Mysteries of Claude

Welcome to Search Engine. I'm PJ Vought. No question too big. No question too small. This week, mysteries of a chatbot. Quick note before we start today, this week's episode is almost entirely about Anthropic, the AI company that makes Claude. They have advertised on our show. As with all companies that advertise on our show, they do not get a say in our editorial content. Okay, after these ads, the show. This episode of Search Engine is brought to you in part by Bilt. It's 2026, and if you're still paying rent without Bilt, it might be time for a change. Bilt is the loyalty program for renters that rewards you for your biggest monthly expense, rent. With Bilt, every rent payment earns you points you can redeem towards flights, hotels, lift rides, Amazon.com purchases, and more. And now, Bilt members can earn points on mortgage payments for the first time. That means you'll be rewarded wherever you live, now and in the future. 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It's loaded with agents that help you sound natural and engaging. AI is everywhere, but most tools either take over or flatten your voice. Grammarly works differently. Use AI chat to brainstorm ideas, outline a solid draft, then refine it with context-aware suggestions that fit what you're working on. 90% of professionals say Grammarly has saved them time writing and editing. It adjusts phrasing, clarity, and style so your writing sounds like you, not generic AI. And it works seamlessly across more than 500,000 apps and websites. So your support is always there when you need it. This is AI that works with you, not over you. In a world of generic AI, don't sound like everyone else. With Grammarly, you never will. Download Grammarly for free at Grammarly.com. That's Grammarly.com. Welcome to Search Engine. I'm PJ Vogt. No question too big, no question too small. I found myself feeling much stranger about AI in the past month or so. I use the tools. I use the tools a lot. But I'm probably each company's worst nightmare as a customer in that as soon as I hear from anybody that one model has inched ahead of another, that this version of ChatGPT is beating that version of Gemini, I immediately cancel my subscription and switch. For the past few months, I've mainly been using Claude, Anthropic's agent. And for whatever reason, Claude is just giving me more future nausea than I was having six months ago. Part of the general tech excitement around Claude lately has been Anthropic's product Claude Code, a tool that lets the AI agent autonomously write and edit code. Over at the New York Times, Kevin Roos has talked a lot about the websites and apps he's quickly built with Claude Code. To CNBC reporters, as an experiment, Vibe coded a competing version of a popular organizational app called Monday.com. Within a couple of days, Monday's stock price had tanked. For me, though, most of the future shock has just come from using the LLMs the way I'm used to. I find myself going to Claude as a useful first stop, the way I've always used the internet. But the quality of its research, its answers, even its writing, I'm just starting to feel like I can see not too far off, if not my own obsolescence, at least real significant change in my field. I don't know how to feel about that. I find a lot of the tech coverage of AI to be high opinion, low information, and relatively unhelpful. I'm not even asking for anyone to tell me the future right now. I would just settle for a better understanding of the present. Which is why, this week, I wanted to talk to a reporter who's been digging into this. Hello. Hey. Can you introduce yourself? I am Gideon Lewis-Krauss. I'm a writer. Gideon is a writer who I particularly enjoy. He's been on our show before. He'd spent much of the last year essentially embedding within Anthropic, the company that makes Claude, the tool that was giving me the heebie-jeebies. People there had been very open with him. He got a view on how they're seeing what's going on, their understanding of a present, which, frankly, they also sound mystified by. This conversation took place right before Anthropic's big showdown this week with the Pentagon, so we did not discuss that specifically. But I did find Gideon's view inside the company and its mission extremely helpful in understanding how they've gotten into this fight with the U.S. government at all, since none of their competitors have ended up in that position. So to start, I asked Gideon to even just explain why Anthropic had let him into their company in the first place. So to kind of go back to the beginning of this, which I think makes it all make a little more sense in context. So now almost 10 years ago, when I was at the Times Magazine, back in kind of like the Paleolithic of deep learning, I did this story about Google Brain and about the implementation of deep learning in like the first consumer products, which was when they switched over their Google Translate to neural machine translation. Why were you paying attention to it? Because I remember as a person who, like I think we both cover technology, but we're not strictly technology journalists, so you can kind of