. That's where WorkOS comes in. It's become the default way fast growing software companies get enterprise ready. Instead of spending months building SSO or provisioning or permissions in house, WorkOS gives you all the core features enterprises require through clean, modern APIs. And in the era of AI, this matters more than ever. AI native companies scale faster than anything we saw in classic SASS. They can't afford to wait on an enterprise compliance. They need it on day zero. That's why so many of the top AI teams you hear about already run on WorkOS. If you're building software and want to unlock larger customers or just avoid reinventing a very unglamorous wheel, head to WorkOS.com. It's the fastest way to become enterprise ready and stay focused on what actually moves the needle your product. Visit WorkOS.com to get started. Hello and welcome everyone. I'm Patrick O'Shanasi and this is Invest Like The Best. This show is an open-ended exploration of markets, ideas, stories and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at Colossus.com. Patrick O'Shanasi is the CEO of Positive Some. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of positive sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Some may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc. The most interesting thing about studying Netflix and talking to Reed is that it is as a business probably the single most relatable example since we all watch Netflix of two really simple ideas that everyone talks about but are very hard to do in practice. The first is this notion of finding a simple idea and taking it extraordinarily seriously. Netflix has effectively been scaling up its core original model since its inception. Reed talks in our conversation about how even the DVDs were nothing but a stepstone towards the streaming future that they envisioned at the very outset of the company's founding in 1997 and simply letting that idea play out over decades without getting distracted and how powerful that can be. The second is this notion of talent density. This is a term that now get thrown around every major company and really it was Reed and Netflix that pioneered this concept of what can happen if you set and keep a talent bar exceptionally high. We get into why that's difficult. What Netflix did to make that talent density bar work and sustain itself over decades. This conversation really is an ode to those two simple concepts and of course in this case it's fun to learn about because it's something that we all watch every day. I want to go back to your first business and this sort of origin story of this notion of talent density that you become very famous for. We'll talk about talent density for sure. It's one of these ideas that's now ubiquitous in most technology companies. I think you were sort of the originator of the concept but I want to hear how you came to learn that lesson in the first place, presuming that your very first team wasn't just incredibly talent dense and perfect. What was the early origin story of that concept? I founded Pure Software in 1990 and grew typical great software company doubling. I wasn't careful about it and I would say talent density declined. That company, we went public in '95, got acquired in '97 and when I analyzed looking back what happened, one of the major things was declining talent density and then with declining talent density you need a bunch of rules to protect against the mistakes and that only further drives out the high caliber people. It was through that experience that I realized I've tried to run software like a manufacturing plant and reducing error and putting in process and then that doesn't get high productivity or high talent. We should manage software much more artistically with inspiration rather than management. So typically we humans we value being nice and we value loyalty. Yet in the workplace that's attention because being nice is in contrast or intention with being honest. I generally like people that are nice and yet I want you in the workplace to be honest with each other so that we're more productive. So we have to find a way to give each other permission to not be conventionally nice and instead to be focused on the team's success which is being very direct. Similarly with loyalty, we come to see loyalty which is something in your family like you would never fire your brother if you were tight on money. You would share and that's what we admire and yet in a company what we do is we lay people off and so this whole idea that a company is a family it's unintentional but it just derives from all the structures of society we're family. All companies used to be family companies and then corporations have grown more recently. All countries used to be family countries and kingdoms and so basically family was the deep organizing unit so it's natural that that spills in to how we think about an organization but the contrast is a professional sports team and that's an admired model. It's really focused on achievement and everyone understands that you change players as you need to try to win the championship and we all got to fight every year to keep our position because if we can upgrade we must to achieve the winning of the championship which is producing a great company. How do you protect against the natural way that companies seem to bleed down towards lower talent density over time? There seem to be very few organizations that get it high and then keep it at that same level especially with scale. What are the ways that you learn to keep talent density as high as possible as the company grew so big? Well as the companies grow you may be able to pay people more so that will help if you think of the sports team in the biggest markets they can afford the highest compensation and like the Yankees or the LA Dodgers they often have the best players. It's not a direct one-to-one on how much you spend and quality but there is a strong correlation. I think the second thing you can do is continue to really evangelize the benefits of talent density over like total quantity so that more and more of your leaders get adept at managing for density. I would love to talk at each stage of the funnel to creating talent as in a business starting with how you found people in the first place with the most reliable ways where a finding people and then also how you evaluated them and then I want to talk about further down the funnel but starting just with like top of funnel what were the most effective ways of finding people that had the potential to be extremely talented inside of one of your businesses? I've come to look at it like keeping a pretty broad funnel and hiring a lot of people and then over the first year you really get to know them and you can figure out what you want to do. Do you want to keep them or not? Other people have a view like very hard to get in but then you can stay no matter what and I think that's been more of the Google orientation as an example and it comes from their graduate school background right it's really hard to get in to stand for graduate school and then it's hard to get pushed out too and so it's just natural that they mapped themselves onto that model and there's some benefits of that but that's a different model and mine is more have relatively open doors. We'll interview broadly and try