The Realignment Ep. 43: Balaji Srinivasan vs. Big Media

Yeah, recording a video.

Karama is always fancy live. Okay, great. Balaji, welcome to the realignment.

Thanks for having me, guys. Yeah.

Good to see you, Balaji.

So there's a million things we could talk about you with, but I think what we're going to focus on first is this idea of decentralizing media because obviously you had a bit of an interesting Twitter dissertation discussions, shall we say, about the New York Times. And obviously we could sort of focus on the personalities. But I think the thing that makes actually interesting conversation point is it's clear about something bigger, sort of like a bigger set of ideas and conflicts within east coast media and Silicon Valley. So it'd be great to sort of see where is your thinking at on all these topics.

Yeah, so I have a tweet actually from last year where I said mainstream media, then social media, then decentralized media. And that means decentralized reporting, sourcing, hosting, distribution, payments, bounties, predictions, reputation verification, consensus and truth. Okay, that's a ton of stuff right there. That's a PhD thesis. Right. But let me kind of give. So that's like a bunch of keywords. I can drill into each of them and I will do that, but at a high level. Let me kind of describe one way that I and really other folks in tech think about this nowadays because a lot of the concerns and things I've said on social media are by no means limited to me. They're something that really a lot of folks in the global tech community have been thinking about for some time just to also level set. Actually an interesting point, just a day or two ago, the New York Times announced a new CEO, Meredith Levine, and seems extremely well qualified and so on. There's an interesting interview in the information which talked to her and you know what her vision for the New York Times was. Like a tech company. That's exactly right. Right. And you know, with music downloads and, you know, movies and films and so on, sort of like a, like a Netflix, Spotify, Apple News ish combo. Though of course, you know, the news is where their first party starts. And in a sense, you know, this is like the path not taken in the year 2000. There's sort of a fork where, you know, tech folks, you know, Yahoo tried to become a media company and it didn't work for a number of reasons.

One was Community. They actually had a bunch of shows like on.

They had a bunch of shows. Yeah, it turned out that was like the infrastructure era of the Internet and people were mainly interested in tools and it just wasn't ready at that time. Or maybe the personnel, you know, sometimes you have an elan, they can pull the future 10 years earlier. You know, SpaceX and Tesla are still ahead of their time. And you were even further ahead when he started them, right? Or actually he didn't start Tesla, but you know, when he, when he invested in it. But point being that an entire generation of tech companies saw the lesson of Yahoo that essentially you can't be a media company and a tech company and they just built pure tools, right? So that's Google, obviously, but then it's also Facebook, which called itself a social utility, right? That's the entire concept of user generated content like YouTube and entire set of social networks. It's also Dropbox, it's also all the SaaS apps, right? These are all tools that are, you know, content, you know, I shouldn't say agnostic because there's certainly, you know, filtering and defaults and so on put into them. You know, is it vertical video or is it 140 characters? There's definitely constraints, right? But for the most part they're pipes. And this was considered, and until very recently the conventional wisdom that you don't do media companies, right, because those aren't actually important or profitable. And then on the other side of things, the legacy media companies were not innovating in terms of doing search engines or social networks. Just as sort of an interesting historical tidbit, Don Graham actually almost invested in Facebook in the Washington Post.

That's right, him and Zuckerberg, they came very close.

It was very close, right? And Don Graham bowed out of it. That was a mistake for him. But you know, not that he needs the money or whatever, but that might have led to a different universe where maybe the Post doesn't get acquired by Bezos or there's like a post Facebook fusion, who knows, right? And you know, so what happened was for many years essentially media, you know, kind of mocked tech or thought of tech as a kind of little brother, kid brother over here in San Francisco. And tech just grew and grew and grew. And I think that by about 2013 or thereabouts, right after the first Obama reelection, tech and media were basically allied going into Obama's reelection. And you can pinpoint it to like December 2012, if you remember that, like there's a bunch of articles in Politico, the Atlantic about how the nerds go marching in and tech people helped Obama get reelected. And there's a lot of positive media coverage and so on around that, right? And you can date the, you Know, like the. The silico bureaucrat split, you know, the West, east coast split to basically, like, about four months later when, you know, post Obama's reelection, there was now a conflict between the east coast and the west coast, where east coast folks sort of woke up out of their reverie and realized that for the last four years, these tech folks who they had kind of thought of as just a, you know, just another constituency, had now just risen up to such an extent and taken all their ad revenue, especially Google and Facebook, and thus began a spate of negative articles that grew and grew and grew over the last six years in the form of the tech lash. Right. Going after every kind of technology company.

Quick thing, Balaji, because you just made an allegation which I think is an interesting one, which is that the negative coverage of the tech industry came because of the business competition.

Right.

So the second that all these sort of publishers were losing ad revenue to Google and Facebook, they started saying, we need to take this thing hostilely. I think that's. Do you have any evidence for that? Yeah, it's not just. Do you have any evidence for that? But I think the reason why I'm skeptical of that idea is that if you actually talk to reporters, of which Sager has actually been, they don't know anything about the business side to their detriment.

Right.

Because, you know, the reason why Craigslist was able to sort of take classified advertising from places like the New York Times, the Washington Post, and local papers was that there was this. Chinese wall is the term between the editorial operations and the actual business side. So I just don't see a world where actual tech reporters started thinking, holy crap, the business model that we use is under threat. So we're gonna start writing. Thanks, Sagar. You've got something, too.

One second.

Yeah. I'm sending you some tweets.

Okay. Yeah, we're looking.

We're looking. Okay. All right. Put this on the screen, Jamie, or.

Our Rogan sensor budget isn't there yet, unfortunately.

All right.

Yeah. Right.

Well, so if you Let me just read this to you. So there's a tweet I had on May 16 quoting Ben Thompson of Strateckery. Okay. And he, in turn, is quoting the NYT reporter. And here's his quote. That is why this section of Smith's article is so illuminating and so depressing. Just look at the logic chain. Smith lays out media crusades against tech. Governments respond to media. Facebook has taken a beating. Facebook pays media companies. Media approves. Again, this is Smith's logic chain, not mine. At what point do we believe him?

So here's the thing though, and this is. I've read that article.

That's just one. Yeah, yeah.

I really, I really suggest everyone read it. But this is why I'm just trying to focus on the specific timeline here.

Right.

Because 2016-2017-2018-2019. I really buy that analysis.

Right.

But in 2013, 2013 was still a time when a lot of media companies like Buzzfeed, Mike stuff that even A16Z where you used to be a VC at were investing in, they still really saw themselves positively. So I'm just sort. I think that it could be true that there's this negative relationship now, but I just don't think in 2013 the issue is that was driving the tech wash.

