Reed Hastings - Building Netflix - [Invest Like the Best, EP.453]

6 Jan 2026 · 1 h 2 min · 26 chapters

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Podcast Episode Notes: Reed Hastings - Building Netflix - [Invest Like the Best, EP.453]

Episode Overview In this episode, Patrick O'Shaughnessy interviews Reed Hastings, the co-founder and former CEO of Netflix. The conversation dives into Hastings' insights on building Netflix, the company's culture, strategic decisions, and the lessons learned from both successes and failures.

Key Themes and Discussions

  1. Simple Ideas with Serious Execution
  2. Concept of Talent Density: Hastings emphasizes the significance of maintaining a high talent density within the organization, which means having highly skilled individuals who can drive innovation and performance.
  3. Focus on Streaming: Hastings notes that the DVD rental model was just a stepping stone toward their ultimate vision of a streaming service, which was identified from the company's inception in 1997.
  1. Company Culture and Strategy
  2. Talent Management: Hastings discusses the “Keeper’s Test,” a metric used to determine if a manager would attempt to retain an employee if they were considering leaving. This approach encourages honesty and high standards within the team.
  3. Open Compensation: Initially implemented to promote transparency, Hastings later acknowledged the drawbacks, including petty rivalries that arose due to competitive comparisons.
  1. Learning from Mistakes
  2. Qwikster Incident: Hastings reflects on the disastrous decision to separate DVD and streaming services, which led to significant customer backlash and stock price decline. This failure taught Hastings the importance of collective decision-making and the value of diverse opinions within the executive team.
  1. Innovation in Content Strategy
  2. Venture Portfolio Approach: Netflix's content strategy is likened to a venture capital model, where various shows and films are treated like investments, ensuring that the risk is distributed across a diverse portfolio.
  3. Competitive Landscape: The episode discusses the challenges posed by platforms like YouTube and traditional TV, emphasizing the necessity for Netflix to create compelling, unique content to maintain viewer engagement.
  1. The Role of Technology and AI
  2. Technological Backbone: Hastings describes the infrastructural challenges faced by Netflix, especially in the early days of streaming, and the importance of building robust technology to deliver a seamless viewer experience.
  3. Future of AI: The conversation touches on the potential impacts of AI on content creation and recommendation systems, acknowledging the transformative possibilities while also being cautious of the challenges it might bring.
  1. Capital Allocation and Financial Strategy
  2. Investment Philosophy: Hastings discusses how Netflix prioritized content spending to enhance user experience and subscriber growth, always aiming for a balance between quality content and cost-efficiency.
  3. Shareholder Returns: The decision to prioritize reinvesting in content rather than immediate shareholder returns reflects Netflix's long-term vision of growth and market capture.
  1. Transitioning Leadership
  2. Stepping Down as CEO: Hastings shares insights on deciding to step down when he felt confident in the leadership capabilities of his successors, highlighting the importance of succession planning in business.
  1. Current Ventures and Future Goals
  2. Powder Mountain: Hastings discusses his current project in real estate and revitalizing a ski resort, applying many of the lessons he learned at Netflix, particularly around talent density and innovation.
  1. Thoughts on Education
  2. Focus on K-12 Education: Hastings expresses his commitment to improving education through technology, advocating for personalized learning experiences and the use of AI to enhance educational outcomes.

Key Takeaways

  • Sustaining Talent Density: High-performance standards are crucial for fostering innovation.
  • Learning from Failure: Mistakes, like the Qwikster failure, can lead to meaningful organizational change.
  • Content as an Investment: Treating content creation like a venture portfolio can optimize success.
  • Long-term Vision: Prioritizing reinvestment over short-term profits can lead to sustainable growth.

Conclusion Reed Hastings' insights offer valuable lessons for entrepreneurs and executives in various fields, emphasizing the importance of a clear vision, talent management, innovation, and the willingness to learn from mistakes.

