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Chapter 1: What are the cultural implications of AI in today's society?
People are becoming what we now refer to as AI vampires. They've got these huge bags under their eyes. They're completely exhausted, but they're like euphoric. There's Ralph. We're entering the golden age, which is AI is going to be a superpower that everybody in the planet is going to have access to. It's like the most dramatic increase in programmer productivity ever. Twitter proved it, right?
Cutting 70% and then it's running better or as good as it was before. I generally don't wish I could go back in time and do things over again, but it would be really, really fun right now to be 18 or 20 or 22 and to have this capability and figure out what I could do with it. We are going to see super producers the likes of which we've never seen in the world. There's news about it. UFOs.
What is clear is the government at certain times has hid certain materials. Why would they do that if there's nothing to really worry about? Two things are pretty clear at this point. One is that... AI is moving from novelty to infrastructure, but the conversation around it is still dominated by extremes. Fear on one side, hype on the other.
Meanwhile, the reality is playing out more quietly in how people work, what they build, and how organizations adapt.
Chapter 2: How is AI transforming job roles and productivity?
Productivity is increasing, roles are shifting, and entirely new ways of building are emerging. At the same time, the systems around information, media, and authority are being reshaped in ways that are harder to see, but just as important. The question is not just what AI can do, but how it changes the structure of work, institutions, and culture.
Here, Marc Andreessen joins me to talk through what's actually happening. Mark, welcome to Monitoring the Situation. Eric, it is great to be back. So there's a lot to monitor today. I want to first start with something that just happened, which is the anthropic blackmailing incident.
And I first want to tell a brief story, which is my friend Joe Hudson has this concept called the Golden Algorithm, And the gold algorithm states that whatever you're scared about, you bring it about in exactly the way you're scared about it. So if you're scared about getting abandoned, you'll be super insecure. And then people will abandon you because you're so insecure.
This is an example of a literal gold algorithm where people have been so scared that AI is going to be evil and have written about all the ways in which it's evil. And in fact, maybe it's informed something. What's happening there? Or what do we find interesting? I haven't studied this one in detail. I've been monitoring other situations.
But, however, just what I saw so far, I think I just saw Anthropic's thread. I haven't read the underlying material yet. But Anthropic's thread said they trace some black male behavior literally to the AI doomer literature. Yeah. Yeah. that was in the training data.
So there are all these, there are all these, there are all these, you know, scenarios of like, you know, the terminate, you know, the rogue AI gone wrong that the AI Doomer's been writing about for 20 years. And literally Anthropic, of course, which is, of course, the company is like, you know, half Doomer.
And really, you know, basically, you know, essentially said that their own, their own, their own movements literature is the thing that's causing the behavior that they say they, they, they don't want. So it is a fairly incredible, Yes, yes, it is, yes. Oh, I mean, like, look, if you don't want to build the killer AI, you know, step one would be don't build the AI. It's like, hmm.
And then, you know, step two is, like, don't train it on all the data that says it's supposed to, you know, the literature that you movement wrote that says it's supposed to be a killer AI. So, you know, yeah. I don't know. Yeah, it's like your golden algorithm coupled with, like, the snake eating his tail coupled with, you know, I don't even know. Like, the whole thing is so bananas.
Yeah.
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Chapter 3: What shifts are happening in the media landscape due to AI?
I don't exactly know how to pronounce that, Gad Saad. And, you know, very brilliant guy. And there's obviously lots of YouTube videos and books and so forth. And really brilliant guy. So he's got this new book coming out on so-called, what do you call it, suicidal empathy. And, you know, there's a sort of political loading to it, which, you know, we don't need to spend a lot of time on.
But, you know, it's sort of this idea that there are kind of these social justice, you know, kind of social reform movements. you know, kind of through time that have this characteristic of, you know, they claim to be causing positive change, you know, in some direction. And then it turns out they have, you know, sort of severe, you know, sort of negative consequences.
Chapter 4: How is trust in institutions changing with AI advancements?
The great Thomas Sowell, you know, basically spent 50 years writing books about this. And by the way, nobody listened. And then in the last decade, we've been through, you know, wave after wave of this kind of social activism that kind of, you know, results in... I mean, it's all this stuff, right? It's just, you know...
All these like, you know, crime policy reform, defund the police things, and then it causes these massive crime waves. And then, of course, low income and minority people get hit hardest by that. And, you know, all these other crazy things. And so he says, you know, he says the characteristic of kind of that kind of social reform movement is characterized by what he calls suicidal empathy.
And the idea being basically it's sort of driven by a pathological, you know, take it backwards, a pathological form of empathy on the one hand, which is, you know, it's sort of a deep desire to be nice and empathetic, you know, but coupled with like basically, you know, a sort of self-destructiveness, you know, either a willingness to really cause damage to the people you claim to be speaking for or by the way to cause damage to yourself.