Sorry. Yeah, so one second. I think I, based on my conversations with a lot of these people, kind of like where I think the animus comes from. I actually think it's about cultural power and I think that they don't think about it necessarily in the same way that we are about the business models. And yeah, it has become a lot more brazen kind of in the ad revenue crash. We should remember, I mean 2012, 2013 was still not, it was quite a profitable year for a lot of media companies. What I think they saw was the ascendance of these titans really in politics that are beginning to take on the role that they once had. So the anointing role in politics that Mark Zuckerberg could play such a key role in the 2012 presidential election, when it used to be that they had almost a monopoly on the, on the use of influence, so to speak, like in warfare terms. And then all of a sudden you have this competitor that just grew so dramatically. Right. In only a four year period. I mean, Barack Obama famously only sent one tweet in 2008 on the night of his election. And you think about how much influence Twitter had in 2012. I think it's much more about a power relationship than it is necessarily about business. But go ahead.

I think it's. So to be clear, I do think it's all of the above. Absolutely. It's advertisers and its influence. But let me give a few key kind of points here just to help level set. Right. So I'm going to show you a graph which shows that the revenue disruption and by the way, I absolutely agree that the cultural aspects, like in terms of influence are as important or really more so than even the business aspects, but it's both you know, in the sense of like when it sounds so much like any individual reporter is thinking consciously about the economics of any individual article, but globally, they're seeing, oh, these people that I went to school with, who they think of as being as smart as them are now much richer than them. And these redwood trees are just going up in technology in Silicon Valley. And meanwhile, budgets are being cut, newsrooms are being shut down, local news is getting crushed, their friends are out of jobs. It's harder and harder and it's tougher for them. And so there's an economic squeeze there that's happening. It's not so much about any individual line item, it's just a kind of global perspective of, oh, our industry shrinking. And these folks is expanding. Now, of course, you know, the question of, oh, are they smart? Or whatever, like this is something where, you know, you're not going to get lots of, you're going to get lots of different opinions on this. But certainly one concept is, you know, if you have somebody who's 6ft and stands next to Steph Curry. I think STEPH Curry is 6ft, actually. What's his actual height? Is he 6ft? Is he 6 3?

And we really need Jamie to get us.

Yeah, okay, so he is.

He's 6 3. He's 6 3.

Okay, fine. All right, so let's say, you know, you have a 6 foot 3 person who stands next to Steph Curry. So that person is certainly equal to Steph Curry in height terms, but that does not mean that person can shoot a basketball like Steph Curry can. Right, right. Clearly, you know, they're equal in one dimension, but perhaps, you know, there's a huge skill gap on the other. Right. And so just the fact that you can carry on a conversation with somebody like Drew Houston doesn't mean you can program like Drew Houston, who coded the first version of Dropbox in this laptop on a bus. Right. And I think that is something which is a huge skills gap that is actually not perceptible or it's not as easily perceptible. Right. And one of the things about that is it also means that we have a group of folks from around the world. You know, tech is actually, it genuinely is more global of a phenomenon than, you know, kind of the east coast media. It's much less nepotistic. You know, nobody inherited Google or Facebook. That wasn't given to you, it wasn't handed down.

Someone almost inherited WeWork. But that's the one exception.

There's exceptions. Right. But basically, like, you know, It's, I can name a few people who are second generation venture capitalists, for example, but it's pretty unusual actually, relatively speaking. Most of these folks are first gen, they really are new money, right. Whereas on the east coast people are impressed by, you know, the, the so and so family and you know, without naming in a particular family, like inherited wealth is actually impressive there and it's completely unimpressive in, you know, in tech, right. In the West Coast, Right. So that's kind of a third dimension, is a culture clash, right? It is, it is influence, it is, you know, it is advertising revenue. But it's also culture where, you know, in many ways actually tech is like a fork of the East Coast. You know, how like a long time ago Yale was like a fork of Harvard. You know, these seminarians went and they kind of forked it, right? If you go and look at the kinds of folks who are leaders in tech, right, you know, obviously Gates, you know, left, Harvard, right. Steve Jobs dropped out of college, Zuckerberg left, Mark Anderson, left, Larry and Sergey, left, you know, Stanford, right. And you know, you look at the folks who are predominant and you know, Peter Thiel, he did graduate, but he abandoned the track of going and becoming a jurist, you know, at the Supreme Court. Paul Graham, Harvard grad, but he also abandoned the East Coast. If you look at the folks, and this includes, by the way, more recent things like Daphne Kohler and Andrew Ng, who left Stanford to go and do Coursera, Sebastian Theron, who left to go and do the self driving car, what you're essentially seeing is that folks who in another life would have been academics, jurists in some cases, journalists, for example, Mike Moritz famously left and journalism to go to Sequoia. More recently, a bunch of journalists have become VCs, right? So, so folks who would have been academics, who would have been jurists, like Peter Thiel, who would have been journalists, who would have been actually nowadays activists, like somebody like Moxie Marlinspike, who does signal, would very much have been like any, arguably still is. He's an activist, but he uses technology. Exactly. That's right. But he uses technology to encrypt, right? So you have something where there's definitely a common thing there, right? There's a common thing of folks who work with letters and numbers, who stare at a screen all day, who are fundamentally intellectually driven. One of the reasons that I think tech people can make a lot of money is they actually don't really care about it in the sense of, you know, if you're offered A million dollars, who cares? $10 million, who cares, right? It's only like when you start to get to like, really scientific notation numbers that you're like, okay, maybe I will take these winnings and then I'll plow that into Mars, right? Or I'll plow that into something bigger. You know, let me take a pit stop here and go for it.

Can I add something real quick to this because it's interesting, because I think this whole point is getting at why I think the New York Times has been particularly sort of a thorn in the side of a certain part of Silicon Valley is because all this can be true, right? Sort of the meritocratic part, the legacy, not really mattering, you know, new institutions versus these sort of old outmoded ones. But the New York Times has been so successful over the past seven or eight years. Not because anyone learned how to code any better, not because they added like a GitHub like function, which you sort of talked about. It's not because, you know, somehow the code is 10x better than it was 10 years ago. It's because what they said was, let's put a paywall in front of all of our stuff, AKA we're not going to distribute information freely on the Internet. We are going to lean into the fact that we're this old, 200 year, almost like legacy institution. Let's lean into the fact that we're owned by the Salzberger family. So there's this like, complicated share structure and let's charge for our content and then let's use that legacy brand to create the daily, right? So I get really annoyed when everyone sort of says, oh, look at Joe Rogan. He's totally wrecked the legacy media. It's like the other big podcast in America is the New York Times Daily Podcast. So there is this sort of legacy, there is this strength that comes from their legacy East Coastness. Now, I think the point that's fair, but I should add to this, is that it's not quite clear that that is scalable to other media brands, right? So it seems like you have the New York Times, you have the Wall Street Journal, you have the Washington Post, right? These sort of three east coast titans. But other sort of publishers who try to sort of use those legacy brand things haven't been as successful. So I think it's an interesting wrinkle to the dynamic you're talking about here.

Absolutely. These are all actually really good points. And the thing is, you know, to give the devil their due, they actually.

Have what's Your perspective on the New.