Additional Information

  • For more details, full show notes, and links to mentioned content, visit the episode page [here](https://www.joincolossus.com).

Sponsors

  • Ramp: Streamlining company spending to reduce expenses.
  • Vanta: Automated compliance and monitoring.
  • Rogo: AI platform for finance professionals.
  • WorkOS: Enabling SaaS companies to add enterprise features easily.
  • Ridgeline: Real-time operating system for investment managers.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Understanding Netflix's Success

4:44 to 7:42

Exploring the key principles behind Netflix’s successful business model.

“Netflix has effectively been scaling up its core original model since its inception.”

The Origins of Talent Density

10:52 to 12:20

Reed Hastings shares insights on the importance of talent density in companies.

“And like the Yankees or the LA Dodgers, they often have the best players.”

Managing for Talent Density

12:20 to 14:00

Strategies for maintaining high talent density as companies grow.

“And mine is more, have relatively open doors.”

Managing on the Edge of Chaos

14:00 to 14:50

Learn how to balance creativity and chaos in organizations.

“And the looser that you can run, the more creative that the organization will be.”

The Art of Letting People Go

14:50 to 16:36

Discover effective strategies for managing employee terminations.

“I'm curious with the 20 % attrition rate, what you learned about letting people go well and the right way.”

Lessons from Quickster's Mistake

16:36 to 19:15

Understand the impact of rapid decisions on company direction.

“How did the keeper's test literally work?”

The Value of Non-Consensus Decisions

19:15 to 22:16

Explore how non-consensus ideas can lead to significant value creation.

“If you think about 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?”

The Evolution from DVD to Streaming

22:16 to 23:19

Learn how Netflix transitioned from DVD rentals to streaming.

“And it's precisely because of that contrarian thesis that we didn't have much competition in that.”

Insights from Board Membership

23:19 to 26:18

Gain insights on the technology landscape and board dynamics.

“I'm curious from those seats, what the technology landscape looks like to you today?”

Effective Board Management

26:18 to 28:00

Understand how to run a great board process and add value.

“For society, it's great because he does amazing amounts of innovation funded with what would otherwise be the profits of the company.”
Show all 26 chapters

Selecting Board Members for Crisis Management

28:00 to 29:08

Learn about the criteria for choosing board members who can handle crises effectively.

“how does the business work, what are the issues with it?”

Cultural Insights at Netflix

30:17 to 31:46

Explore the evolution of Netflix's compensation strategy and its impact on culture.

“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?”

Budgeting for Original Content

31:47 to 33:51

Understand Netflix's approach to budgeting for original content and its calculations.

“So again, we would take on an experimental view on things.”

Building a Diverse Content Portfolio

33:52 to 35:44

Learn how Netflix made strategic decisions to build a diverse content portfolio.

“I mean, now it's so many things, but in the early days, you know, you're obviously making choices.”

Fixed Costs and Subscriber Growth

35:45 to 37:05

Discover how Netflix manages fixed costs while seeking subscriber growth.

“And so then it's trying to figure out how much money to put in each area.”

Competing with YouTube and Other Platforms

37:06 to 38:25

Examine Netflix's competition with platforms like YouTube and traditional TV.

“we knew that if we could produce better television, make it lower cost and more enjoyable being on demand, that there would be a huge market for it.”

AI's Impact on Content Creation

38:26 to 40:15

Explore the potential effects of AI technology on Netflix’s content creation process.

“But we do worry about YouTube because it's sort of a substitution threat.”

The Future of Show Formats and Contrarian Thinking

40:16 to 42:00

Discuss the future of show formats and the challenges of contrarian thinking in entertainment.

“Well, visual effects is one where there's a lot of that workflow that can be automated.”

Exploring Film and TV Formats

42:00 to 43:30

Discover the enduring appeal of traditional storytelling formats in film and TV.

“So, for example, on formats, people have been trying to think about multi-ending, design your own story, short form, quibi.”

The Netflix Technology Backbone

43:48 to 46:24

Understand the infrastructure and technology that made Netflix a success.