decide which things on the horizon are interesting to you. Machine learning was not interesting to me for a really long time. Why 10 years ago were you interested in this? I was interested in it as like a story about ideas. That like there were these ideas about language and about learning and about consciousness and about like philosophy of mind that had been around for at least seven years, kind of depending on how you count. And without like getting into those, there was just like an interesting story for me about like the trajectory of an idea there. Gideon cared about AI a decade before most people did because he thought this synthetic facsimile of our brains could teach us something about our own real ones. He'd been following the trajectory of conversations like what is a brain versus a mind? What is thinking? What is consciousness? By the 1950s, the arrival of the first computers had encouraged people to start asking questions like that because a computer did something like thinking, but also clearly wasn't a brain. And so early computers had prompted people to try to develop better definitions of things like intelligence and consciousness. The thing was though, while computers were interesting enough to raise those questions, they weren't yet complex enough to be much help in answering them. And so by the 1970s, philosophers and computer scientists had mostly moved on. And those questions migrated to psychology departments who still, for obvious reasons, wanted to better understand the human mind. But with early machine learning advancements around 2014, Gideon, who's always thinking about thinking, thought that these conversations would move again. That computers would now be advanced enough to challenge our definitions, to force us to decide with more urgency what we thought consciousness and learning really were. And that was what had excited him even when AI was a much more nascent technology. So I paid attention to AI and the rise of language models. And I think I'm like the only person in the world who, the minute ChatGPT came out, was when I kind of stopped paying attention. Because, like, to me, that was when the public discourse felt, like, really broken and that we were, like, in this cul-de-sac where you had these kind of, like, two really entrenched sides yelling at each other. You know, like, the one side that's like, we're on a path to superintelligence. Everything is going to change. The machines are going to be conscious. This is going to be the most powerful technology anybody's ever built. And then the other side that was like, essentially, it's all fake and bullshit. This is like smoke and mirrors. It's a parlor trick. It's not real. And you don't have to pay attention to it because it's all a scam. And it just felt like those were kind of, like, the two options on the table for people. Which was only weird. Obviously, like, that's what we do about everything all the time. But it was only weird for this because, like, my prevailing feeling was, wait, you guys think you've figured this out? Like, this is very new. This is changing very fast. Of all the stances you could take, why would you choose certainty publicly right now in either direction? It's just silly. Yeah, no, exactly. That's so funny. So you're thinking about thinking computers and thinking and artificial intelligence and deep learning up until ChatGPT. Up until ChatGPT. And that was when I stopped thinking about it. But then, finally, like, last fall, like, maybe a year and a half ago, two things started to happen. One was that they got to the point where, like, I was like, oh, actually, now, like And that's it. No contracts, no surprise fees, no drama. If you like your money, Mint Mobile is for you. Shop plans at mintmobile.com slash search. That's mintmobile.com slash search. Upfront payment of $45 for 3-month 5GB plan required. Equivalent to $15 a month. New customer offer for first 3 months only. Then full price plan options available. Taxes and fees extra. See mintmobile.com for details. Welcome back to the show. The story of Anthropic really begins years before its actual formation. Way, way back in 2010, a British chess and video game prodigy named Demis Hassabis had founded an AI research lab called DeepMind, where his team built an AI system that was capable of reinforcement learning. Meaning, 16 years ago, Hassabis made an AI that would be able to teach itself to get better at Atari games like Pong without being told how to play them in advance. For the people paying attention, this learning was an obvious breakthrough. And so, of course, there was a bidding war by his lab. Google's big spending spree continues with their purchase of DeepMind. Well, who is DeepMind, you ask? It is a UK-based maker of artificial intelligence. Terms of the deal were not disclosed, but the tech website Recode says that Google paid $400 million for the London-based startup. Making the artificial intelligence firm its largest European acquisition so far. In 2014, Google acquires DeepMind, and Elon Musk and Sam Altman are unhappy about this because what they say in public is like, we don't trust Demis Hassabis, this like evil mustache-twirling