York Times, Babaji, I'm being gracious here. I try to be. No, to get, you know, to give them their due. Like, they were actually in very dire straits in, you know, the early 2010s, and people were talking about, hey, are they going to sell? Just like, you know, the gram sold the Post, I believe, to. To Bezos, actually. Were they the owners at the Times? They sold.

Yeah, that's right.

Yeah. Okay. Yeah. So around that time, you know, there's a fork in history where, you know, had Steve Jobs not died or, you know, Zuck might have bought The Times in 2011. Right. That's a, that's a branch in history which we don't know. You know, and in many ways, their turnaround at the Times, you know, a big part of it obviously is. I don't know if you've seen the graph, it almost exactly corresponds to Trump's election where their subscriber base just goes vertical like this. Right. So, you know, now there's other graphs, if you've seen Paul Graham's. Think on this, where, like the words that are appearing in the mit. Have you seen that?

Basically for listeners, Paul Graham, and correct me if this is incorrect biology, but Paul Graham points out that if you notice the New York Times tonal change in its writing, it starts becoming much more progressive, it's much more left leaning. So they're not really doing the whole sort of neutral paper record aesthetic, if that were ever sort of real or not. You could debate whether there was bias in the 50s and 60s, but at least there was an attempt. And what's interesting about Paul Graham's point is that he sort of uses the metrics to prove this, right?

Yes, that's right. And you know, that's how we like to do things, right. Is something numerical, which is indisputable, and you can at least anchor on that. You know what I mean? I'm gonna put up some graphs just to. Speaking of anchoring on numbers. All right, let me put up some graphs here just to. Okay, okay. Can you see the screen? All right.

Yes, we can.

All right, so this is a graph that shows basically this is going into 2014, by the way. Blue is newspaper print revenue. And you can see it hits its peak around the year 2000. That's kind of like flat ish for a while, basically, over the course of 2000s. And Google is growing, it's growing, but then there's a total collapse after the financial crisis. Right. And it's just like whoosh through a Floor like, I mean any industry that's dropping like 70, 80%, like this is crazy going from 60 something billion down to like 20. Right. So it's just a catastrophic collapse of newspaper revenue. And then digital isn't, you know, it's coming, but it's not giving them that much. Right. And in the meantime, boom, here comes Google and here comes Facebook. Right. And this is the kind of environment where, you know. Yeah, like if it was, if it was a dollar or two dollars, that's one thing. When you're talking about the catastrophic collapse of one industry and the meteoric growth of another, Yes, I do think the business aspects mattered. Right. So that just gives some anchoring on it. Right.

And just to give everybody an idea, just for people who are listening at home, because I want to make sure they can visualize this, we're basically looking at an upward graph of newspaper and ad, newspaper print revenue which peaks at 67 billion around the year 2000 and then has a drop which isn't that dramatic down to like the mid-50s and then at that point has a precipitous drop over the next like 20 years down to 16.4 billion. I'm thinking that's what is that, 2013. Yeah, exact same time. Right, go ahead.

Yeah. So you can Google newspaper advertising revenue adjusted for inflation, 1950 to 2014. Right. And so this is something where when economics contracts, there's just less opportunity for everybody. Right. Everybody suddenly feels like they need to, they're not as charitable. Right. They have to dunk on somebody else for likes or RTs or faves to scramble to the top of an ever narrowing pyramid and so on. And this is before digital started working. So it was a real time for them then. What was the strategy? Well, I'll show a couple of things. One is this is Paul Graham's tweet, New York Times word usage frequency 1970-2018. And without commenting on any particular word. And you can see a bunch of things start spiking and they start spiking really kind of 2013, right after that, right. Now. One way of thinking about this is just from a neutral standpoint. If you're a restaurant and you need to juice sales, well, you might start spiking sugar into more of your food that is shown to actually make people rate the food more highly and so on. Even if, yeah, it's time to start.

A restaurant right now. But if anyone's taking notes for next year, maybe you could think about it.

Well, so I believe there have been, you know, I may Be misremembering this. But I believe that there have been studies on this with, like, fruit yogurt where they found that sugaring it more and more just improved sales and customer satisfaction. But of course, that's like lacing it with an addictive drug. Right? And what happens is you have a classic externality where the population is getting fat and getting diabetes and obesity, and you're seeing that just explode in the US over the last 30 years. I don't know if you've seen. Have you guys ever seen the graph of that, by the way?

Yes, of course. Right, yeah.

Oh, you haven't seen it. Okay. The obesity GIF is worth looking at.

Okay, I've seen this one.

If you've never seen this, it was crazy. Even a few years ago. This was like seven years ago. But here. You want to do screen share again?

Yes.

You're on. It's up. I'm still doing it. Okay. Yeah. So watch the country get fatter in one animated map. And look at this. This is insane, right? Like, right.

We're watching the country basically just go orders of magnitude larger from 1988 between. What is that, 2010? And I'm sure it's only just gotten.

Worse in the last.

It's only gotten worse in the last year because we're all stuck at home. And I bet you people are not.

That's exactly right. So by analogy to this, where something that was good for a food corporation was bad for America. Right. It's quite possible that the spiking of. And this is on all sides, by the way. Certainly NYT is one here where we've got the numbers, but people spiking their social media feeds with more and more, you know, literally triggering words. Right. That, you know, if we could instrument ourselves, instrument our bodies and actually see the. The spikes. Right. Just to give you a sense of what I mean by that, to see the spikes. So glucose.

So biology searching for glucose. Blood, blood, blood in cookies.

And we're looking for there for what exactly is. Yeah, that's right.

So for those who are listening, go ahead.

Seth is going to have a fun time editing for audio.

Yeah, that's right. Well, I guess, I think in slides or whatever.

No, no, no, it's good, it's good. It's more visual.

This is actually cool, though, because we're putting this on YouTube and we're putting this on Apple Podcasts and Spotify as well, too. So I think we're sort of building different products here. I think that's a good example of how to tech show for a second we could sort of see how these different tech products can make it so that we can try things in different ways that you couldn't have done before.

Obviously, I think that's right and I think I should think about the right way of doing something that's cross platform. But let me at least describe what we're see, right? If you look at like Israel Science Info.com, i don't know the website, but I know this study. It's reproducing the study from iran Seagal & Co. Which basically shows, you know, you can give different people bananas and cookies and watch their blood glucose visibly spike and then come down over time. Okay, and the point of this is basically first, different people respond in different ways to these two things, but both of these things do spike glucose in different people. What's the point? If and when we can actually instrument your physiology, right, which I think you can actually there's folks who are measuring dopamine and so on, but if we can get even better at it, like really looking at your emotions, your fight or flight response and so on, I have a feeling that it's going to show that the combination of social media and legacy media over the last six years is just like an addictive thing, just like sugar, where we're just juicing ourselves every day with these trigger words and situations, you know, people fighting, people screaming at each other, etc. And it's addictive in a weird way, just like, just like sugar is. But it's bad for you. And only when we can actually see the metrics of that and see what that's doing to your psychology and to your biology will we realize that, oh, this was this massive externality. And by the way, I put a lot of blame on tech here as well. Please, please know that.