“I'm also fascinated by the technology backbone and story behind Netflix, the sort of invisible part of the business.”

Capital Allocation at Netflix

46:24 to 49:30

Explore how Netflix managed capital allocation and strategic investments.

“So this was friend to friend sharing about films and what you were watching.”

Transitioning to Powder Mountain

49:30 to 51:20

Learn about Reed Hastings' shift from Netflix to developing Powder Mountain.

“But honestly, for Netflix, there's very little capital allocation.”

Art and Real Estate at Powder Mountain

51:20 to 55:52

Discover how art is being integrated into the Powder Mountain experience.

“So the original people running it ran out of money, so they never finished a lot of the project.”

The Future of Education and AI

56:00 to 58:04

Explore how AI can transform education from traditional classrooms to personalized learning.

“And now we've got dozens of pieces already in and a lot more coming.”

Risks and Rewards of AI

58:04 to 1:00:29

Discuss the potential risks and benefits of AI on society and the economy.

“It's focused on apps that really help kids learn more.”

A Humble Gesture: Kindness in Leadership

1:00:29 to 1:02:16

Learn about a touching story that highlights the importance of kindness in leadership.

“Humans don't have to work as much, maybe not at all.”
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Transcript

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2:38And one of the biggest hurdles, whether you're open AI, cursor, perplexity, Vercel, 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 SaaS.

3:12They can't afford to wait on 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'Shaughnessy, 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.

3:47If 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'Shaughnessy is the CEO of Positive Sum. 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 Sum may maintain positions in the securities discussed in this podcast.

4:22To learn more, visit psum.vc. The most interesting thing about studying Netflix and talking to read 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. Reid 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.

5:10And the second is this notion of talent density. This is a term that now gets 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. Customer trust can make or break your business. And the more your business grows, the more complex your security and compliance tools get.

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6:19They're redefining what's possible in asset management technology, helping firms scale faster, operate 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 Ridgeline? Ridgeline is a technology partner, not a software vendor, and the people really care. I get sales calls all the time and I ignore them.

6:50Ridgeline sold me very quickly. We went from$7 billion to$23 billion and the goal is$50 billion. Ridgeline was the clear frontrunner to help us scale. In your view, what most distinguishes Ridgeline? They reimagined how this industry should work, because obviously they were operating on another level. It's worth reaching out to Ridgeline to see what the unlock can be for your firm. Visit ridgelineapps.com to schedule a demo. I want to go back to your first business and the sort of origin story of this notion of talent density that you've become very famous for. We'll talk about talent density for sure.

7:26It'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? So I founded Pure Software in 1990 and grew kind of 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.

8:08And 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. And so it was through that experience that I realized, okay, 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. And we should manage software much more artisanally 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.

8:53I 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 success, which is being very direct. Similarly with loyalty. We've come to see loyalty, which is something in your family, like you would never fire your brother if you were tight on money, okay? 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 where family.

9:39All 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.

10:22How do you protect against the natural way that companies seem to bleed down towards lower talent density over time? Like 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 learned 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.

10:59It'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 about each stage of the funnel to creating talent density in a business, starting with how you found people in the first place, what the most reliable ways were of finding people, and then also how you evaluated them. And 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?

11:42I'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 into Stanford 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.

12:17And 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 to reason that maybe your one-year attrition rate was higher than, say, Google's or somebody else's. Oh, quite a bit, yeah. What was it like? Do you remember? I think it was 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.

12:47And 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.

13:29If 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 say more about loose? If you overmanage, for example, a tight process or specific hours that you have to be in the office or a wide variety of things, you filter out performance and creativity. And the looser that you can run, the more creative that the organization will be.

14:10So we talk about it as managing on the edge of chaos. You don't actually want to fall into chaos, okay? In chaos, the product barely gets released. It's full of bugs. People are upset. Payroll's not 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 variance. If you're going to be a creative organization, you want to be high variance, high creativity, and again, managing on the edge of chaos.