to select what we think is the best person. It stands for reason that maybe your one year attrition rate was higher than say Google's or somebody else's quite a bit. What was it like would you remember? It's probably 20% in the first year. That's pretty high. What would you tell people on the way in or tell the organization about that rate itself to make sure it didn't spook people that lots of people would leave? Well it did spook people and so it's only fair to let them know what they're getting into. We would say we're not going to guarantee you a lot but we'll guarantee that it will always surround you with great people and have you work on hard problems. That was our core that you may not be happy, the hours may be long, you know, the food may be okay but like the essence of what we can do at work is hard problems with great people. Think of it if your primary orientation is around job security and you're willing to put up with working with uneven levels of talent then there are other companies that are a better fit and there's some benefits of that which is you have stability in your life. If you're more of a performance junkie and the thing that makes you vibe the most is working around incredibly talented people and running fast and loose with great teammates then you're willing to put up with the job and security nobody likes it but you're willing to put up with it to get the performance density. You said fast and loose, can you seem about loose? If you over-manage for example a tight process or specific hours that you have to be in the office or have wide variety of things you filter out performance and creativity and the looser that you could run the more creative that the organization will be. So we talk about it as managing on the edge of chaos. You don't actually want to fall into chaos. Okay. And chaos, the product barely gets released, it's full of bugs, people are upset, payrolls are made, lots of bad things happen. But it's getting us close to that edge of chaos where there's last-minute saves and a lot of dynamism as you can possibly tolerate as opposed to say a semiconductor factory which is trying to reduce variation and reduce error to get rid of variants. If you're going to be a creative organization, you want to be high variants, high creativity and again, managing on the edge of chaos. I'm curious with a 20% attrition rate, what you learned about letting people go well and the right way. How did you get really good at that specific part of the life cycle? Well, I think there's two parts to it to create the confidence throughout the company. One is to release the moral thing. Most managers, they're people managers, they like people, they don't want to hurt people. So it's very difficult for them. And so one of the best things is to do large severance packages, like four to nine months of salary. And so it feels expensive at first, but one is it makes the person who's let go, feel a little bit better because they've got a bunch of money in their pocket. Two, it helps the manager do their job because then they don't feel as bad in letting the person go. And then, you know, it just sets up a much better mutual feeling. Third on the terminations is setting a context where it's not a moral issue. You didn't fail. It's just like a professional sports player. We think we can get someone better here. Okay. So it's a pity for the person, but it's seen as natural as opposed to like a failure. So typically I would say something like, hey, I see Patrick, you're working really hard. You're trying. I'm so sorry to tell you that honestly, if you quit, I wouldn't try to change your mind to stay. The reason I wouldn't change your mind to stay is I think I could get someone in your role that could do what you're doing plus even more. And here's why. The way the company is set up is if I wouldn't work to keep you, I'm supposed to let you go. In that way, we're sort of executing on an agreed upon framework that'll keep our test framework. How did the keepers test literally work? Like how was it rolled out across the company? Well, it was always there that, you know, in the original slide deck, adequate performance gets a generous heavens package. So it's really just starting up front. The test that we encourage people to use is if someone were quitting, would you try to get them to stay to keep them? Because that turns out to be a good test relative to, you know, all the relief we sometimes feel when someone not great moves on customer trust can make or break your business. And the more your business grows, the more complex your security and compliance tools get. It can turn into chaos and chaos isn't a security strategy. That's where Vanta comes in. Think of Vanta as you're always on AI powered security expert who scales with you. Vanta automates compliance continuously monitors your controls and gives you a single source of truth for compliance and risk. So whether you're a fast growing startup like cursor or an enterprise like snowflake, Vanta fits easily into your existing workflows. So you can keep growing a company your customers can trust. Get started at Vanta.com/invest. To me, Rijlijn isn't just a software provider. It's a true partner in innovation. They're redefining what's possible in asset management technology, helping firms scale faster, operates, smarter, and stay ahead of the curve. I want to share a real world example of how they're making a difference. Let me introduce you to Brian. Brian, please introduce yourself and tell us a bit about your role. My name is Brian Strang. I'm the technical operations lead and I work at Congress asset management. How would you describe your experience working with Rijlijn? Rijlijn is a technology partner not a software vendor and the people really care. I get sales calls all the time and ignore them. Rijlijn sold me very quickly. We went from $7 billion to $23 billion and the goal is $50 billion. Rijlijn was the clear front-runner to help us scale. In your view, what most distinguishes Rijlijn? They reimagined how this industry should work. It was obvious that they were operating on another level. It's worth reaching out to Rijlijn to see what the unlock can be for your firm. Visit RijlijnApps.com to schedule a demo. Was there an episode in Netflix's history that you can remember where you were on the edge of chaos and it either did or very nearly cost you very dearly? During the Netflix 25 years, there's a couple small things that we did wrong and one big one being the quickster separation of DVD and streaming. Maybe taking the quickster example, what is it like to see high talent density operate against something like that? I'm just curious what it felt like to watch that happen. Quickster for your listeners was a sad episode at 2011 where I became convinced we really had to go all in on streaming and drop DVD and put DVD in its own company that would drift along and free ourselves from that. Of course, most of the customers were mostly using DVDs. They were still mail me the discs and so they didn't like it, lots of cancellations, stock drop by 75%, so it was a tough time and ultimately it's the right thing to have separated DVD and streaming but we did it too fast. The big analysis of it afterwards was lots of the executives thought that it was very problematic but they kind of said to