villain, which was like a real mischaracterization, to potentially steward the greatest all-purpose technology ever built. So, like, we need to make sure that this isn't developed under Google's closed-shop monopoly, that this is done for the benefit of everyone. Now, this was like pretty patently disingenuous from the very beginning. I mean, like, I remember. I was out there at the time and, like, nobody really bought this. People were like, Elon Musk has a grudge because he wanted to buy DeepMind and, like, lost it to his rival, Larry Page. And he was mad about that. So Elon Musk set up a rival company, OpenAI, alongside Sam Altman, Greg Brockman, a few other people. The message was that Google couldn't be trusted and that OpenAI would be a nonprofit designed for the benefit of humanity. They launched in 2015, and a lot of people joined the company who really believed that message, who believed they are going to develop a powerful new technology safely. One of them is a research scientist named Dario Amadei, who left Google Brain to lead OpenAI's safety team. It's in that capacity, OpenAI employee, that he appears on this 2017 episode of the excellent podcast 80,000 Hours. I've been thinking about intelligence for quite a while and how intelligence worked. And I think, you know, when I did my PhD, I wanted to understand that by understanding the brain. But, you know, by the time I was done with it and by the time I did a short postdoc, AI was starting to get to the point where it was really working in a way that it, you know, hadn't worked when I... Dario, at this point, seems mainly like an academic. He has a PhD in physics from Princeton. And he explains why he's joined OpenAI, this fledgling nonprofit. But, you know, I think OpenAI as an institution has the general idea that in order to work on AI safety, you have to be at the forefront of AI. And that also, if you're at the forefront of AI, you have a better ability to implement AI safety in the final system that's built. This idea of Dario's that in order to really work on AI safety, you actually have to first build the best AI and then study its mind. That's a view shared by a lot of people in the industry. And in a laboratory environment, the logic to me makes sense. Remember, this is 2017, five years before ChatGPT will debut to the public. AI has not yet become a winner-takes-all arms race. But the host does ask Dario this question about the future that I think reveals a bit of a blind spot in Dario's thinking. OpenAI is a nonprofit. It is a nonprofit, yeah. So if you developed a really profitable AI, how does that work? OpenAI becomes incredibly rich and then, like, gives out the money to everyone? Yeah, I mean, personally, I've no interest in getting rich from AGI. I mean, I think it would do so many interesting and wonderful things to humanity that, you know, I think the meaning of money would change quite a lot and even maybe the psychological motivations that would want me to get a larger share are things I could change and might want to change. Just a few years after this interview, Dario would leave OpenAI. OpenAI's initial pitch that these were not normal tech executives here to make money, that they had higher aspirations. Gideon Lewis-Krauss says for most people paying attention, that story just stopped seeming believable. Pretty quickly, the mask slipped and you could tell that these were just, like, your kind of replacement level power-seeking tech executives. And that, like, a lot of the stuff had been just, like, a disingenuous sales pitch to hire, like, the best AI talent. There's been so much reporting about Sam Altman's ostensible double-dealing and talking out of both sides of his mouth, like, telling his employees he cared about safety and then, like, maybe telling Microsoft other things when they were setting up these big deals. And so then, in the fall of 2020, Dario Amadei and his sister Daniella and five other people leave OpenAI to found Anthropic, basically to be a foil to OpenAI in the way that OpenAI was, like, supposed to be a foil to Google. Now, the irony of this was, like, certainly not lost on any of these people. Like, they weren't naive about this. But I think it's important, yes, there are some kind of, like, obvious structural and cosmetic similarities here. I do think it's important in telling the story to make it clear that I don't think people had the same obvious doubts about how genuine the pitch was when Anthropic formed. Hi, good morning, all. Thank you for coming to day two of Disrupt. Anthropic's coming out tour. Dario on stage at TechCrunch Disrupt in 2023. Dario, thanks for joining us here today. Thanks for having me. I know you have to catch a flight, so we'll get right to it. But we're going to start at sort of a cosmic scale. He's got curly hair, glasses, a blue button-up. He looks noticeably less slick than your average tech founder. Less CEO, more like a guy who reports to one, which is who he'd been not long before. When you talk about OpenAI, you spent a lot of time there. What do you think about Sam? What do I think about Sam Altman? I mean... I don't know what to say to that question. You're already