14:52I'm curious with the 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 competence 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.

15:34Two, 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.

16:17The 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 old keeper test framework. How did the keeper's 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 severance 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?

17:00Because that turns out to be a good test relative to, you know, all the relief we sometimes feel when someone not great moves on. 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? Like, I'm just curious what it felt like to watch that happen.

17:36So 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. Unfortunately, most of the customers were mostly using DVDs. Disagreed. So yeah, they were still, mailed me the discs. And so they didn't like it. Lots of cancellations, stock dropped 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.

18:21But they kind of said to themselves, geez, Reed's made 18 decisions right before. So, you know, I'm probably wrong and Reed's 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.

19:08So 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 a hole. If you think about 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?

19:42Well, 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 then 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 the decisions, but it's good for them to collect a lot of information.

20:21And 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 AOL on CD-ROM.

21:05So 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 it turns out you calculate it and it's like terabits 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 and lower latency than.

21:51So I never thought I love 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, 98, 99, everyone was excited by internet delivery. And I'm like, but it's not even close, but 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 in that. Because it worked, we created great value.

22:32When 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 named the company Netflix's Internet Movies. And so 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.

23:06One of the other really cool things about your background is that for a long time you were 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?

23:36First 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. It'll always be true. It'll always be true. I would say as a CEO of Netflix, I learned so much being on the boards of Microsoft and Facebook. They're 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.

24:19And when they tried to do crypto or when they tried to do other things that were not big ad supported 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.

25:04Or 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 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 multi-dimensions for a long time. And then Anthropic, I've only been on the board for a year and it's a wild story because, you know, it's growing so fast.

25:45What 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 convinced that there's going to be something beyond the phones. Maybe that'll be a glasses 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 was 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.

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26:25You'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.

27:04And 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 in weeds. And it's 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.

27:41If 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 the 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 Satya Nadella, then the business takes off.

28:21And all the advice in the world doesn't matter compared to that. If you're on a board, don't measure yourself by did you give a suggestion. Measure yourself by 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 website as a board of directors.

28:54And that seems to be a selection criteria versus like this person is actually going to be good at this insurance layer thing. How did you select board members? Yeah, people who I believe will be wise in a crisis. We call it extreme duty of care. So duty of care is one of the responsibilities of a director. And we amp it up that they really have to know what's going on. We ask directors to come to management meetings 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.

29:29And 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. Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions nobody's watching. Ramp puts guardrails on spending before it happens. Real-time limits, automatic rules, zero firefighting. Try it at ramp.com slash 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.

30:02Check them out at rogo.ai slash invest. The best AI and software companies from OpenAI to Cursor to Perplexity use WorkOS to become enterprise ready overnight, not in months. Visit workos.com to skip the unglamorous infrastructure work and focus on your product. 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.

30:38Here'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 similar people in a similar vein and there would be more trust around gender, around other dimensions that It 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.

31:25And they decided to take it away from themselves and from everybody else and do the traditional, you know your direct reports and their teams, but not the whole company. So I would say that was an experiment in human nature, which got 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.

32:05Another 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 an unlimited half 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 hunters. In terms of any one show, then the question is, what's the likelihood, based on what we've seen, that this is going to be big?

32:43And 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. Okay, so we had to overpay relative to HBO, and then they went with us. And we had to overpay by a bunch because, you know, it's 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 is 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?

33:34Very 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. 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? I mean, now it's so many things, but in the early days, you know, you're obviously making choices.

34:10It's house of cards. It's not something else. And there's tradeoffs. What would surprise people about the conversations that led to the portfolio that you ultimately chose? I mean, 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.

34:47And 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 sort of 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.

35:28And then we promoted those people with great judgment who got this right again and again and had, we called it great taste, but they had more than taste. They had taste in judgment about, you know, would the people deliver? would this come together in 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.

36:02But 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 is an extremely large market.