themselves, geez, reads made 18 decisions right before or so, you know, I'm probably wrong and reads probably right. So they kind of suppressed their own significant doubts and what we realized is if they all knew of each other's doubts, they would have been much more likely to weigh in to probably just have us do it slower. We instituted a much more collective information process on decisions going forward where everybody weighed in 10 to negative 10 on decisions and it's all in a big shared document so everyone sees what everyone else thinks. So that way if we had had that decision process in place, then I think I may well have thought, well, these are all fantastic people and they're all horrified at this idea. So I may be right, but let's at least go a little bit more gently to figure out that and we wouldn't have had as deep of all the value creation that you've been a part of or the leader responsible for was most of that the result of a fairly non consensus idea because that seems like a consensus process or at least if not decision by consensus, at least being aware of what the consensus is. And I'm curious about that tension there. It seems like very often non consensus is where the value comes from. Is that generally true in your personal history of decisions that you made that created most of the value? Well, I think you want to be super careful here because this is the source of much value. You want to be totally independent in your thinking and not consensus oriented at all, but you want to know what other people are thinking otherwise you're, you know, flying blind. So I think there's a high value on information gathering opinions, but they're not averaging them. We would never do that. We were very clear that the concept was the informed captain. So we wanted to make it like the captain of a ship. Okay, the captain of the ship makes a decisions, but it's good for them to collect a lot of information. And so we were very strong on no committees, individuals make decisions, but we want them to be informed about that decision. And then it's up to them to make it. I'm so interested in the bucket of seems like a bad idea, but turns out to be a good idea because there's just less competition if it seems bad. What has been your process of coming up with good ideas in the first place? I fall in love with ideas easily. Like I'll see some combination or insight. The original one was that DVD, which was just coming out when Netflix started was very lightweight. And this was coming out of the AOL mailing CDs to everyone to install a well on CD wrong. So I was kind of like pretty familiar with mailing because I've gotten tons of these just through the mail DVD for movies was just replacing VHS or just starting. So I kind of like clicked on that. And then the classic computer networking thought experiment you do is what's the bandwidth of a FedEx of a tape through the mail? And then it turns out you calculated and it's like carabits per second at low cost to send a backup tape by FedEx. So you start thinking about networks a little bit differently. So all those combinations made me think of DVD by mail as an extremely efficient digital distribution network that someday the internet would be faster than and cheaper than in lower latency than. So I never thought I loved the mail business. I thought I love network business to deliver entertainment. So that was an example. And then the contrarian part of it was when we were fundraising in 1997, 1998, 99. Everyone was excited by internet delivery. And I'm like, but it's not even close. But it didn't matter. They were excited about it. And so it was very we were contrarian. And we had a contrarian thesis that we could build a business with DVD and then transition it to streaming. And it's precisely because of that contrarian thesis that we didn't have much competition and that because it worked, we create a great value. When did streaming first enter your mind as like clearly this is the place that we're going to have to ultimately go? Oh, that was from the beginning. That's why we name the company Netflix is internet movies. And so it was it was really just about managing the transition even from day one designing the efficient system for DVDs was just a notch on the timeline getting to streaming. Correct. It was one digital distribution network and then eventually we would replace it with another. And we knew that would be a challenge, but we knew the best way to be successful at it was to get big on DVD. And so that became for the first decade. That's all we worked on. One of the other really cool things about your background is that for a long time you're on the boards of I think Facebook and Microsoft, I think you're on the anthropic board and the Bloomberg boards. You've had this sort of of course, Netflix itself at the center of technology. You've had this very cool 360 view of probably the most interesting era of technology development ever. I'm curious from those seats, what the technology landscape looks like to you today. Like what are the key considerations, things that you have your attention on that seem the most important to you from those vantage points? First of all, because of exponential phenomena, it's always the coolest time ever to be in computer science. In the 1980s, I thought, oh my god, so much better than the 1960s will always be true. It'll always be true. I would say as a CEO and Netflix, I learned so much being on the boards of Microsoft and Facebook. They had quite different businesses, but they made very interesting trade-offs the way they thought about things. I mean, both of them were very long-term oriented in what they thought they were willing to lose money in certain new areas for a decade. What I loved about looking at Facebook's business was ad supported and everything they did that was on the core like Instagram worked incredibly well. And when they tried to do crypto or when they tried to do other things that were not big ads of board of businesses, it didn't work well. And so that's an example of companies get good at something. And then if you can add to the core mechanism, that's great. Rather than go off to new fields all the time, that helps a lot. So we've always wanted to add content to the Netflix subscription to make it more and more useful, more and more enjoyable, but kind of keep it like one big model as opposed to also do theatrical movies, or you know, also do something else as a way to expand revenue. Trying to find simple, large models that if they work, you can continue to expand and expand on the kind of core monetization engine that you've already got. Or if you look at Microsoft's case, you know, it's building high-scale software. And then I'm on the board of Bloomberg, which is owned by my Bloomberg. It's a trading stations of Wall Street and media around that. And he's been incredible at kind of this long-term orientation to having this intimate relationship with the customers, like becoming a trusted utility for the industry that's been very powerful. Big moats for that business that are really customer loyalty that he's been serving multiple dimensions for a long time. And then Anthropic, I've only been on the board for a year. It's a wild story because, you know, it's growing so fast. What did you learn from Mark? You mentioned a little bit about what