Well, I'm. That's actually one thing, that's one thing that I appreciate really about the problem set that you're laying out here, which is that it is not just a product of the times, right? So like there's this character like balance, New York Times, it's like. No, no, no, no. This is about something, you know, consolidation of media, the large growth of these three particular brands and it's exacerbated by some of these larger tech companies. Which kind of leads you to the macro thesis of what I think you were about to get at here. And I want to make sure we channel and make it very clear, clear for the audience is this is your thing, decentralization, not just of media but of all aspects of this, of technology and media. So can you lay that out for the audience?

Absolutely.

And one. And Balaji, one last thing to add to that, too. You referenced decentralization at the start of the episode. Can you just explain what decentralization is as like a theory, as like an actual idea before we get into the media part of it?

Absolutely. So here's one way of thinking about it. Just I'll start it from kind of political philosophy level, which is maybe congenial to your audience, and then go to a technology level. So, you know, some. Some political factions are very concerned with inequality of wealth. Right. Others are very concerned with centralized power, like abuse of power by the state. And if you actually think about it, these are not. Even though they're voiced by different groups, they're. They're not completely independent concerns. Right. Centralized power or wealth can both be abused. And the sort of faction or intellectual lineage, whatever that I come from is really the crypto community, which really stands against all concentrations of power, whether legacy or new.

And you mean crypto, and that's cryptocurrency.

Cryptocurrency.

We have ecumenical, East Coast, west coast audience here.

So we're going to. Yeah, sorry about that. Yeah, correct. So expand my acronyms, please, whenever I'm being arcane. But, yeah, absolutely. I mean, I think that I may rank order and I'll explain what I mean by this. I may rank order bitcoin over Facebook over nyt. But I'm happy to work with somebody who would rank order bitcoin over NYT over Facebook. What I mean by that is basically, and you might say those three are not comparable. What do you mean by that? Right. And one way of thinking about it is there's a good book called the Truth Machine, okay? It's actually by Paul Vigna and Michael Casey, former Wall Street Journal journalist. Actually Vigna still at the Wall Street Journal. And it gives an angle in bitcoin that I don't think most people outside the space really think about too much, which is. It is actually an algorithm and a set of data structures for achieving truth in a decentralized adversarial environment. Okay, and what do I mean, I'm using this word decentralized, but let me. Let me explain. Bitcoin is basically a database of money. And anybody around the world can read from that database, determine who has money, and anybody with a little bit of bitcoin can write to that database to transfer bitcoin to somebody else. Okay, now, the obvious thing about this is, well, why don't I just write myself a million dollars worth of bitcoin? And the whole thing has been set up with many different overlapping incentives and security mechanisms to prevent you from doing that, to make it cost billions of dollars to acquire a million dollars of bitcoin by simply writing yourself some bitcoin. Okay? The point being that whether you're American or Turkish or Japanese or Indian or Brazilian, you have the same view, the bitcoin blockchain, as everybody else. You have global truth, and not global truth about, you know, the spots of a butterfly or something that arguably isn't important. You have global truth over the most contentious thing out there, which is property, right? $100 billion is protected by an algorithm instead of data structures. And there's nothing that stops that from getting to a trillion and $10 trillion, right? There's nothing that stops that from extending, not just from BTC to protecting cash, stocks, bonds, commodities, property of all kinds. That includes, by the way, the keys to your home or to your car. Any kind of good, like your diploma or something like that, any scarce good of any kind that you can think of can be protected by basically modifications of the circle of blockchain technology. And this actually gets really fundamental. You go back to Locke and you talk about, you know, the state's justification, in part, being as a protector of property rights, right? Well, we now have a new mechanism for doing that and, you know, doing that across borders. So. So why do I bring that up? Well, everything that people are talking about today is the breakdown of truth. You know, you have all these groups, these tribes, and they don't trust each other and so on. But, you know, we're already seeing kind of the solution coming up, even if people don't really understand that it's the solution. Because the solution, in part is going to be these crypto technologies. And more specifically, let me describe kind of one vision of where I see this decentralized media future, and then I'll attack it from a different direction. One vision of this future is what I call oracles and advocates. Okay, so first, let me describe what an oracle is. You can Google the term crypto oracle or cryptocurrency Oracle or blockchain Oracle. But let me give an analogy to explain what that is. Okay, so as you're aware, many sports articles today are wrappers around box scores, right? You know, basically, it's color commentary on top of the box score. You know, many financial articles are wrappers around tickers. You know, some stock goes up, some stock goes down.

Dow Jones Goes up Dow Jones, dow futures down 600. And then some copy and pasted commentary down the bottom.

Exactly, that's right. And, and you can, you can craft a story around this. And this is a fair fraction. I mean, I'm not saying it's 50%, but it's a good chunk of financial journalism. Right. And then third, a lot of political journalism nowadays is wrappers around tweets, right? So in all three cases you have a fundamental numerical data structure, whether it's a box score or more generally a play by play. Right? The box score is just the roll up of it at the final time. But you could have, you know, play by play thing as well, right? So you have, you have a numerical data structure, a feed of events and it's timestamped and then you have a verbal layer on top of that. Right. Whether it's box scores or it's tickers or it's tweets. And in each case, what we're sort of taking for granted there is that that feed of events has not been falsified, right? You sort of take this for granted. But when you cite a tweet on twitter.com, you assume Twitter has not edited it, right? And one of the things that gives you is it tells you who said what, when and often where in terms of the, you know, if they put their location, timestamp on it, right? The context often gives you why and you know, you might even get the devices a Twitter for iPhone or Android. That's a how, right? So who, what, when, where, why and to some extent how. And that's the six questions of journalists, right? So it's like the micro, I mean, this is why journalists are in part why journalists are always on Twitter is that it used to be difficult to get people on the record and now you're just drowning in quotations from everybody. Everybody's trying to be as witty as possible and you know, you can just go through all this to get a picture of somebody's head. It's actually amazing from that standpoint. But it's also open sourced a huge amount of what used to be very difficult to get right. I mean, I can kind of interview Elon by reading a thousand of his tweets and actually get a decent sense of what's in this person's head, right? You sort of open source something that used to be actually very difficult. Most people could not get access to this person to even hear their thoughts, you know, even, even 20, 30 years ago. Right. So what if we extend this right so it's not just feeds of sports scores and ticker symbols and tweets, but you have feeds of everything. Okay? You have feeds of coronavirus deaths, you have feeds of weather statistics. Right? You have feeds of real estate trades. You know, and actually all of these already exist, right? You know, you've seen these numbers. You know, whether it's Covid tracking for the COVID stuff, right, Or Zillow for the real estate stuff, all these feeds exist. They're just siloed right now. Okay, here's the novel thing, which you may not have heard of. Crypto people are working on taking every single one of those kinds of feeds and one by one putting them onto a blockchain, which will timestamp them and make it very difficult to change them. Right? Now, what that means is, you know, you'll say this entity, on June 22, 2020, said that there were a thousand coronavirus deaths in this country. It doesn't say that that was true. What it does say is very, in a very hard to falsify way that this entity said this at this time. Okay, it's kind of like, you know, anybody can tweet anything. You can't necessarily say whether it's true, but you can say that this person.