36:39Basically, 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, OK, what percent of that could we capture? Even today, Netflix is about 10 percent of U.S. 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 it 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.

37:19What kind of shows do we have? 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 does that include like YouTube watched on? No, YouTube is about 12%, includes everything sports, video gaming, its 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, we're 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 against something like YouTube?

38:04It'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 are 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 of people's time? And that's the user generated world.

38:39And 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 you know 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 won all these awards and it's been the number one documentary this last month you know clever fresh perspective content like that or k-pop demon hunters which was our hit this summer So, you know, it's ability to create those hits.

39:25What is that magic? Like, 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, right? 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 outsized returns.

40:03What 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.

40:43But, you know, in terms of the sequencing, so think of AI as 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 AIs will be winning the Booker Prize and doing the best fiction of the world. And remember, we're only interested in like the top 0.0001 % of the stories that get written. So simply writing a story, I mean, there's a million film students. We could just go to them. 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.

41:25Can 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 you have to say most of the time, contrarian thinking is wrong.

42:00And 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've 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.

42:46It doesn't mean we won't eventually come up with a new art form. That's quite different. But I don't think it's as 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, again, 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.

43:24As 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 slash invest. Ridgeline 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. I'm also fascinated by the technology backbone and story behind Netflix, the sort of invisible part of the business. everyone just takes for granted they can hit a button and have this beautiful thing pop up.

43:57But 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.

44:32It was on time. The postal carriers didn't steal it. So there was like a huge amount of machinery to shipping a million red envelopes a day 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 100 companies that stream now. Consumers can't particularly tell a difference between them. So I would say that's now just become part of the base systems and commoditized.

45:10What'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 into 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 to TV series, and we're really glad we did that. And then we expanded into unscripted content, you know, Love is Blind.

45:51So 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 launch of Netflix Friends.

46:26So this was friend to friend sharing about films and what you were 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, OK, 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. Then we tried one or two other variants, but it was probably eight solid years.

47:00And 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 that hit 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 a 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 flow.

47:43Those 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 6%, 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.

48:20So we definitely spend time thinking about that. Which things should we license our content exclusively, non-exclusively are 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. Okay. So they were the 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.

49:02Amazon and Bezos 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 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 were generating. Well, in most businesses, that's highly material, you know, building a lot more warehouses or something.

49:32But 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 one percent 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 buybacks 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.

50:26And 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 leap 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. 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 Powder Mountain?

51:02Like it seems it's such a wildly different project in almost every way that I can imagine. It's very, very different. How much directly translates and how much needs to be left behind given the different nature of the project? So Powder 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. I 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 turnaround.

51:40And 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, hire incredible 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.e. 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?

52:21And then what were 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 where they 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 vale 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?

53:35Yeah, skiing is about one eighth or one tenth 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 and social with your friends on the lift. It's got some of those same properties. Interestingly, there are 25 ,000 golf courses in the U.S., and about 20%, 4 ,000, are private golf courses. And private golf courses, you get better tee 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 Peaks Ranch, and Powder.

54:19So it's very underserved market 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. It's, I think, because you have 20 or 30 miles between you. And so it's a lot more collegial. and its 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.

55:04It's beautiful, yeah. Okay, so think of Storm King on a ski mountain. Skiing through it. Yes, and skiing through it. Tell me about that part of it. So how did you conceive of that and how did you execute it? Like how do you, how does one acquire Storm King-like art? It's the conceptual part 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 and 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.

55:33But 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'd been to Storm King, but Storm King has a 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 side's really coming together as the heart of our summer-fall experience.

56:12How did you decide to focus so much on education as one of the buckets of your time? We talked about Powder Mountain, but education, charter schools, et cetera, is 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, 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 out of college. And so I've always cared about K-12. And I've done a lot of philanthropy in that sector over the last 25 years.

56:47And 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 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 kid. 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're helping on discussion, social, emotional learning, a lot of the more human and emotional factors.