you learned from Facebook, but what did you learn from him specifically? Super committed. Like when you look at the metaverse and convince that there's going to be something beyond the phones, maybe that'll be a class's format and not wanting to be dependent on it, wanting to be really the invention of that layer, which is, you know, extraordinarily ambitious. I probably would have just been like the ad giant if I were doing that business and try to go after TikTok, but he wants to do bigger and broader things. For society, it's great because he does amazing amounts of innovation funded with what would otherwise be the profits of the company. You've been on these great boards. You had a board yourself, of course. What advice would you give to people to either be a great board member or run a great board process themselves? So typically board members want to add value because they're getting paid. It's a human nature thing. And the problem is by the conflict rules, they don't really know the business. If you run an airline, you can't be on another airline's board, but you're doing that board one day a quarter for the most part. And on one day a quarter, it is super hard to add value. And so what you see is a lot of directors who struggle to add value and then management has to be super polite to them. Management can't tell them you don't know what you're talking about because they run the thing. So you see this dysfunctional thing, where board members ask hard questions and management ducks and weeds and is not very functional. So I would say first part is board members to realize, okay, I'm not here to add value. They can hire consultants who know the industry and are not conflicted and that they pay for the advice. So I shouldn't spend my time trying to give advice. So then what am I doing? I'm here as a board member as an insurance layer. If the company falls apart, I will step in and be part of replacing the CEO. And that's basically the entire job, which is replacing the CEO well. And to do that and to have a confidence to do that, you have to learn the business. So you can't be asleep. You've got to really ask a lot of questions and learn what drives the profit streams. How does the business work? What are the issues with it? But again, you're not trying to solve those problems. You're trying to get a grasp of the business so that you can determine, you know, who might be the best person to run the firm. And if you get that right, as say Microsoft shareholders or board did with such an adela, then the business takes off and all the advice in the world doesn't matter compared to that. If you're on a board, don't measure yourself. I did you give a suggestion? Measure yourself. I did you get more and more prepared for the small chance that you will have to take big action. And so it's a lot like a firefighter who drills and drills and drills and hopes that there's never a fire. When selecting for people that would be that insurance layer for your own business, what did you select for? Because a lot of these boards are full of very fancy people like you that are great names to have on a, you know, website as a board of directors. And that seems to be a selection criteria versus like this person's actually going to be good at this insurance layer thing. How did you select board numbers? Yeah, people who I believe will be wise in a crisis. We call it extreme duty of care. So duty cares, one of the responsibilities of a director and we amp it up that they really have to know what's going on. We asked directors to come to management meeting so they can watch what's going on, watch the sausage being made. Again, not so they're adding value, but so they're highly informed. And so we look for people who are wise in crisis. And so a board interview process would be those kinds of things. Tell me about different business crises that have happened. And in case that happens that they would be wise. How much of your time when you were running the business full time was systems structuring and thinking around the business versus like the marginal, you know, strategic initiative or something? I never like booked hours on my calendar to think about the culture. You end up just trying to make things better and then watching what's going well and what's not and making observations. Here's an example. So from maybe 2004 on, we had open compensation. So basically the top 100 or 500 people of the company could see all the comp throughout the company. And the rationale was then they could keep like a similar people in a similar vein. And they would be more trust around gender, around other dimensions that could be discriminatory. Because the data was all out for everyone to see. That was all true, but it also created a lot of petty rivalries. I make a huge amount of money. This other person makes a huge amount plus $10,000 more. And so it got pretty distracting. And ultimately we put it to a question of the VPs about 10 years later, 2016, 17. And they decided to take it away from themselves and from everybody else and do the traditional, you know your direct reports and their themes, but not the whole company. So I would say that was an experiment in human nature, which could have resolved pretty decisively to be less mavericky, but it ended up working a little better. So again, we would take on an experimental view on things. And that's a good example because then you can see like we're not geniuses. We're just willing to question things and try them. So we did open comp for a number of years and then decided that its net costs were negative. Another strategic question that always fascinated me about Netflix was how you determined how much to spend on originals and original content. As much as we possibly could say more about just the core calculus or thinking there. I'm sure there would be some directors that would accept that unlimited out of your money to make something. There's how much on any one show. That's a different question. But in terms of the total budget, we would always try to shovel money into that on the hopes of creating the great next K-pop demon honors. And in terms of any one show, then in the question is what's the likelihood based on what we've seen that this is going to be big. And it's also a competitive market. In the very first original series that we had that helped make our reputation was House of Cards and we had to bid that away from HBO. So as media rights capital was making it, they had bids both from HBO and us and we were a DVD company. So we had to overpay relative to HBO and then they went with us and we had to overpay by a bunch because it was a lot of risk. And then they came through and made a fantastic show. And then we were off to the races and original content. And it's a simple way to think about it, almost like one would think about a venture capital portfolio or something that you want to make lots of bets. And you don't know exactly which one's going to be K-pop demon hunters, but that there being a K-pop demon hunters is the thing that matters that you have some dominant massive franchise. Very much so. But it's similar to venture capital. If every a round were 100 million and there was just an a round. So it tends to be pretty much a single round to fund the construction. You do get sequels and other things you have option rights to. But that would be the big difference from venture. Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions nobody's watching. Ramp puts guard rails on spending before it happens. Real-time limits, automatic rules, zero firefighting. Try it at ramp.com/invest. Every investment firm is unique and generic AI doesn't understand your process. Rogo does. It's an AI platform built specifically for Wall Street connected to your data understanding your process and producing real outputs. Check them out at rogo.ai/invest. The best AI and software companies from open AI to cursor to perplexity use work OS to become enterprise ready overnight, not in months. Visit workOS.com to skip the unglamorous infrastructure work and focus on your product. If you think about the portfolio of content, what else would surprise people about the conversations happening inside the business, especially in the early days of developing that portfolio? The considerations that matter to you as you expanded it. Now it's so many things. In the early days, you're obviously making choices. It's house of cards. It's not something else. There's trade-offs. What would surprise people about the conversation that led to the portfolio that you ultimately chose? Everything for us was around reinforcing the brand, trying to figure out what should the brand be. So the cable networks by necessity were narrow brands because they got one cable slot. And so FX and Hallmark were both interesting doing different types of content, but the handle on the brand gave you the type of content, which was inherently pretty niche because it had one network slot. We were doing something that had all the network slots. And so then we spent a lot of time thinking about how much of the programming do we want to be Hallmark, soft, easy, romantic stories feel good versus FX and be cutting edge and violent and dark versus comedy central. Our main issue relative to the industry was that we had this incredible breadth of content to choose from. And on any new film or series, unless it's completely derivative, there's just so many variables compared to other things. So it ends up you can do asset allocation, which is how much in comedy, how much in drama. But in terms of the stock picking, it ended up being intuition and people's judgment. And then we promoted those people with great judgment who got this right again and again and had, we call it a great taste, but they had more than taste. They had tasted judgment about, you know, would the people deliver, would this come together, and all kinds of ways. So it became just people picking. And so then it's trying to figure out how much money to put in each area. And then the people in those areas would figure out how to best spend it. The other side of the equation, of course, is the beauty of the business model is fixed cost for a piece of content and then a growing subscriber base across which to spread those costs. But that requires that you grow the subscriber base. How did those two interrelate? Like, what did you learn about what sorts of fixed spend on content would create great and reliable and high subscriber growth? What I loved about Microsoft and Facebook's business is they, at that point, basically had one big product or, you know, maybe two highly related ones. And then it was grow those products to be, you know, 50 billion in revenue on a product. When I started Netflix, I was like, well, thankfully we can do this as, you know, one really big product because entertainment was an extremely large market. Basically, every human on the planet watches television to varying degrees. But it's a deeply human thing to watch stories. And so then the question is, okay, what percent of that could we capture? But even today Netflix is about 10% of US television. So we've got a long way to go and internationally, it's less than that generally. So plenty of in terms of how do we think about subscriber growth? We knew that if we could produce better television, make a lower cost and more enjoyable being on demand, that there would be a huge market for it. So it was kind of constrained on essentially product quality. What kind of shows do we have? And now the streaming is kind of flawless and not differentiated between competitors. But for a decade, we did it much better than our peers. That other 90% is that defined as just traditional television? Or is that include like YouTube watched on? No YouTube is about 12% goods, everything sports, video gaming. It's uses of the television screen. I mean, we compete for time on mobile phones too, but we're very small there. It's not a big use case. And television were a big use case, but still really it's under 10%. If you think about that percentage as an important thing for Netflix, the business, what are the competitive frontiers or fields on which you feel like you're competing in something like YouTube? It's more easy to imagine versus cable or network shows or something like this, but versus something like YouTube that's sort of a pure UGC platform. Do you think about it that way? Like we're competing against them and therefore we want to do certain things to win? Well, they're growing and we're growing. And traditional linear is shrinking. So you're right that mostly we both compete with linear TV. But we do worry about YouTube because it's sort of a substitution threat. Does it get better and better with AI creators? And it just becomes more and more people's time. And that's the user generated world. And it's not really user generated. It's on spec. That is there are some very professional people who make content for YouTube, but they don't get paid on it in advance. Then they put it up and they see what kind of ad revenues they get. So in our case, we pre-fund the programs, which gives them a bigger budget. They don't have to do it on spec. And that's really the biggest difference in the business model. But it's ultimately, do we produce content like the perfect neighbors, a documentary that just came out one of these awards? And it's been the number one documentary this last month. Clever, fresh perspective, content like that, or K-pop demon hunters, which was our hit this summer. So it's ability to create those hits. What is that magic? What is shared amongst the people like Ted and others that have been able to reliably and consistently be a part of creating those big hits over time? If only it were reliable and consistent. K-pop was probably our 30th animated film. So it's not at all reliable and consistent. No, it is a lot more like that of art and seeing the contrarian edge. And what's the story? I mean, imagine the pitch for K-pop demon hunters. So it doesn't fit a set of formulas. So in that way, it is a lot like venture and also that a few of the companies will generate outsize returns. What do you think will be the most interesting impacts of AI on the Netflix business specifically? And this could mean from the perspective of cost to create the content it could mean for the service. Where does your mind go as you think about the raw capabilities of the technology? Well, visual effects is one where there's a lot of that workflow that can be automated. But in terms of like recognizing a K-pop demon hunters at a script stage or pitch stage, which is the biggest value creator, you know, which things do we