Was tweeted at this time with this context, et cetera, from this location, right?

That's right. So at least you can come to truth claims on the metadata. Right? Which is something, right, that's actually agreeing. In an adversarial environment, the numbers allow us to agree. We may not think what they said is true or false, but at least they said it at that time. And this person. And this was, you know, like perhaps where they said it. We trust Twitter to give us the correct location. Right? Okay, so you generalize this to thousands and tens of thousands of feeds. And why? Because on each of these feeds, people are setting up prediction markets. Okay, so I've RT'd something on this. You can look at something called Kleros K L E R O S. That is a decentralized court. And again, I'm going to come back and just define this term decentralized in a bit. But I'm just. Let me. Let me give it us exactly. I'll do it by usage first and then. Okay, so Klaros is really cool. I have no stake in it or anything like that. I just RT'd some stuff on it. So what it is, is essentially something where folks are betting in these prediction markets and one person bet, like there's going to be more than a thousand coronavirus deaths in this country. Their person bet less and they're betting pseudonymously, so, you know, nobody can attack their character for, you know, oh my God, you're betting on something so morbid or so on. The premise, at least from a moral standpoint, is you're getting better information out of this. Right. In the sense of, you know, like if you could predict the number of deaths, you might be able to plan around that. And if this showed a track record of predicting better than that would actually be useful, even if it seems gauche to bet on something like that. Right. So I personally am not betting on those things, but I understand the motivation to bet on that. Okay. Just to. Just to. Just to put a. In case your viewers claim are out there. Exactly.

That's right.

That's right. Okay. Point basically is that some outlets reported fewer than a thousand deaths and some reported more. So there was a dispute. And that dispute is being actually resolved by a decentralized court where both sides are making their case as to which outlets should be trusted. Okay. And you now have a meta layer of education over the raw facts that are going into news reports and so on around the world. Right. And what is incentivizing that education and that micro scrutiny of individual numbers, which are really important, by the way. Right. Those numbers often just go without dispute into all kinds of things. And people go back and find out, oh, there's a bug or an error here, you know, whenever you've diligence to anything, you've probably found something like that. Right, Right. So now we actually have a market mechanism to diligence raw numbers of all these different feeds in the world because basically people are doing a Kentucky Derby like betting ring on them. Right. And now what this does, by the way, if you've ever heard of the concept of futarchy, right? And like prediction markets for predicting the future, this actually turns it on its head where you may or may not get signal out of the prediction markets, but where you do get signal is from the raw facts and the feedback. Right. Even if the prediction markets themselves are not that great in terms of forecasting the future, the debates and the fights over them are actually useful for adjudicating what was true at that time, for basically getting these cryptographic feeds. Even if prediction markets themselves are break even, these feeds are extraordinarily valuable in their own right because they give you digital history.

Let me jump in there just a bit because this presumes, I think, that the central problem in our media, in our. The new York Times. And all this is objective truth, Right. Like objectively verifiable deaths. And there's massive benefit. Absolutely. To having a market mechanism which can determine the objective number of people that have now died from COVID 19. But the issue that I think that you have, I have, Marshall has, and with much of our media coverage today is more about subjective matters, right? So it's about the framing of a headline about Uber versus the framing of a headline about, let's say, a different company, about Johnson and John, which is not a tech company, about the way that we cover something. And I want to, you know, bring in. Let's bring in Noam Chomsky, who I think is one of the most apt observers on the media. We wrote this, you know, so many decades ago. He basically.

Consent, right?

Manufacturing consent. So to just summarize the quote, essentially what he said was what they choose not to show you is actually more important than what they choose to show you. Now, I don't know how a blockchain mechanisms could basically correct for a subjective bias in the way that we cover. So how is that factoring into your. Go ahead.

And I just want to. I want to build on that real quick. Biology, because I think these are. I think this stuff is really interesting. I think it's key to sort of define the problem, right? So like if we. Let's pretend that, you know, we're launching a startup here and we're trying to, like, identify a problem that we're trying to solve in media. You said earlier that the problem in me that there's a problem with truth in media. I think that I sort of disagree with that in the sense that I don't think the media lies too much about objective things very often. And oftentimes if there is an incorrect fact that's verifiable, it's quickly corrected. Now, there are narratives that are complicated, right? So like you yourself have seen the issue of people saying it's just the flu and then like, they don't correct the record afterwards. But I put that in the category so of subjective truth. But for example, if I were to write in. Let's say Sager and I launched the realignment publication, if we were to write one day, 10 people in D.C. died of coronavirus. But it turns out after the fact, it's revealed that it was 20 people. We'll go back and fix that. And that's always sort of dealt with the bigger issue, though. What I sort of see in media is that people don't trust the realignment publication at all.

Right?

Like, the issue in media is that you don't trust Recode. It's not that you don't think that Recode is literally lying about coronavirus death numbers. It's just that you think that Recode and Kara Swisher and the broader sort of vox set of people are dishonest and aggressive and hate tech.

That means something.

That Blockchain is going to.

Well, let me. Oh, there's. That's a big organization, but go ahead.

The idea of Recode, I'll give you. I'm not alluding that.

Like the broader things there, which here is like COVID deaths. Right.

Okay, I got to respond because I've got a bunch of things on the stack from what you guys said. Okay, I'm saving mine.

I'm saving mine.

Person, man, woman, car, tv. Okay, just. Got it. All right, so, okay, so basically, let me respond first to Sagar's and then to Marshalls. Okay? So who cares about facts, right? Raw facts. Well, first, the New York Times markets itself as the Truth Capital T. That is their marketing campaign. Right? This is also why they're disincentivized to run corrections, because every correction is kind of backing down. Right. The same pathology, by the way. It's not unique to them. It's also found in academia, where a retraction or a correction is a black mark on your cv. This is very distinct from, for example, in the open source community, where if you have public issues, then that's a sign of a healthy project. Like edits and so on.

Are Wikipedia and those sort of places.

Yeah, exactly. Like a heavily edited thing is often a signal of a project's health, not its frailty. Right. It shows it can accommodate error, it can update and so on and so forth. Right? So number one is they definitely do market themselves as the Capital T Truth. And indeed, a significant part of their influence comes from people looking at them as, quote, the highest source of truth. Just a recent example is this whole UFO thing, right? You know, even folks who I. Who I like were like, well, maybe it's now true because the New York Times said it. And I was like, you know, there's. There's been a lot of Gel man amnesia. Have you heard that term?

No, go ahead.

Oh, you haven't? Okay. That's. That's term you should. I'm gonna. I'm quote it to you. Okay. This has never been on your show. Gel Man Amnesia by Michael Crichton. Right. Who's now, you know, the late Michael Crichton, famous author. Right.

Jurassic Park.