57:42But 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? It could take decades because of the regulated nature of 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 kid's six or 16, what's going to happen to them in the workplace? And they need more and better skills than ever.

58:22And, you know, 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 and the boredom and frustration of that is at the heart of it.

59:04I'm curious, as you think about the future just broadly across all your interests, 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 anthropic camp 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 higher quality of life on a global basis.

59:41I'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, you know, is war become how many robots do you produce? And, you know, it'd be unfortunate if we both end up having to spend a bunch of money on that because of distrust.

1:00:24Kind of a new Cold War would soak up a lot of GDP growth. And 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?

1:01:0630 years ago I worked at a startup I was a frontline engineer 28 so doing all-nighters all the time I used to have coffee cups spread around my desk and over a couple days it would get kind of ugly and messy and janitor every now and then would clean them all and I'd come in there'd be clean mugs and 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. And I looked at him and I was like, Barry, are those my cups?

1:01:47And 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. And 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.

1:02:28You 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 slash subscribe.

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From the publisher

My guest today is Reed Hastings, the co-founder and former longtime CEO of Netflix.

Netflix is an example of two ideas that everyone talks about, but are extremely hard to do in practice. The first is finding a simple idea and taking it extraordinarily seriously. Reed talks about how even the DVD business was nothing more than a stepping stone toward streaming, which they envisioned from the company’s inception in 1997. The second is talent density, and what it actually takes to set and sustain an exceptionally high bar over decades as a company grows. 

We talk about how those ideas shaped Netflix’s culture and strategy, what Reed learned from mistakes like Qwikster, and why Netflix treated content like a venture portfolio.

We also discuss Reed’s work today. He shares how he’s thinking about AI, what he’s learned from serving on the boards of Microsoft, Meta, Anthropic, and Bloomberg, and what excites him about Powder Mountain, the ski resort he acquired after Netflix.

Please enjoy my conversation with Reed Hastings.

For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠

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This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vanta. Trusted by thousands of businesses, Vanta continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit vanta.com/invest. 

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This episode is brought to you by Rogo. Rogo is an AI-powered platform that automates accounts payable workflows, enabling finance teams to process invoices faster and with greater accuracy. Learn more at Rogo.ai/invest.

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This episode is brought to you by ⁠WorkOS⁠. WorkOS is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit ⁠WorkOS.com⁠ to transform your application into an enterprise-ready solution in minutes, not months.

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This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com.

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Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠).

Timestamps

(00:00:00) Sponsors

(00:03:33) Welcome to Invest Like The Best

(00:04:29) Intro

(00:05:43) Sponsors

(00:07:16) The Concept of Talent Density

(00:11:19) Evaluating Talent

(00:13:47) Managing on the Edge of Chaos

(00:14:51) Why Netflix Gave Large Severance Packages

(00:16:37) The Keeper’s Test

(00:17:07) The Qwikster Mistake

(00:19:15) The Informed Captain

(00:20:39) How to Come Up with Good Ideas

(00:22:32) Transitioning to Streaming

(00:23:05) Being on the Board of Facebook, Microsoft, Anthropic & Bloomberg

(00:26:25) The Role of a Board Member

(00:29:37) Sponsors

(00:30:15) Why Netflix Had Open Compensation

(00:32:04) Netflix’s Content Strategy

(00:37:52) Competing with YouTube and Traditional TV

(00:39:23) Creating Hit Content

(00:40:02) Impact of AI on Netflix

(00:41:24) Innovations in Show Formats

(00:43:23) Sponsors

(00:43:44) Netflix's Technology Backbone

(00:45:29) Expanding into Gaming

(00:46:06) Lessons from Failed Projects

(00:47:30) Financial Strategy and Capital Allocation

(00:50:27) Stepping Down as CEO

(00:50:52) Powder Mountain

(00:56:08) Focus on Education and AI

(00:59:00) Risks and Benefits of AI

(01:00:56) The Kindest Thing

(01:02:56) Sponsors

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