back? That will be a far distant skill. So eventually AI might eat up everything and be better than humans on everything. But, you know, in terms of the sequencing. So think of it. AI is not particularly incented and the companies are not to do long form character development. But at some point, they may do that and focus on that. And then the AI's will be winning the Booker prize and doing the best fiction of the world. And remember, we're only interested in like the top 0.001% of the stories that get written. So simply writing a story. I mean, there's a million film students. We could just go to that. So the issue is trying to find one that's really unusual, extraordinary and recognizing that one early. So I think AI will have had a lot of other effects before it hits us on that. Can you imagine kinds of innovation in the form factors or formats of shows? Like it seems like we've got a couple. You know, there's the show. There's the documentary. There's the full length feature movie. Can you imagine lots of different kinds of form factors starting to proliferate? Well, let's step back a second and think about contrarian thinking generally. So you love contrarian thinking, right? But you probably need to remember that contrarian thinking most of the time is wrong. And once in a while, it's right. And that's when you get the big reward. But if it's a most of the time, contrarian thinking is wrong and the conventional thinking is right. So for example, on formats, people have been trying to think about multi-ending design your own story, short form, quibi. There's all kinds of things, right? And the enduring aspect of a film at one and a half to three hours as a story has stayed strong like the enduring form of a novel or the short story or the TV series. So these things are tapping into something human that other things. So you got video gaming as a different modality. And that's quite a bit different. But like most of the hybrids between TV series that you kind of interact with have been very small markets. It doesn't mean we won't eventually come up with a new art form that's quite different. But I don't think it says easy as choose your own adventure. We're in lean-back mode with TV. And we're mostly wanted to tell us a story. And if you think of young kids two year olds, half of the time they're like, daddy read me a story and half of the time it's daddy play with me. And these like are two different modalities that are different. One is passive. And I mean, I get I think it's very biological and we're selected for it. And one's very active. One of those becomes TV and another becomes video gaming. I'm also fascinated by the technology backbone and story behind Netflix. This sort of invisible part of the business everyone just takes for granted they can hit a button and have this beautiful thing pop up. But I know there's quite a lot of building that happened behind the scenes. Can you tell that part of the Netflix story of what it took infrastructure wise and technology wise to make what we all enjoy possible? Well, it's always been a sort of medium barrier to entry. I would say first with DVDs and we had incredible sorting and shipping machines and postal integration. And I used to spend all this time on types of polycarbonate plastics that break and don't break. And we were impressing plants. And the biggest issue we had was that the DVD would get to you without cracking or shipping or being damaged. It was on time that postal carriers didn't steal it. So it was like a huge amount of machinery to shipping a million red envelope today consistently FedEx style, right? And then certainly streaming the mechanics of getting the bits to people was challenging. We first launched in 2007. And for probably 15 years, the internet was underpowered and you had to do a lot of clever engineering things. But for the most part, there's a hundred companies that stream now consumers can particularly tell a difference between them. So I would say that's now just become part of the base systems and commoditized. What's unique is still being able to do the AI recommendations, all the deep learning on. There's a thousand things on Netflix. You would enjoy which one would you enjoy most at what time? That's still a big area of tech innovation. The gaming is we're trying to push in a different types of games and figure out gaming in addition to TV series and films. Why do gaming at all? Like if you're so good at the core thing and there's room for scale, still, you're only 10%. Why bother with gaming? We used to just be movies and then we expanded the TV series and we're really glad we did that. And then we expanded into the unscripted content, you know, love is blind. So we've always been expanding in new categories and gaming is just another category of entertainment. And so we've got some cool stuff going on the TV where your phone is the remote control, which has higher latency, but it's easy for party mode type games and it's really fun on these sort of social interactions. How do you know when to keep betting on something and how long term to be behind something? Like gaming is a great example. I'm sure there's examples of things you tried that didn't ultimately work that you stopped doing. Sure. Well, let's do one of those. If you look at the New York Times, January 2006, there was a watch of Netflix friends. So this was friend to friend sharing about films and what you are watching. Facebook was still just at Harvard. And then we worked for two or three years on that. Could we get people sharing what DVDs were you picking? Could you give each other? We tried different permission schemes. Then Facebook started doing that whole integration, you know, where they did photos and you could share via Facebook. So then we said, okay, that's the problem. You don't want to set up your own network. And so let's all share via Facebook. And then that didn't work any better than we tried one or two other variants, but it was probably eight solid years. And that's part of what got me on the Facebook board, which is trying to figure out more of this. How is social going to be? And ultimately, that probably got solved by TikTok. How do you think about TikTok? What are your impressions of it? It's like old cable used to be and you'd change channels and you'd just be there numb changing channels, looking for something to watch. But really it was the head of the new thing constantly. So it's hitting that part of enjoyment. Very creative as a business and all of that and very effective. But I would say not the thing I want to spend a lot of time on. When you were CEO, I'm curious how you thought about generating and keeping business power, which leads to free cash flow. And then allocation of free cash. Those seem to be, you know, especially once you've got product market fit and you're growing and you're huge. Those are really important things. How much would you sit down and think about where does our power come from? Is it scale? Is it some other cornered resource? Is it some set of different things and guide the decisions to get more power? How much was that like specifically on your mind? Power is a way of saying above market margins. So the theory is that we can all earn a marginal rate of maybe six percent. But to earn above that is because it's hard for competitors to do what you