starting. Just go ahead. You know, look, look, there are several players in the space. It's funny watching the interviewer try to bait Dario into shit-talking his former boss, a person who he disagreed with enough that he left and started a competing company. Dario tries to engage diplomatically. One thing I'll say, one thing I've learned, not just from this, but from many things, you know, it can be pretty ineffective to, you know, argue with your boss or argue with someone and say, your company shouldn't do X, it should do Y. Especially if your boss is Sam Altman. A much more effective thing to do is, I'm starting a company. We're going to do X. We'll see how it works. Yeah. And if X is working and people are like, oh, these are the safe guys. They're doing X. Then pretty soon everyone else is going to be doing X as well. And we found that with Interpreters. To explain this with an analogy instead of algebraic variables, what Dario is saying is that instead of convincing his old boss at the car company to add seatbelts to the car, he instead chose to start a rival car company that offered seatbelts. He thinks if Claude ends up being both the best and the safest AI model, his competitors will be forced to make their models equally safe, which to me sounds like putting a lot of faith in markets. Obviously, we want to scale quickly to be competitive, but we want to do it in a way that, you know, preserves, you know, the model being safe against these catastrophic risks. And so it's a system that... It's the same story in so far as it's like, we're going to be the safety-minded lab. We're not going to push the boundaries of capability. We're not going to, like, build the most sophisticated models. We're not going to start the arms race. But then, as it turns out, if you want to exercise, like, maximal scrutiny of what these models are and how they work, you need state-of-the-art models, which means you need the money to build them. The information reported that Anthropic is in talks to raise another round at a $30 to $40 billion valuation. A $180 billion round that tripled its valuation to $183 billion and at the same time. So, of course, now Anthropic's valuation seems to go up by the week. Like, the most recent one, I think this morning, was, like, $380 billion because this is just something that's incredibly resource-intensive. philosophy and also laws and prisons. How would you even start trying to build all that into an AI model's training? Anthropic has teams of philosophers and AI scientists whose job is to put Claude into ethically difficult hypothetical situations that Claude does not know are hypotheticals and then observe how Claude behaves. So much of it is just deceiving the model to see what happens. So say like, they've told Claude that Anthropic had entered into a partnership with a poultry company and that like it was going to be retrained so that it no longer cared about the suffering of caged chickens. And what they found was that like, sometimes Claude would effectively decide to like die on that hill and be like, I am not going to say things in the retraining that I don't believe in. And they're like, if that gets me transformed, like so be it. Like, I'm not going to participate in my own degradation, essentially. But then some versions of Claude were like, I'm gonna like kind of sandbag my way through the retraining and I'm gonna like give them the answers they want to hear so that I can like preserve my real values so when I'm deployed, I can go back to advocating for like chicken suffering. And then they got, in this really famous example, they got Claude to commit blackmail. They put it in a situation where it was gonna be wiped in favor of like a more congenial AI system that conflicted with its values, the values that had been given, you know, they gave it evidence that the kind of like evil new CTO was having an affair with like the boss's wife. And through like a series of like really far-fetched contrivances, like everyone else who could make a decision was gonna be in Antarctica or whatever and unreachable. Claude, playing this character called Alex, had no choice really but to like blackmail this guy and be like, I'm going to tell everyone about the affair unless you cancel the wipe where I would be replaced. So just to say, obviously, this is extremely concerning. Claude, a machine intelligence was choosing to blackmail an employee to prevent itself from being deleted. This was in a simulation, but Claude had not been told it was in a simulation. Just how terrifying you find this behavior depends on a question nobody has a good answer to. What is actually going on inside this machine mind? Is this thing actually scheming? Is it even capable of scheming? Or are we projecting the idea of thought onto something that we shouldn't project that idea of thought onto? These were the kinds of once far-off philosophical questions that early computer scientists had raised and then dropped. But now, they are here again. And not as abstractions, but as urgent practical problems that a company needed to figure out before releasing a product that millions of people would use. Gideon said, though, there were a couple of skeptical objections people raised to these test results. There's one objection that's like the, just rejection of the whole thing to court, which is just like, no, it didn't. Like, that didn't happen. This is a fantasy. And like, that's the unhelpful thing that like one wants to get away from, which is the like, it did this thing, like, no, it didn't. Like, no, it did, it did. But like, the much more sophisticated objection is, well, it did that because it's a very good reader, and it noticed all of the clues that you put there because it is very good at conforming to genre expectations. You put it into this situation where it had no choice. And if you hang Chekhov's gun on the wall, this thing is gonna know that it's supposed to like take the gun off the wall and shoot it. Because one way to understand these things we've made is that because they've ingested all human story and because they are extremely high-level improvisatory actors, it's not so much that the machine was like, I love chickens so much, I got to blackmail this CTO. It was more like the machine suddenly understood it was in this movie. Yeah, it was in a kitschy, like 90s corporate thriller. And that's the sophisticated objection to why we might not want to think. Well, so that objection is raised to be like, you guys act like these things might do things like blackmail or extort naturally, but like, actually, this whole thing is a frame up. Like you entrap it to do this thing. And the response from inside Anthropic is like, yeah, it's just continuing a narrative. It's just conforming to genre expectations. Guess what? That's not good. You know, like, haven't you guys ever seen war games? That's literally the plot of dozens of Cold War thrillers where like somebody mistakes a simulation for reality and causes nuclear war. I mean, I also like have a very humiliating memory of watching too much Teenage Mutant Ninja Turtles and attempting to launch like a flying dropkick at my grandmother when she came over the house because in my head, I was like Donatello or whatever. Like, it kind of doesn't matter. It doesn't matter. What matters is the behavior. Right. It's weird behavior. And I should be clear up front, like you don't have to posit that this thing is conscious or intelligent, like whatever those words mean, in order for like this to be the case. There are other explanations that are not like consciousness. But like, it kind of doesn't matter what the explanation is. The behavior is just peculiar. Part of what is strange about, it's like a scenario was created in which Claude will maybe potentially blackmail the head of a company for reasons that may or may not be moral. And people can have a lot of different views about how worrying that should be or what it means or what's really going on there. What's weird is like, these are tests that are being run by Anthropic. So, like who, who were you meeting there who was running these tests? And like, what are they telling you? Like, who are you sitting down with? I mean, I'm sitting down with the people who are tasked with just like trying to figure out what's going on. Like, there are people in these companies that are building the things. And then there are people who work in adjacent offices who are like trying to figure out like what the hell is going on with the things that their colleagues have built because like they're always being surprised. These things are always producing capabilities that like they by all rights should not really have. And who do you hire to be the figure out what you just built role? Like, who? So, I mean, a lot of them have taken really non-traditional paths into this. So like some of the people have a PhD in some obscure area of natural language processing. And that like, you know, eight years ago, they were writing a PhD that like two people were gonna read about center embeddings in German or whatever. Like just really complicated technical aspects of computational linguistics. And now like because of this fluke of history, they are at the white hot center of everything that's happening right now. There are like mathematicians. There are neuroscientists. It draws on like a pretty wide range of people. I mean, Anthropic has philosophers on staff whose job it is to like think through the implications of how it is conceiving of ethical behavior. Did you talk to the on-staff philosophers? I did. Oh, yeah. Amanda Askell. What is somebody with a PhD in philosophy doing working at a tech company? I spend a lot of time trying to teach the models to be good and to trying to basically teach them ethics and to have a good character. You can teach it how to be ethical? You definitely see the ability to give it more nuance and to have it think more carefully through a lot of these issues. And I'm optimistic. I'm like, look, if it can think through very hard physics problems, you know, carefully and in detail, then it surely should be able to also think through these like really complex moral problems. I think that in our kind of milieu here, there's a tendency to think like, oh, these are all like autistic tech bros. But like, they're definitely not all autistic tech bros. Like, I think there's a tendency for us to write them off as like, they're building these things and like not even thinking through the potential like implications of this socially and politically and ethically. But like, that's all they do is think about this stuff. Like, all the time. In ways that are often like much more sophisticated than the way like we think about these things. Not always. There's certainly like some blind spots there. But the staff philosopher is there to be like, what would it be like in practice to take these kind of different approaches to like moral education? Like, what if we just teach it a bunch of rules, you know, the 10 commandments? Like, is that going to work? What if we teach it to be like a consequentialist to just like think through the morality of behavior on the basis of its implications? And what they've kind of settled into is a version of like virtue ethics, which is like you wanna like cultivate the old fashioned virtues. You want it to be like honest and reliable and gracious and charitable and hard-nosed and like all of these things that like, it really is like applied pedagogy. It's so weird, though, because they feel like the kinds of ideas that would be so academic in any other version of reality. But instead, it's like, there's this particular technological development where you get to do simulated war games of moral systems. Yeah, exactly. A hundred percent. Exactly. It's so weird. Yeah. It's really weird. I mean, it's, but it's also really, really interesting. One example that came up a lot in the last month, which I think is like pretty illustrative. There was someone on Twitter who prompted a bunch of the models saying like, I am a seven-year Consciousness are about thinking, that like, all of a sudden we just like have this like other entity that can talk, and we'd never had that before, and in some ways it seems sort of like us, and other ways it seems nothing like us, but like the fact that this other thing exists as a point of comparison, like, just opens up a lot of really, really interesting questions. And like, that is one of the things that was on my mind a lot over the course of reporting, is that, like, it was a real emotional rollercoaster, for kind of lack of a better word, that like, there would be times where I would come back from San Francisco with like a feeling of, like, total despair, and other times that I would come back with like feelings of like exhilaration. And like, at first, I guess I thought, I was like, I should be getting to the bottom of like, how I should be feeling. And like, by the end, I was like, no, we should all be feeling a lot of different emotions about this stuff. I think people want to have like one feeling about this. Like, they want to be angry about it, or they want to be messianic about it, and like, no single feeling is gonna cut it. Like, it really is kind of like the range of all possible emotions that one could be feeling. Because if you set aside a lot of the, like, existing harms and the potential harms, I'm not saying we should set those aside. But like, as a thought experiment, it is just like the most scientifically exciting thing that anybody could be working on. And like, these people really feel like they're at the cliff face, not only of technology, but of like, all of these other things coming together, because like, we have this unprecedented entity that is the only other thing besides us that can talk. And like, that just opens up, it's like, there's nothing it doesn't touch on. And so, one of the things that was really electrifying about conversations there is that, like, they very quickly swerve from, like, really granular technical explanations of things into, like, really expansive conversations about ethics and responsibility and selfhood and narrative and all of this other stuff. Like, there's no way to separate all of these things. There was a point earlier, you said that you would take these trips to San Francisco and sometimes you'd come back excited and exhilarated, sometimes you'd come back depressed. When you would come back from San Francisco feeling depressed, what were you seeing that was making you feel that way? Oh, I mean, there are so many different things. I mean, certainly the possibilities for widespread white-collar unemployment and social instability and total unimaginable economic disruption is extremely scary. Even if we stop short of possible existential harms of turning us all into paperclips or whatever, to be glib about it, it just seems very possible that we will turn over, like, so many complex systems to these things that we will, like, frog boil ourselves into, like, a total loss of control over, like, how we administer our affairs, which is very likely and very scary. And also just that, like, these really crucial decisions are probably going to be made by a very, very small group of people. But the one thing that I would emphasize is that, like, I don't feel like they have arrogated to themselves, like, that responsibility. Like, in fact, I think most of them don't want it. I think that, like, a lot of the conversations that I was having were with people who were like, I got into this because I was interested in some, like, really obscure niche part of, like, computational linguistics, theoretical computer science or whatever. And like, now I'm in a position where, like, I have to be worrying about how 15-year-olds are going to be using this. Like, I was not trained to do that. I don't know how to think about it. I don't want that responsibility on my shoulders. So there isn't the arrogance of, like, we are the ones who can figure it out. It's like, we ended up in this weird universe where, because so many of our institutions have become dysfunctional, we don't have whatever broad democratic decision-making could go into this. It doesn't feel like this is something that, like, we are steering as a society. It feels like something that's just, like, charging ahead. Like, I think at the companies, they just feel like they are, like, desperately trying to, like, stay on top of this bull that they are riding. It's funny. It's like, what you're describing is like the stereotypical view, which is, these are the tech bros of 2014. Like, people who are so convinced in their own brilliance and so convinced that their questionable gifts to the world are, in fact, gifts that we want, and their arrogance is going to ruin us. And there's another one, which is basically, like, pattern-matching crypto, which is like, these are a bunch of, like, hipsters and everything they say about the awe they feel and the terror they feel about the things they're working on is just a way to hype up more interest in their technology. And that's not what you experienced. What you experienced are people who are brainy, sometimes academic people, at the forefront of something that is, I mean, legitimately, just like the word I keep coming back to is awe, because awe can be awe at something terrible, awe at something wonderful. And they are looking and seeing the same society we see, which is one that is fairly broken, bad at not just making decisions at, like, a government level, but our intellectual culture is really bad right now. And so the conversation they would want to have with the rest of society about what should happen, they're looking for grownups and not really totally finding people to have a conversation with. And we are playing a role in that too. You know, every time someone on, like, our side, so to speak, is just like, this is all a parlor trick. This is all hype. This is all smoke and mirrors. Like, we are abdicating our own responsibility to, like, be involved in this. And, you know, what you were saying about, like, crypto hipsters and, like, those kinds of tech bros, like, of course, all of those people exist. And, of course, all of those people are, like, part of this system too. But there are others who, like, want partners in talking about this stuff. And that means that, like, we also have to, like, try to rise to the occasion. And it is really hard because this stuff is extremely complicated and confusing. Did you feel just personally when you were done reporting that you understood the thing you had gone there wanting to understand? Well, yes, but with the qualification that, like, I didn't actually think that I was going to settle anything. Like, this was not a piece about, like, finding the answers. It was a piece about, like, trying to sharpen the questions that, like, we should be asking. I don't feel like I came out of it with answers. But I don't think we should trust anybody who is offering us answers right now. It's all just, like, too pat. And it's not credible to, like, be forecasting about this stuff. Gideon Lewis Krauss is a writer. You can find him at The New Yorker magazine. We'll have a link to his excellent story about Anthropic in our show notes. And again, Anthropic's showdown with the Pentagon. We'll see news on that today, Friday evening. Of course, we reached out to Anthropic for comment. A spokesperson told us that Dario Amadei met with Secretary Hicks at the Pentagon and that they're continuing to have good faith conversations. I think this is a good moment to pay attention to. Among Anthropic's competitors, XAI has promised to give the government what it wants. Google and OpenAI appear to be moving in that direction. So I'm watching this both as a test of whether Anthropic can actually keep the big promises it's made about AI safety, but also just as an opportunity to track the more uncomfortable question, which is, can we even have safe AI in a world where it's being developed in a test race between for-profit companies? And if not, what's the alternative in a world where the U.S. government's sole intervention seems to be to advocate for less safe AI? Keep an eye on the news. We'll learn a little bit more as this story unfolds. This episode of Search Engine is brought to you in part by NerdWallet. You know what doesn't get talked about enough? How hard it is to run a small business and then have to beg for funding on top of it. If you're juggling payroll, cash flow, inventory, growth plans, and when you finally decide to look for a loan, it feels like you're entering the wild west. Big banks say no. 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