Kind of in that process. And it's the kind of thing where, you know, if you've lived through, you know, like everybody in San Francisco has lived through this for the last decade and seen the consequences of these movements.
You know, the San Francisco version of this is like the, quote, harm reduction movement, you know, that ended up basically handing out, you know, free drug, you know, paraphernalia and, you know, in some cases actually just free drugs to, you know, people who were just literally dying in the street from drug addiction.
So you just look at it and you're like, well, yeah, they claim to be activists, they claim to be reformers, they claim to care about these people, and yet they're killing them and then killing the city and causing innocent people to get harmed. It's like, okay, they seem so actively like they're doing it out of some sense of compassion that this must be suicidal empathy.
The problem with it is, and I think the problem is the theory is sort of easily falsifiable or maybe lets the reformers off the hook, which is, they certainly don't show empathy to their enemies.
And so if they're like all empathetic, you would think that they would be less aggro when it comes to destroying their ideological opponents, who they take great delight in trying to wreck, number one, on the one hand. And then number two is they use the classic reformer move is to use these movements to gain power and status and money for themselves.
And again, San Francisco is a case study of this where you have all these nonprofits that recall this damage on the city and yet basically get like lavishly funded, including, by the way, by the city government, by the state government.
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Chapter 5: What does 'AI-native' culture mean for future builders?
In my view, that includes, you know, very deeply un-American and I think in many cases unconstitutional removal of free speech rights and also literally the ability to bank.
And in fact, you know, our partner Ben's father himself was specifically tagged and attacked by the SPLC for unfairly, very unfairly, for being racist and was himself debanked and, you know, really directly threatened his livelihood in a really, you know, egregious way. And then, by the way, the significance of this is, of course, it's not literally the U.S. Department of Racism.
It's actually arguably worse than that. It's not a government agency. And so it's not subject to, like, any level of government oversight. It's not, you know, it's a completely, you know, as I say, it's an NGO, right? And so it lives in this, like, twilight world. You know, it doesn't have the, you know, business responsibilities of a company.
It doesn't have any of the legal oversight, you know, that a government agency has. It lives in this kind of twilight world where it gets to do, you know, fundamentally gets to do whatever it wants. Um, and then by the way, on top of that, you know, it raises, raises money as a nonprofit. Um, so, you know, on top of that, everybody gets a tax break.
And so it's this, it's this, you know, kind of shadowy thing. Like if you didn't agree with his politics, you were just like, wow, like that, this is like a weird star chamber, like shadowy thing. Like what the hell? But, like, it had, like, really, really, really, really intense power, particularly in the business world, particularly in the financial sector, particularly in Silicon Valley.
Like, it was like a Death Star to be able to aim at obliterating people's reputations and rights. And so, you know, this was a really big deal. By the way, many of the big corporations and including big tech companies funded it directly. And so the money trail on this is not just major philanthropists and political activists, but also actual, you know, actual companies.
And then, by the way, they also had, you know, a long history of actually cooperation with certain government agencies, including, I think, for a long time, they quote-unquote trained FBI agents on basically, you know, essentially catching, you know, racist and therefore, you know, sort of presumptive domestic terrorists or something. And so just like a very powerful outfit.
And then, you know, this thing that dropped is that they've been now criminally indicted by the U.S. Justice Department. And I should say that the indictment reads like a novel. Now, it's an indictment that SPLC, in fairness, has not had a chance to present to defense. And so, you know, presumably in court, we'll get both sides of this, which I'm sure will be an absolutely spellbinding experience.
So, you know, of course, I want to say, you know, all of the things that are in the indictment are allegations and innocent until proven guilty and, you know, so forth. You know, however, the allegations are eye-watering, right? And the allegations are that the SPLC, using donor funds, was directly funding, among other organizations, the Ku Klux Klan and the American Nazi Party. Right.
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Chapter 6: How are young graduates preparing for careers in an AI-driven world?
At our leading-edge companies, estimates are the leading-edge programmers are like 20x more productive than they were a year ago. It's like the most dramatic increase in programmer productivity ever. And so, again, logically, people get paid according to their marginal productivity, and you're also seeing that track in the compensation data.
I'm seeing that on the ground in the companies, which is the more hyper-productive a coder becomes, all of a sudden, the more bargaining power that they have for their compensation. We're seeing a comp for those people ramp up quickly. And so it's just kind of staring us in the face. And coding, of course, coding is like the first domain in which this has happened.
Now people want to project forward and say this is going to happen in every area of knowledge work. And then I think you can predict a similar outcome. And then that gets us to the bloat topic, which is, of course, the other thing that's happening is, of course, companies announcing big layoffs. And then, you know, of course, immediately it's like, you know, two plus two must equal four.