Yeah. So briefly stated, the gel man amnesia effect is as follows. You open the newspaper to an article on some subject, you know. Well, in Marijell Mann's case, physics. Marijuana is a Nobel laureate in physics in mine, meaning Michael Crichton's show business, you read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often the article is so wrong it actually presents the story backward, reversing cause and effect. I call these the wet street. Wet streets cause rain stories, papers full of them. In any case, you read with exasperation or amusement the multiple errors in a story and then turn the page, national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page and forget what you know. So now the critical thing is here, that opening sentence. You open the newspaper to an article on some subject, you know. Well, okay, so he's not just trashing, you know, journalists for the sake of trashing. He's saying that he has disciplinary expertise in a matter of and is able to independently diligence and reproduce the claims in the article and finds them wanting, whether by omission of facts or making incorrect deductions or whatever. Right. That is a very specific kind of critique. And it's not like what I consider it dumb to be like, oh, it's all fake news or whatever. It's different when you say a disciplinary expert in this area would find these errors in the writing. Right? Yes. Now, the thing about the Internet is you can summon the gel mons of every discipline in theory. Right. That's like a new thing, you know. No, no writer, no generalist writer can ever know more than, you know, a thousand specialists in bioinformatics on Covid or a thousand specialists in physics on physics. Right. It's just not possible. And it's no, you know, insult to that writer. What's my point? The point is that it's not just a binary of, oh, everything that appears is true or they're intentionally lying to us. There's huge swaths of things where they don't know or they tried and they got it wrong, or there was sort of like a tribal thing to show, shade the facts and like omit some versus other. There's a whole spectrum of things in the middle there. Right. And you know, I. I'm not, you know, like, you can kind of go first order, second order, third order on this stuff. Like first order, sort of like naive, oh, the truth matters. Right. Second order is where I think a lot of people are today, which is truth doesn't matter, it's all tribal and so on. Third order is the truth matters for serious decision makers. Okay. If you're allocating resources, if you are. For example, I'll give you a classic example from earlier this year. Corona. One really important thing, and I didn't mention this earlier, but I should. One really important thing that shapes how tech people read the pressure is we are all used to examples where the news report wasn't like 50% off or something, but it was a thousand X off. Okay? For example, Bitcoin's going to die. No, Bitcoin goes to 10,000. Coronavirus is contained. No, actually it goes to millions of people. Here's a few other headlines I just pulled up here. 2002 NYT, Google's toughest search is for a business model. 2013 Quartz why Facebook will never make a significant profit. 27 June 2000, Amazon. How the Internet's Biggest Success Story Turns sour. Right. In each of these cases, you're not talking about like 50% off. You're talking about like a. I mean, they researched it, they wrote whatever they wrote, but they were a thousand x off from what actually happened. And you couldn't just read their stuff and discount it because, you know, again, first order is you just read it and believe it. Second order is I'm going to read this, I'm going to take it with a grain of salt because I know where they're coming from. Third order is you're like, they know nothing. I know nothing until I have diligence and reproduce this for myself. Right? That's the attitude of a scientist towards a scientific paper. You know, interestingly, we're actually more skeptical of a lot of the scientific reporting on Corona because we kind of know, see, scientists are flawed in many ways. Don't get me wrong. Right, but. But scientists do include references for every single thing they're saying. They at least make a nod towards empirical reproducibility. It's not considered like some insult to try to go to reproduce their. Their work usually. Okay, I'm not saying, oh, some of them do get insulted by it, but they try to, you know, give raw data. And fundamentally, the most important thing is that the judge of whether something scientific is true is not really peer review. It's independent replication. Right? And so that's kind of. This is where I say like, third order. Right? Third order is the truth really does matter to serious decision makers. Coming back to the February thing, the reason Corona was important is hundreds and hundreds of companies that I knew about had to figure out whether they were going to remote work or not. Right. Like, literally billions of dollars of capital had to be allocated based on, you know, was this thing real or not? Right. Not to mention, obviously, like, all the health decisions that need to be made, you know, because you're making decisions, it's not just money, obviously. It is. It's the health and livelihoods of your employees and so on. Right, right. The reason I say that as a, as a second thing is usually most of these informational errors in the press just cost you money. This one could actually have cost you your life, which put it up to another level. And yet we haven't seen corrections or retractions. It's just kind of breezed on by.

Quick thing, though, because I do feel we need to advocate for our colleagues in the press. I think if we, if we're looking, because we're all citizen journalists, so technically.

Sure, sure, sure, sure.

We're all colleagues here.

Right.

Galaxy Brain. So I think in most of the examples you cited, though, those are opinion analysis pieces, right. So, for example, the 2000Amazon bomb one you're referencing, right. That's in the middle of the dot com crash. That's an analyst whose job it is to make predictions. But that's still not like factual, basic things, Right. Like if you're looking at the Facebook article in 2013, that's a case where a analyst was offering an opinion column that's like laced, but that's not like reporting. So, for example, let's talk about another company that's been in a lot of trouble lately, Quibi. So Quibi, for example, is a company. It raised billions of dollars of funding. It's gotten all these sort of really negative press pieces about it. But those press pieces aren't making a claim of truth, they're just making a claim of analysis. So, for example, there was that big New York Times Quibi piece that came out in May where it had Jeffrey Katzenberg saying, quote, in the interview, I think everything that's gone wrong of Quibi was because of the coronavirus.

I saw that.

Everyone saw that.

Right. Because.

But the point there is that it could turn out that everything with Quibi will turn around. And actually, for realignment listeners, we're actually going to cover Quibi a little later next month. So quick note for that, but maybe if everything turns around with Quibi in, let's say, December 2021, because they still have $700 million in the bank that doesn't make that New York Time piece predicting query was going to do poorly. Inaccurate. So how does that fit into your framework here? I think you have something to add.

Yeah, well, let me just respond to that quickly before. So the thing is that this stuff is. It's presented in the passive voice, right? It's often presented as a way to drive a conclusion as opposed to merely being neutral reporting, Right. In many ways, you know, when you talk about impact journalism, the point is actually cause a change in the world, not merely to report it, right? Not merely to be a, quote, a stenographer, but even though you're reporting passively, you inject adjectives, you pepper it, you flavor it, such that it's kind of like what I call the disassembled bomb theory of journalism, right? Where you give a disassembled bomb to the reader and you have just enough distance where you know exactly the reaction it's going to evoke in the reader's head. They're going to put the bomb together and be like, ah, I hate that guy, go get him. Right? But you kind of maintain some degree of passive distancing or whatever, right? And I think, you know, that's one aspect where many of these articles were written by people who wanted these companies to fail. They weren't just, you know, like neutral observers or whatever. They're trying to drive an outcome. But even, let's say that some of that was just, you know, commentary. And yeah, you can get it wrong. Get it right. Here's the thing, like, only some, you know, like crazy guy who goes and does the research eight years later or seven years later and is like, ah, see, they were wrong. And that's their accountability mechanism. It's only us blowing them up. Yeah, exactly. It's only some lunatic, you know, like me, whatever, right? Who would do that. Because VCs are kept accountable, you know, angel investor, you're kept accountable by your portfolio. The problem here is you get the clicks today and the reputational cost seven years later. Who remembers that you said Facebook would never make a profit? Right? Sure. Facebook took the damage, then you got the clicks then. But there's no. Nothing catches up with you, Right? So that's a real. That's another externality. It's like, you know, like putting the dopamine, you know, juicing things into the, into the feed. It is something where, especially if you're marketing yourself as the truth, you know, like, again, it's a totally different thing if it's like, oh, this is just a comment by some person. Right. When you're like the truth, you need to actually hold oneself accountable. Right. Okay, go ahead. Saga, you're going to say.