do. And then you can get an above market margin. So we definitely spend time thinking about that. Which thing should we license our content exclusively, non-exclusively, our deals on televisions and those kinds of things? They would often want to tax us. So a typical television maker thinks, well, Netflix, you're making a lot of money. So if I'm putting the app on the TV, I want 30% like Apple gets. So they would be battles over that and then power is essentially, could they sell a TV without Netflix? Or could we, how many members would we lose if Sony televisions, for example, didn't have the Netflix app? So that's an example of how that worked out. Amazon and business very famously for constantly reallocating capital back into the business to keep generating more customer benefit, which obviously Netflix has done as well. How did you think or would you think about the point in the company's life cycle to do more harvesting to pay dividends to buy back shares to do this sort of thing? And just I'm so curious how you thought through like the capital allocators toolkit of the things that you could do with the capital that you're generating. Well, in most businesses, that's highly material, you know, building a lot more warehouses or something. But honestly, for Netflix, there's very little capital allocation. There's the total budget and per show. But the biggest shows we have like stranger things were less than 1% of viewing in a year. So we have extreme non-concentration and lots of different budgets and spread. There was very little capex of any long term nature margins were pretty close to free cash flow. And then we just have always done buy backs with it rather than build it up. Probably the related tension was how profitable how soon it wasn't a strictly cash one, essentially a P&L margin question. And what we decided is let's have a low margins relative to cable, which ran at like 35, 40% margins so that we can invest a higher percentage of revenue into the content to have better content for our revenue level than we would otherwise. And that became the fundamental lens that we ran the business and they still run it today. How did you know when it was time to lead being full time CEO? Because Greg and Ted were ready. I've been developing them for at least a decade. And I felt like coming out of COVID, they were ready. And then unless I was going to be around for another decade and train a different set of people to take over, this was the time. So it was really driven from them. And since they took over, they've tripled the stock and, you know, they've done incredibly well. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest. Ridgeline is redefining asset management technology as a true partner, not just to software vendor. They've helped firms 5X and scale enabling faster growth, smarter operations, and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. How does something like the set of ideas we've talked about so far translate to a totally different domain like what you're doing with pattern mountain? Like it seems as such a wildly different project in almost every way that I can imagine is very, very different. How much directly translates and how much needs to be left behind given the different nature of the project? So pattern mountain is a ski mountain and real estate development that fell on hard times in Utah. So the original people running it ran out of money so they never finished a lot of the project. We happen to have a house there. Love the place. It's, you know, natural beauty is insane. It's 10,000 acres. And so after retiring from Netflix, I decided to take control of it and best in it and do a turn around. And so then it's rebuilding the staff, rebuilding the vision. And I would say 90 plus percent of talent density, no rules rules. The whole model has worked extremely well and the ability to move fast higher and credible people have them do things. It's everyone being very creative. And I would say the talent density model has been worth the pain I eat the turnover and has created an amazing set of leaders throughout the company. How did you approach it from the beginning in terms of the original vision and plan? So it's a distressed asset that you go in and buy. How do you determine the initial vision and then over the first couple steps to execute against it? It was a series of transactions to gain control. So it took six months to buy out a majority of the company of the shareholders to have control. Everyone wants the billionaire to pay a lot and being clear with them that this thing could collapse if I don't come in. That was stage one. Then stage two was figuring out, okay, this is a great mountain. But if half of it were private like Yellowstone Club and half stayed public as it was, then it could be a real win win with a share operating costs and are more efficient. And we can then have a very uncrowded resort on the public side, which gets to something that's gone on in the ski industry, which is high crowds. So it gets to compete with that. And then on the private side, it's building a 650 home community of ski lovers where they get their basically their own enormous ski resort, the size of heavenly or veil just for the 600 homes. So it's pretty spectacular. In terms of what drives the ski business, what, aside from the real estate stuff, what are the most important variables or considerations that you've figured out in your studying of its history? Yes, skiing is about 1/8 or 1/10 as big as golf, in terms of number of people and playing. So I'd love to close some of that gap, you know, it's cold, but it's very family oriented to get outdoors as social with your friends on the left. It's got some of those same properties. Interesting that there are 25,000 golf courses in the US and about 20% 4,000 are private golf courses. And private golf courses, you get better T times, the nice clubhouse atmosphere, social, you get to know people. And that's really what it is for private skiing also. There's about 500 ski areas instead of 25,000, but only three are private Yellowstone Club, Wasatch Beach Ranch and Powder. So it's very underserved, marked at relative to golf. What's most fun about it to you, the whole project? That it's very right brain. Everything at Netflix was very strategic, logical, a lot of big competitors. In skiing, the competitors are very cooperative. And so I think because you have 20 or 30 miles between you and so it's a lot more collegial. And it's aesthetic. The big wins we've done have been building up the art to Powder Mountain. So there's got a lot of outdoor land art that's incredibly beautiful to ski through. So if you've had the good fortune to go to Storm King North of Manhattan, okay, so think of Storm King on a ski mountain, skiing through it. Tell me about that part of it. So how did you conceive of that and how did you execute it? How does one acquire Storm King like art? It's the conceptual parts, the key, which is we want to have a ski resort and to differentiate. So what are we going to do in summer? Well, you could do zip lines in mountain biking, but it's like it's all been done over and over. And frankly, it's high adrenaline and it's like, okay, but it's not that great a match for real estate sales. But most importantly, it's conventional. It's been done. So what's like interesting