And so if it's AI coding, it must therefore translate into layoffs. And, you know, Mark, you're wrong. You know, therefore, all of your ideas are wrong because that's evidence that, you know, these companies are wiping out their employees. you know, they're reducing their workforces or really nuking them because of AI coding.
And I guess there again, this is like maybe the inside baseball take on it, but I see it up close, which is just every major Silicon Valley company is overstaffed. Every major Silicon Valley company has been overstaffed basically forever. They all know it. There's a whole variety of reasons why it's the case.
By the way, I think this is true basically of just like, you know, corporate America broadly, you know, companies broadly. We can talk in detail about why that's the case because it flies in the face of the idea that these companies optimize for profits, which they definitely do not.
Um, like the one thing that is the least true claim in the world is that companies are optimized for profitability, which is 100% not true.
Um, uh, and so, um, and so, you know, and then, you know, basically if you're going to do a big cut, like if you want to do a big cut, if you want to take out, you know, whether it's 15% or 40% or whatever, like obviously you want to, you want to scapegoat, right? You just, you want to peg it on something.
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Chapter 7: What are the generational divides in attitudes towards technology?
Um, and so, um, of course it didn't get pegged on AI. And again, it's not like it's just like a straight lie. Like it is simultaneously true that there are these massive, you know, for this same amount of coding, you can now have fewer people using tools. Like that is true. And so do you need as many aggregate number of programmers if you're generating the same amount of code? No, you don't.
And so you can take out people on the other side. So there is truth to that. But what that misses is what happens on the other side of that, which is, of course, you're not just going to be generating the same amount of code in the future. You're going to be generating a lot more code. You're going to be building a lot more products a lot more quickly. Right.
And that's going to fuel enormous amounts of employment growth on the other side. And so I think you're seeing basically both phenomena play out. And you kind of have to read the announcements coming out of these companies in code because of the way those two dynamics are crossing. Yeah, that's well said.
There was an article that was going viral in our circles the other week about the jobs of the future.
And Yoni Reckman, he said, there's a possibility the only jobs in tech companies are going to be, one, product engineer slash vibe coder slash slop cannon, two, you know, infra security systems, three, the adults in the room, you know, like legal and finance, and then four, hot people slash personality hires. Any truth in there? What do we make sense of this? What do the hot people do exactly?
Sales, people, customer support. There will always be an important place for those who present an easy UX to the world and are pleasant to be around. There are many ways to be hot. Otherwise known as the pharmaceutical sales rep. Yes. Or the Oracle sales rep. So, yeah, so, yes, exactly.
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Chapter 8: How do skeptics and advocates perceive AI's impact?
So, yeah, I mean, look, this is going to happen. Well, not literally. The jobs are going to change. I mean, this is sort of the obvious thing, and this always happens. The jobs are going to change. You know, by the way, so there's like a nascent concept that is actually playing out.
I'm seeing it a bunch of the early leading edge companies in the Valley, which is they're kind of circling around a job title loosely called builder or something like it. And basically the idea is that you have these separate jobs in the past of programmer, product manager and designer.
And I've been describing what's happening in the Valley companies as sort of this three-way Mexican standoff where the programmers think that they don't need the product managers and the designers anymore because they can have AI do that. And then each of the other two doesn't think they need the other two either. And what I've been predicting is like they're all correct.
You know, the product manager can generate code and design now. And, you know, so each of them can do the job of all three. And so the idea is the job's changed. Now the job is builder. And you might come into the builder, you might get on the builder track by coming out of coding or product management or design or maybe even something else, customer service or whatever.
But you then become responsible for building complete products. And again, you have this kind of, you know, you're super empowered by the AI that can help fill in all the things that are not directly in your background. Yeah.
And so, like, I think it's entirely possible that we're sitting here in 10 years, you know, in 20 years or whatever, and like, you know, the job of coder is gone, but you have this just, you know, extraordinary number of builders running around. And again, by the way, this is the historical pattern, right?
And so, I think our partner, David George, did a post on this this week, but I forget the exact numbers, but it's, you know, some giant percentage of the jobs that existed in, you know, call it 1940 were like gone by 1970, right? And they were like ancient history today. Right. I mean, the ultimate example of this is, you know, United States 200 years ago, like 99% of the people in the U.S.
were farming. And today it's like 2%. And having, you know, grown up in farm country, I can tell you all these people who worry about, you know, job loss and job change would not like to go back and be farmers. I guarantee that. And particularly they would not like to go back and be farmers the way people were farming in 1800. Like they definitely don't want to do that.
And so the new jobs that have been created, of course, are far better jobs. And that isn't to, you know, understate the level of, you know, kind of stress in individual people's lives as the economy changes. But in aggregate, the result is evolution towards, you know, towards higher income and sort of more jobs that people are happier to do.
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