Well, so I think that's. I think that's a very important point. But kind of what I was getting at earlier about omission was about, let's take the perfect example of the riots or the protests and all that, plus coronavirus. You basically had public health experts and the papers and many others just completely obfuscate that there could have been any relationship whatsoever between that and a spike in coronavirus deaths. In what way would. And decentralization made it so that, yeah, even on Twitter, all of that, you know, we can all go out and tweet and be like, this is ridiculous. Hypocrisy, et cetera. But that doesn't mean that we can force the organs with mass influence in this country, cnn, New York Times, msnbc, to acknowledge that. Right. So if we can't get these people to acknowledge or to even report verifiable facts and then, even then to bring on something somebody like an expert who's willing to say that again, it's a sin of omission and of framing rather than a sin of not reporting the increase. So, like, right now they're like, oh, coronavirus deaths are out of control and X, Y and Z. And it's all because of governors reopening. And I think that there's a lot to be said about that, but I haven't seen even the same amount of accountability as you're saying, for the, you know, for the protest movement and much of that. So how does that fit into a verifiable blockchain framework?

So I'm going to come to that. But one thing I want to do is, you know, I want to praise there definitely there were. You're absolutely right. I think generally there were some folks, you know, Connor at the Atlantic, Alexis and the Atlantic, Dan diamond at Politico, they did point out that of course you need masks, of course you need all this other stuff, but you also need to avoid large gatherings and, you know, coronavirus doesn't care how, you know, righteous. Your cause is it will spread there, right? And, you know, like clockwork, like, you know, the spike happened basically like about three weeks later. And so it's this. It's this thing where there were some folks who were smart and courageous and they put out the right content. The problem is that that message isn't getting amplified. The incentive structure isn't there. Society's signal amplification mechanism is broken in tech, basically, if you make a right bet that is against the grain, but it's really right, you're rewarded 1000x, right?

That's the theory of venture capital.

That's the theory and all those things. I mean, look, it doesn't always work. I mean, I get.

But that' the point of. That's the business bet, right?

That's the idea.

It's funny though, because in media, just quickly, it's like if you make the wrong call on the Iraq war, or you make the wrong call on many of these other things in dc, you get rewarded for it. These people are now MSNBC contributors. These people are now people who are very famous. And if you were a dissenting voice, by and large, you're not more famous as a result. So clearly that system is broken.

That's exactly right.

And I think.

And just, just to build on that, because I see Biojee of a couple, I think Sagar, I think that's like so interesting. But by the way, though, and this is where we get into sort of like making decentralized media more real for people. There actually is a system that's emerging which can reward people for being right. So let's think of like Matt Taibbi, right? So like Matt Taibbi is someone who is very aggressive on pushing back against the worst excesses of like Rachel Maddow, Russiagate crap. Just like the worst msnbc, clickbait, cable news, really bad faith, like just stuff that's totally incorrect. You know, in the past it would have been unclear, but he could sort of be rewarded for that. But now, because of a substack, what he can do is he can leave the Rolling Stone. I know he still does his podcast at Rolling Stone, but he gets create a substack and charge money that's very, very marketed towards. Hey, I'm this left guy who tells it like it is, who's going to sort of be rewarded for that. So that's something that if, you know, if you were someone on the left or the right who critiqued sort of the rush to the Iraq war in 2003, there is no way that you could be financially, you could do a blog. But like, that wasn't monetizable to the same degree. So I think that's a good example. We're seeing this with Andrew Sullivan, Mikey, Asha Munk. There's this whole cohort of substack people who in previous eras would have been stuck in these big centralized institutions. But this goes to your point about the decentralized model they can now do that. So I know that's something you're very supportive of.

Absolutely. I mean actually, so it's funny, decentralized media is a term that you can slice from about 15 different directions. And I may include like, like a bunch of mini essays on this because it's actually, it's kind of a rich conc. But one of them is exactly what you're talking about where you, you basically, you take apart a media corporation and you have the top folks there once they are all individual personal media corporations. Right. Their own voice. You know, it's basically that's a fusion of the concept of media corporation and the concept of an influencer. Right. The personal media corporation substack is like v1 of that. Then we're going to start getting dynamic newspapers, you know, like basically like combinations of these individuals, you know, pulled together. I think subsequent quick pushback.

Right. Like.

Yes.

Isn't a dynamic newspaper just centralization again?

Right.

This is why this stuff is so interesting to me because you know, if you've read your Tim Wu, which I think you have to a certain degree, you know, his basic thesis on any sort of dispersion of information is we go through these cycles, right? So you have a cable bundle and that turns into a bunch of streaming services and then they come back together again. If all these little substacks start bundling together again, which is starting to happen, how is it not any different than the previously centralized media with just a little more writer control? I'm curious, we can talk about that dynamic.

Yeah. So what I think is I've got two ways of talking about that. You know, I don't know if you're the saying by. I think it's either Jim Barksdale or Jim Clark. But only two ways to make money in business are unbundling and bundling, right? Yes. But there's another way of thinking about it which is all progress happens along the Z axis. Okay, so for example, at, let's say 12:01. Imagine a clock, right? At 12:01 somebody is frustrated with some existing megacorp, they leave, they strike out on their own, they start getting some traction if they're fortunate and hard working. And then by 3 o' clock they actually start to get some employees and so on. By six o' clock they're in their spring, they're rising, they're the next big thing. By around this time there's a crucial change that has happened where they switch from the burn rate to the bus number becoming the most important thing, that is to say early in the life of the company, every single person must be incredibly iconic. They have to pull their own weight. They have to be totally unique because you have to minimize your burn. You need these exceptional, exceptional people. At a certain point, maybe when the clock ticks over past six, the bus number becomes more important, which is you now have a multicellular organism. And if any one person is not replaceable, you haven't done your job as CEO. That's a huge shift where you go from recruiting a team of totally irreplaceable people to once you have a stable business model that's really throwing out the cash, you have to switch it to a bus number model. Because now if you have 200 people and any one of them leaving will kill the company, you're actually not doing your job. So you have to move to kind of a bureaucratization, an impersonalization of the company where you put more into processes, more into code. You start taking away individual initiative to make the organism more robust. This transition is not one that most people see unless they've actually been a manager that's gone through this cycle. What that results in is that by around 9pm you have an organization that started to get bureaucratic, it started to become deadening of human initiative. And then by about 12 o' clock, someone leaves and goes and does their new thing. Now that's like an interesting cycle of life sort of thing. And you might say, well, did we land up where we came? But I think one way of thinking about that is you have Fairchild Semiconductor and then you have the trader state. Actually, maybe I'm getting that wrong historically, but did Fairchild proceed? You had a semiconductor company and then you had the trader state come out of that, and then you had more companies come out of that and so on. So it's like a corkscrew turning up, right? Even though it didn't happen quite this way. It wasn't like the founders of one company came from the next. But you did have, for example, the founder of Salesforce came out of Oracle, right? And then founders of other companies have come out of Salesforce and you have this corkscrew where it's like IBM and then Microsoft, right? And Apple, and then you have Google and then you have Facebook and then you have, I think, crypto, which is actually what's coming after Facebook. You know, most people don't really, don't really see that yet, but each turn you're actually progressing, even if it seems like you've come back in the same spot. So that's my, that's my answer to you, Marshall, is, you know, you do actually overall make progress, even if it seems like a loop.

So I just went before Babaji. We asked people for sort of questions they wanted to ask you before we did this. Everyone wants your thoughts on geopolitics in India before we transition there. I just want to do my last word on this topic. I want to make a prediction that hopefully in five years we can debate on post blockchain. What I think is going to happen with all these newsletters or individual writers are. They're going to go out on their own. People are going to discover pretty quickly. But it's actually super hard to build a business by oneself because, you know, decentralization has certain advantages, but centralization has certain other advantages, right? Sort of the editor, the marketing people. Sagra and I love this quote where a newsletter writer, Jacob Donnelly, pointed out that when he created his newsletter, which is very excellent, by the way, three fourths of the work he does is actually marketing. It's not even the writing part. So there's going to be people who are going to come in and say, hey, like, guess what, Jacob, we'll handle your marketing. You just write all day. So what I think is going to happen is the New York Times, as they've already been doing in other verticals. So for example, they just bought Serial this week. Who created cereal, they're buying other things. I think they are going to start acquiring newsletters. So that's how the recentralization process is going to go. They're going to offer people much more sort of editorial control. But I really just think that that's how this sort of cycle is going to sort of go, which is that we're going to see all these decentralized things get picked back up into sort of centralized places, and that's how that cycle is going to sort of go.

Perhaps. I think it's quite possible that they'll acquire newsletters and so on. You know, they acquired this podcast. However, I do think there's something really important here, which is if you're a writer at a publication and you're part of the mainstream and your primary currency is your reputation among your peers, right Then there's a very strong pressure to hew to the orthodoxy because you might lose your job, you might lose your opportunities for promotion and so on and so forth. In fact, the incentive is not to stick out too much and just to laugh at the same jokes and perform the same ironic detachment that Freddie DeBoer had in his awesome essay that he took off his website. Did you guys see that?

No, I didn't.

Okay. It was actually really funny. Basically, I'll quote it to you. I'll find it while we're talking. But he actually took it down. But it's. It's still there. If you. It's about like the immune immovable object versus the ironized thing. Basically points out that most folks in media just make ironic jokes all day and all night and to each other, and they're just performing for their peers and they don't actually believe in anything anymore. Whereas he's like, you know, tech people. Right. Okay. He's like, that's what you just described.

Blue check Twitter in D.C. and New York.

I was like, it's all. Literally all in group signaling. That's. It's all about in group signal.

It's all in group signaling. Right. Whereas. And he correctly observes, and I give him credit for observing this, even if he's like, you know, by his own. By his own nostrums, he says he's. He says he's a communist or whatever. Right. By his own declarations. Right. So, you know, he. Even though he says that he is at least perceptive enough to know that nostrum's not the right word. Put her. He's perceptive enough to know that Silicon Valley believes in something. He says it might be California ideology plus the blockchain, but they believe in something, and that actually gives them strength. And that's true. But coming back to this thing about the orthodoxy aspect, essentially, when you have folks who can't step out of line, they. They can't step out of line, not just on Twitter. They can't step out a line in their writing. They all have to echo the same thing. And it's all just a hundred rehashes of basically the same narrative. The big advantage of Substack, and then really, you want to get your own domain and have your own newsletter at your own domain, because Substack is great, but it's an intermediate step towards that. The big advantage of that is nobody can censor you. And in fact, and this is critical, you have to acquire subscribers from everybody else. So you must stand out. That is completely new. Right. That's an incentive for uniqueness in writing, you know, and what I think will happen is, yeah, some of these things, because, you know, there has been essentially a monopoly in the community. One way of putting it is even though there's like, you know, different media outlets, there's Vox and Recode. Recode is part of Vox, but Vice and buzzfeed and whatever. Right. Nyt. That is one community. Right. Folks go and work at each other's companies.

Williamsburg, Brooklyn, specifically.

Exactly. It's headquartered in Brooklyn. Right. In the same way that tech, which, quick note, soccer.

Lived in Brooklyn. So we need to be very honest about our own biases.

I was originally, I came from New York, so I do know something of the culture. Right? So tech is also like that, where you've got a 16Z and you've got, you know, like Google and you've got, you know, these different companies and there's. There's a. There's a flow of people between them. You usually know somebody who knows somebody who's at one of these companies. It is a community, just like media is a community. And they're increasingly disjoint. Right. In some ways because, you know, they're not just separated coastally, but mostly culturally. And of course, it's not entirely geographical, but maybe it's. That's just. That's just a good mental way of thinking about it. It. What's my point. Point is the whole advent of, you know, the combination of pressures that are getting someone like Barry Weiss and so on to exit and the advent of being able to just set up your own shingle with a few clicks at something like substack and actually monetize your audience online. Because audiences have grown like, you know, probably 10x at least, but maybe 50x depending on when you count from the age of blogs. Right. And more people are used to buying stuff online and so on. Now you can have media content that does not agree with Brooklyn anymore. That's a critical thing where there's a lot of niches that are simply not served due to this sort of monopoly community. And that's a critical thing. It's a monopoly community. It's not one company. It is a community. And that's why you need to decentralize. That's why you don't need a new media company. That's the thing is that's not the way to solve this. You need a new media community of lots of writers online who have their own shingle. And crucially, some of them should be pseudonymous. Pseudonymity is another critical part of decentralized media. Because, you know, Satoshi writing nine pages changed the world. You know, literally nine pages. Yeah, Bitcoin, right? Satoshi Nakamoto writing nine pages. I mean, of course, it wasn't just that he also wrote a lot of code. You couldn't have done it without the code. Right. But that's the power of pseudonymous writing. Pseudonymous writing created the Republic. You know, that's the Federalist Papers. And I think we're going to go back to the future on that, where pseudonymous writers monetizing under their own names or their own pseudonyms on their own domains, potentially earning crypto. That's a very powerful force. And you can now build small organizations around it, maybe even medium sized organizations, which are making not just print but, you know, podcasts or video images, what have you. Right. And a lot of the AI stuff is actually going to.