and scalable and fantastic, but hasn't been done. And that's the art part. And you know, I've been to Storm King, but Storm King has the level 600 acres. So it's not like in a mountain, but it is outdoor sculpture and incredibly stunning. So again, it was that synthesis to then trying to do that on a mountain. Then it was building in the curators and getting the work going. And now we've got dozens of pieces already in and a lot more coming. That's how it's really coming together as a heart of our summer fall experience. How did you decide to focus so much on education as one of the buckets of your, we talked about powder mountain, but education charter schools, et cetera. It's a huge chunk of your time and philanthropy as well. What was it about that sector that drew you? And I'm just curious for you to riff on the problems that you see in the space. Yeah, and it's interesting. I spend probably a third of my time on powder mountain because it's a joy. And then on the education side, I was a high school math teacher as my first job at a college. And so I've always cared about K12. And I've done a lot of philanthropy in that sector over the last 25 years. And then the new big thing is AI. So it's easy to then put those together. And how are we going to apply AI? The core vision and it's super well articulated by your prior guest around alpha school is kids should be taught individually as opposed to having a teacher stand in front of a class and lecture to them. And that industrial model of the teacher, the sage on a stage, we call it needs to be replaced with individualized tutoring. And prior to AI, individualized tutoring would cost you $100,000 a year per kit. So out of reach of everyone. And so now with software, we can have individualized instruction. And the teachers become more like social workers where they are helping on discussion, social emotional learning, a lot of the more human and emotional factors. But the content transfer, what were the roots of the civil war, how to do fractions, that's all becoming software. And hopefully as quickly as possible, because then it's very global and because kids will learn more. What do you think we can do to speed that up the most? And it could take decades because of the regulated nature of the schools, things move slowly. What could we do that could speed that up? It's focused on apps that really help kids learn more. It's helping parents see that they all wonder, "Hey, with AI coming when my kids six or 16, what's going to happen to them in the workplace?" And they need more and better skills than ever. And every 16-year-old is learning things on AI anyway. So it's having them be more focused on that and less on traditional classrooms. When you think about classrooms, we use it in K-12, we use it in college. And then like in the workplace, we never use it again. You did all this classroom learning and it has like no bearing in your working life. And so again, it's really driving the percentage of kids' time that's not in classroom. And as Joe says, it's helping kids really love school because then they'll continue to love learning. And the classroom in the board of frustration of that is at the heart of it. I'm curious as you think about the future just broadly across all your interests, that you've got a cool purview on the world. What most worries you and what most excites you about the future? I'm part of the anthropocamp where it's good to talk about the negatives. It's not because we think they're going to happen, but because we'll lower the chance of them happening if we're honest and talk about them. So I don't think the AI boomer and doomer thing is that useful. I think we all want to acknowledge there's some pretty significant risks, but they're not dispositive. And then we humans may be able to capture tremendous benefit by harnessing AI for a higher quality of life on a global basis. I'm on team human for making that happen. But I would say that's the biggest swing factor of the next 50 years is how well we do that. What do you think the biggest risks are? Well, the near term risks are unemployment causes societal chaos and strife. So if you were to get a lot of unemployment, then you might get radical politicians promising to get rid of AI and that destabilizes society. There's the long-term power competition between us and say China. And then is war become? How many robots do you produce? And be unfortunate if we both end up having to spend a bunch of money on that because of distrust, kind of a new Cold War would soak up a lot of GDP growth. In the benefit side would be that we cure disease, we get nuclear fusion with huge amounts of low-cost energy. Humans don't have to work as much, maybe not at all. They get to do things like learn chess and learn how to play all kinds of games. You learn biology for fun like you learn chess today. So there's tremendous upside to automating a lot of this and taking it to the next level. It's just keeping humans on top as the beneficiary of them. My traditional closing question for every interview is the same. What is the kindest thing that anyone's ever done for you? 30 years ago, I worked at a startup. I was a frontline engineer, 28, so I do it all nighters all the time. I used to have coffee cups spread around my desk and over a couple days, then we'd get cut ugly and messy and janitor every now and then we'd clean them all and I'd come in, they'd be clean mugs. I didn't think about it that much. One morning woke up early and in those days, you had to go in the office because of the computers were there. You couldn't take them home. So I went into the office at 4.35 in the morning, walked in, went into the bathroom, and there was my CEO washing coffee cups. I looked at him and I was like, "Berry, are those my cups?" He said, "Yeah." And I said, "Have you been washing my cups all year?" And he said, "Yeah." And I said, "Why?" And he said, "You do so much for us, and this is the one thing I could do for you." And I was just very moved about his humility and his caring kindness in your question. And so I felt like, "God, I'll follow this guy to the ends of the earth." Wow. So simple gestures. Holy cow. Great story. Amazing place to close. Thank you so much for your time. Real pleasure, Patrick. If you enjoyed this episode, visit JoinColossus.com where you'll find every episode of this podcast complete with hand-edited transcripts. You can also subscribe to Colossus Review, our quarterly print digital and private audio publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at JoinColossus.com/Subscribe. You know how small advantage is compound over time that's true in investing and just as true in how you run your company. Your spending system is your capital allocation strategy. Ramp makes it smarter by default, better data, better decisions, better economics over time. See how at ramp.com/invest. Rogo does. It's an AI platform built specifically for Wall Street, connected to your data, understanding your process, and producing real outputs. The best AI and software companies from open AI to cursor to perplexity use WorkOS to become enterprise-ready overnight, not in months. Rigline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5x in scale, enabling faster growth, smarter operations, and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm.