[0:00:11] Hi, everybody. Welcome back to the San Francisco season of It's Not Magic, our podcast from Sixth Street. We invite influential leaders and founders to get to the core of how they're creating innovative solutions to stand out in their industries. San Francisco, we've got a motto. We say it all starts here, and it does. Music, culture, food, tech, and not incidentally, Sixth Street. This season, we've been focusing on the leaders driving the renewed momentum shaping our city's future.
[0:00:38] And it's not just magic, as we say. We're excited to dive into the vision, grit, and the people making it happen. It feels very important that we sort of have this concept of a human in the loop to also just make sure that the models are not kind of veering into a direction that we don't want them to be. Are we letting the models be 100% fully autonomous for tasks? Or is there a process of being able to kind of bring humans and AI together?
[0:01:06] Hold light and shade is one of our values. And it's this concept that the technology itself has great risk and great opportunity. And that that is a very complicated, complex thing to hold, right? We have to consider and talk about all of the risks, all the things that could go wrong, while also considering thinking about and building towards a world where all of the things go right.
[0:01:25] My sense is given the locus of the technology industry being here, a kind of orientation towards creativity, it doesn't surprise me that artificial intelligence, you know, first took off in the Bay Area.
[0:01:37] There's accountability that the non-tech residents of San Francisco kind of put on the technology companies that I don't necessarily think is bad, right? They're like, hey, we're providing a home for you. We just want you to be good citizens. Over the course of the past few years, there's been a lot more mutual understanding between what I'm describing as kind of old-time San Francisco and tech. That's Daniela Amadei, president and co-founder of Anthropic. If you're paying even passing attention to AI, and you definitely should be, you know Anthropic.
[0:02:06] Their founding group broke away from OpenAI to start a more human-centered AI company. They're famous for promulgating a responsible scaling policy for Claude, their next-gen AI system. Like many of our guests this season, Daniela was born and raised in San Francisco, and so was Anthropic. They were founded in 2021 as a public benefit corporation, and Anthropic's become one of the fastest-growing tech companies in history, embodying San Francisco's spirit of entrepreneurship and innovation.
[0:02:33] Beyond the millions of people who use Claude, Anthropic serves over 300,000 business customers from Fortune 500 companies to startups, and they employ thousands of people, including 1,300 people right here in San Francisco. Anthropic actually just announced it's taking over an entire 27-story tower in downtown San Francisco to support its growth. In fact, since we recorded this conversation at the end of January, lots has happened because something crazy and dramatic happens about every 10 minutes in AI. On February 5th,
[0:03:02] Anthropic released its newest model, Opus 4.6, and reports from software engineers are that their new model and OpenAI's new model, they're another major leap forward doing the technical parts of their jobs, not just adequately, but very well and very quickly. These revelations and the excitement and anxiety that come with them, they rippled through markets over the last two weeks as capital tries to figure out what all this means.
[0:03:25] You're seeing OpenAI and Anthropic back competing super PACs gearing up for this election cycle, effectively staking out ground over whether and how we should regulate AI. And the rest of us, we're watching with combined wonder and fear at the possibilities, at the risks we're trying to understand. So this is a super interesting moment to sit down with Daniela in the library at Anthropic's headquarters in San Francisco. Look, we talked about a lot of different things, including how you create products with a strong emphasis on responsibility and safety.
[0:03:52] Actively addressing the potential dangers of AI and how you measure if any of that's working. We talked about what Anthropic is seeing in terms of adoption in different regions within the United States and across the globe and how you encourage more consistent adoption. We talked about when is the industry supposed to insist on being regulated. We talked about Daniela's experience as a musician. We talked about books, how generalists and specialists get the best out of each other, how you preserve culture amid really rapid growth. And we talked about why we're all very long and optimistic on San Francisco.
[0:04:21] If you're tuning in to learn the latest trick that AI can do, forget it. You already missed it. Instead, this is an interesting conversation with an interesting person in a very important seat set in a vibrant downtown in a beautiful city. Kind of cool moment, I guess, and I think you'll enjoy the conversation.
[0:04:38] Thanks for having us. Oh, my gosh. Thank you for having me. It's great to be here. It's a pleasure. Good to see you. Can you tell people what room we're in? I mean, you can't really see the books on camera, but like we're in a library. It's amazing. We are in a library. Yeah. Anthropic is such a unique company. And I feel like a library speaks to the research roots of Anthropic. But in general, I think we're very well read, like people at the company. Oh, interesting. Very multidisciplinary. Like I think when we first.
[0:05:00] Started out, one of the things that most struck me was just how many different disciplines people came from who came to the company. We had like political scientists and ethicists and biologists. I was a literature major. As you can see, the literature major has like shown through. Yeah, you definitely do. But I actually encourage you if you want to borrow a book on your way out, go peruse. Really? Yeah. That's like kind of like a pass to come back in and return it, which is nice. Okay, so.
[0:05:23] It's January 2026. I feel like even if we drop this podcast tomorrow, so much stuff will change between now and then, whether it's geopolitics or the economy or tech or AI. Tell us where we are. How do you think about it? Yeah, light, easy question to start with. Yeah, exactly. You know, I think one of the challenges of working in this field is it's much easier to look backwards and talk about an epic that happened. But as it's happening, sometimes we don't even necessarily...
[0:05:51] Expect or fully understand where we are in relation to kind of what will be true six months from now or three months from now. But I think there's kind of a few things that feel especially like present or happening right now. One is at least internally, we feel like the last class of models that we released was a big step up. So Opus 4.5.
[0:06:12] Just in its capabilities, right? The level of intelligence of the model, but also the way that it's now being used in the world. I think particularly on the coding dimension, you have developers who are now saying, I'm running Claude Code like 100% of the time that I'm working. It's making me twice as productive, right? It's doing most of the low-level tasks for me. We're also seeing quite a lot of adoption in biological sciences and healthcare, which we've always had this dream, right? It's something we talked about really from day one of...
[0:06:37] I mean, it sounds aspirational, but can you use tools like Claude to literally help find cures for diseases like cancer?
[0:06:45] This is sort of this big dream, this big idea we've had. But now as we're doing company planning, we're talking about, hey, can we contribute to helping to eradicate polio in 2027 and 2028 if we partner with groups that are doing it? So I think probably for us, the biggest thing I would say right now is just the step up in the capabilities of the models. And then all of 2024, 2025, agents was kind of this word that was thrown around. I almost feel like it lost meaning.
[0:07:10] But I think this is truly the first time we've seen Claude capable of significant agentic abilities. So Claude is able to actually go onto your computer and move your files around or open them or process them or delete them or restructure them. That was just not possible literally in December. So the difference between...
[0:07:30] 2025 and 2026 in the course of a month has felt like a big increase to us. Yeah, I feel like at the end of the year, all the kind of wrap-ups of the year on A were like, oh, agents are actually disappointing. This was not the year of agents. We've got years and years to go. What changed between a month ago and now? You know, what I find interesting is, again, like, do we really know? No.
[0:07:49] I would say this, I don't know if prediction is the right word, but we have this sort of belief in this concept of scaling laws, right? You give more compute to the models, you give them more information. They get smarter at a predictable rate. And we couldn't have predicted in advance when we would have crossed a particular capability threshold, right? So we wouldn't have said, oh, we know like this model or at this date, Claude is going to be more capable of agentic capabilities. But I think as the models just get better and get smarter, A, we're able to do some training stuff to actually help.
[0:08:17] You know, empower some of those capabilities. But I think more broadly, what we're seeing is just like watching a person get smarter over time, right? Get more education, go to college, learn more things. And I don't necessarily know that we're going to be able to predict every future.
[0:08:30] I think what's interesting is, like most technologies, AI is following...
[0:08:54] I would say a mostly predictable adoption path, right? Which is that, unfortunately, the folks that have the most are going to be the first to adopt it, right? They have the most resources. They have the most time. They have the most access. And so they're going to be the folks that say, like, cool, I'm a computer scientist at MIT. Of course, I'm going to start using Claude Code. But I think what we're seeing is the rate at which the technology is being adopted is significantly faster than anything else, right? If you look historically, even at things like...
[0:09:18] The adoption of Google or when people had dial-up for the internet, AI is just going much more quickly in terms of adoption rates. The trend is the same, but the speed is faster. And so I think what we're going to see over time is a broader distribution of state adoption than perhaps with previous generations of technology. And I actually think the same will be true internationally as well. But I also think that there's work we have to intentionally do to make sure that there are not...
[0:09:44] Big regions of the world that are left behind. Right. Because of how quickly the technology is developing, being one year behind or two years behind could actually have an incredibly big impact. Yeah. How are you thinking about that? Like a theme of knowing you a little bit, following you guys, a theme of Anthropic is there's the slogans and there's the culture and the good stuff and you're known as the ethical company. You're actually trying to back that up with concrete in the world stuff to use the technical term. On that point in terms of like adoption in countries where it's just not happening, how would you do that?
[0:10:14] I think there's a couple of different ways that we approach this. Yeah.
[0:10:36] Publish papers and reports about the trends that we're seeing, right? And that's everything from adoption, like we've talked about where the technology is being adopted, potential risks that we see, suggestions for policy about how to address some of these issues, because we alone cannot solve the problem. And I actually think corporations alone together can still not solve the problem. It's going to take action from civil society groups, from government. We do personally try to take some responsibility for this. Anthropic has two different teams that work on something we call beneficial deployments.
[0:11:05] And this is essentially our efforts to deploy the technology for things like biological and life sciences, healthcare, developing world. So we have a number of pilots with the Gates Foundation. We also work with the Clinton Health and Access Initiative. And we're running many different experiments to see how we can just approach potentially deploying Claude in developing countries. Got it. All right, let's talk about Anthropic, the ethical company. So I think everybody who's listening to this already knows the constitutional AIs, but spend a minute on...
[0:11:34] What do you actually mean by that? Constitutional AI is this idea that our researchers sort of invented. And the reason we came up with it is that the previous techniques used for training LLMs essentially was a like reward function system. So basically, if you ask it a question, if it answers the question correctly, you give it a reward. If it answers the question incorrectly, you don't give it the reward. Sometimes you even give it sort of a form of punishment is the wrong word, but you say, hey, that was the wrong answer.
[0:12:02] We felt that there was just a better way to kind of approach how the model learns. And it evolved into this concept of constitutional AI, which is essentially rather than sort of saying, hey, this is a good answer. This is a bad answer. This is an ethical answer. This is an unethical answer. We actually gave Claude a system, a framework for thinking about ethics. So we trained it using a variety of different documents. I think most famously in the original constitution, we put in the UN Declaration of Human Rights. The Apple Terms of Service are in there.
[0:12:31] We recently published Claude's constitution, but I think essentially we're sort of trying to say like, we really want the models to understand a broader system of ethics. So not just what is, you know, one particular question, how are you answering it? Is it correct or incorrect? But how do you actually give it a framework, like a moral framework to say, how should people be treated, right? How do you make sure that you're not discriminating against people? How do you make sure that you are thinking critically about how you approach?
[0:12:58] Complex ethical questions. And what we've seen is this, you know, over time, not only increased the ethicalness of its answers, but it increased its overall intelligence and capability too. How do you judge if that's working? Can you measure that? I mean, it's ethics, so it's famously subjective, but...
[0:13:15] How are you determining whether or not it works? So there's two different mechanisms that we use. The first is definitely looking at kind of performance compared to competitors. But the second is there's an evolving sort of set of benchmarks that are used around a variety of different measures of model capabilities, but also sort of models' abilities to grapple with complex issues. And it's really tricky because the benchmarks are pretty outdated. They were sort of made for a different era of LLMs.
[0:13:41] Even kind of prior to LLMs. But what we're attempting to do is have a system of benchmarks and evaluations that are kind of agreed upon in the academic community to say, how are we actually going to measure these models? And I think it's a little bit of an imperfect art, but Anthropic has invested significantly both in measuring our own models, but also trying to contribute to say, how should we have these benchmarks kind of exist in the world? Got it. We're kind of in the pre-collective action era in terms of like how AI should live in the world.
[0:14:10] And right now, I think one of the things that you guys talk about is constitutional AI ought to result in a race to the top, right? Where other companies, hopefully, or other players are adopting because they see that it's working. They see that it benefits you guys, so they'll want to do it, and you're in favor of that. Where are you seeing that? You know, I think race to the top is a really useful concept that we've actually applied across a variety of different ways that we operate. So I think one of the most classic ones is...
[0:14:34] Many of the guardrails and the safety techniques of which Constitutional AI is one, Anthropic pioneered. And what we saw was that this drove demand for our products in the market. And I think in particular, enterprise customers really care about having a lot of these safety, security, reliability features in place. And so a lot of the time what would happen is an enterprise would sort of say, wow, we're choosing to use Claude. We're choosing to partner with Anthropic because...
[0:15:01] Right. Right. Interesting.
[0:15:30] We talk about it with businesses. We talk about it in our research papers. And suddenly people are coming to Anthropic to work on our interpretability team, but they're interviewing at competitors and saying, hey, if you had an interpretability team, I might be more interested in working here. And what we've seen is interpretability teams now spinning up at competitor companies. And so I think this idea that if you can find the intersection of something that is.
[0:15:53] So I think a really important dimension of this is that Claude's capabilities are also extremely powerful.
[0:16:23] And I think over the course of the past several years, we've arguably had the strongest models for the majority of the time. And so what we've seen is particularly in areas like coding and agentic coding, that cuts across industries, right? So if you work in financial services, in healthcare, in the technology space, at a legal law firm, right? All of those areas have a need for technical development tools. Anywhere that's going to have...
[0:16:47] A set of developers, people that are writing code, they're going to be using Claude Code. And so there's an enterprise demand to use our products sort of regardless of industry.
[0:16:55] And I think that's also just speaks a little bit to both the specificity of this kind of artificial intelligence skill, right? We talk a lot about artificial general intelligence, but like the models are really, really good, for example, at writing code. But then there's also a set of general use cases that I think apply, again, across a lot of business sectors. And actually what we've seen is pretty rapid adoption, unsurprisingly, you know, most quickly from technology companies, because again, they're going to be the most, you know, tech savvy. They're going to be reading the news about AI. But increasingly,
[0:17:24] Especially over the course of the last year, I would say many more enterprise businesses have, I think, understood the need to have an artificial intelligence strategy. And I think in addition to having capable models.
[0:17:36] Having this very strong safety orientation. Anthropic is also just well oriented to being a business to business company, right? We care about partnership. We integrate directly with a lot of the companies that use Anthropic. We serve over 300,000 businesses worldwide. And we've just gotten a lot more practice actually working closely with customers in the enterprise space. I love that. I was a transactional lawyer for a lot of years. And I think about my training.
[0:18:02] This question is about like are we in the age of the last experts, right? Because I think what people say is we're always going to need humans. We're always going to need judgment. We always need people like you sitting on top of organizations like with vision, with judgment, with ethics, with the ability to communicate. But how do you train that? And like the way that you in all likelihood, you know, develop judgment and continue to develop judgment, the way I developed judgment was like getting my reps as a young person and doing the drudgery, honestly. And if we take that away, how do we make sure that people can develop judgment? I think.
[0:18:30] We as a society are entering a really interesting period. What does productive work mean? Just the nature and the shape of it. I think in the same way that before the internet, which I'm old enough to remember a time before the internet.
[0:18:44] What you did for work every day looked really different than what you do. You know, the difference between 1990 and 2010 was dramatic. We're kind of compressing that into a much shorter period of time in terms of the rate of technological development in artificial intelligence. But I think fundamentally, you know, what's interesting is I should start with a caveat, which is suddenly all these developers are saying like, oh my gosh, like Claude is so good at doing my job. This feels a little scary.
[0:19:10] And as kind of a people leader and a manager, I'm like, oh, yes, of course. This could impact your work, but Claude could never do my job. And then I'll ask Claude to help me coach a report through a challenging situation. And I'm like, wow, Claude, that was actually a really good answer. My report could have asked you that question. And so I do think it's a reckoning that we're all going to have to face together. But I will say, I think we are underestimating the degree to which AI and human compatibility
[0:19:39] And partnership are going to be how we walk into this new world. So much of what we've seen, even today, even with the incredible capabilities of something like Claude Code, is developers are better with Claude Code than Claude Code alone or the developer alone. Right. Will that...
[0:19:56] Continue forever? Of course we don't know. Will there be some disruption? I suspect yes. But I think what we're really seeing is that the intersection of AI doing what AI does well and humans doing what humans do well is actually going to be the way that we sort of pull everybody up. Yeah. And I'm also remembering we did like a leadership offsite and our chief product officer at the time drew this kind of diagram of like what a developer does.
[0:20:21] Right? And he said, actually, like, hands-on keyboard coding is about 20% of their time. So even if you imagine... This was when? This was like before? This was six months ago. Okay, fine. So maybe now it's 30%. A lifetime ago. I don't know. Maybe 30%, maybe 40%. Okay. But nevertheless, there's so much work that goes into, you know, how do you actually architect the code that you're writing? How do you have it communicate, you know, with other parts of the code base?
[0:20:43] What is the product you're actually trying to build? Who is the customer you're building for? How much time are you talking with them? You're spending time with designers. You're spending time with product managers. You're trying to understand the customer. And so a lot of where my mind goes is that...
[0:20:57] People who have the ability to work with other people, who have humans like to talk to each other, right? Regardless of how good AI becomes, I think there will always be a role for people to communicate with each other. Even if we were, you know, to imagine that that full 50% were able to be done by an AI, say it's 50%, right? Of the kind of code writing process for a developer. First of all, I don't think that's necessarily going to be the case, but even if it were, what it means is that the other 50% of the job becomes a bigger focus, right? And I think our ability...
[0:21:26] And maybe in the sort of example you shared.
[0:21:46] Rather than kind of coming up through the ranks of sort of having to grind away, you know, when I worked in DC, this was the ethos too, right? It's like grind for 15 years and then you'll kind of have the plum job. You kind of get to leapfrog some of that. And maybe that's actually nicer for the next generation of people that's going through the 15 or 20 years of this sort of drudgery. It does all go back to something you said about when do we decide to flip the switch into collective action? Like whether it's industry-wide or there's some sort of government thing, where are we relative to that? Where are we relative to sort of having to have some guardrails that...
[0:22:13] We're all going to kind of agree on and are we there yet? And what should that look like? So I think there's a few different ways that we can approach this. One of the things that I think Anthropic has always felt.
[0:22:23] Strongly about is the need to have a human in the loop in a lot of work that's done by artificial intelligence. Some of that is for safety reasons, right? You just don't necessarily want a new technology to go off and be able to just kind of take actions 100% independently from sort of an end-to-end task without a human checking, particularly for very important decisions, right? Anything related to health, financial services, you just want to make sure a human is kind of checking over it. But I think...
[0:22:48] In general, it feels very important that we sort of have this concept of a human in the loop to also just sort of subtly make sure that the models are not kind of veering into a direction that we don't want them to be. And I don't know exactly the sort of structure and form that that might take to kind of bring it to your point about collective action. But I think this concept of are we letting the models be 100% fully autonomous for tasks?
[0:23:11] Or is there a process of being able to kind of bring humans and AI together to do things collectively or to do things together? And doesn't that sort of, A, give humans the opportunity to sort of say like, wow, is this really what we want the model to be doing? Is this the intention behind it?
[0:23:29] It provides some guardrails. Again, I don't necessarily have a recommendation yet for like, what should that look like? But I think this concept of really combining the work of AI and humans together is going to be really, really critical in the next few years. Okay. This is the San Francisco season of our podcast. When you and I first met, we met with Mayor Lurie. He was our first guest on the scene. We've had some incredible guests, including you. We're in downtown San Francisco. You're from San Francisco. Was it just inevitable that AI had to be here and you guys had to be like, what is it about this place?
[0:23:58] Oh, man. You have to be careful about asking a native what it is about San Francisco because we'll talk forever. But one of the things that I find the most incredible about it is just the dynamism of the city, like how much it has changed. It has waxed and waned over the years. I grew up in San Francisco. I grew up on the mission. I went to Lowell. And I have friends from sort of different eras of time in San Francisco. And inevitably, at some point, someone will say something along the lines of like, well, the way San Francisco used to be or like kind of how things were better in the old days.
[0:24:27] And I think what I find so interesting is like, you know, my parents moved here in the 70s. And I can easily imagine them saying like, oh man, by the 90s, it was so different, right? Like the good old days of the 90s. In the 70s, the hippies were here and it was creative. It was so artsy. And then all that kind of got washed away. And I think it's just like a good moment for reflection and for humility to just think of like.
[0:24:48] What other city has gone through the level of transformation that San Francisco has gone through over the course of the past hundred years even, right? Long before anybody in my family lived here. I think it is a one-of-a-kind city. The combination of openness, expression, creativity, I still feel that spirit.
[0:25:07] In San Francisco, it has obviously changed a lot since I was a kid. But I think sometimes we underestimate the sort of, I don't know if rebellious is the right term, but there's a counterculture component to the city that has always been there. And it's taken different forms, right? I don't know if it was inevitable, but my sense is given the locus of the technology industry being here, a kind of orientation towards creativity, it doesn't surprise me that artificial intelligence first took off in the Bay Area. How do you think about the relationship between
[0:25:35] Anthropic and the city, or maybe more if you want to generalize it, like companies that are here in our city. Are there responsibilities? How do you approach that? I think what's so interesting is that as natives, Dario and I never had a question of where we would start. Anthropic, right? We've always wanted to be in the city. It's home, right? I'm thinking of friends who don't work in technology who I grew up with. Of course, there's this sort of tension of like, oh, the old San Francisco, the old timers, and these tech folks came in, they ruined everything. And I think like...
[0:26:04] Just like kind of any industry, and I'm not a New Yorker, but I imagine financial services and old-time New Yorkers probably have reckoned with this as well. I think there's common ground that can be found on both sides, right? And there are parts of San Francisco that I spend time in, and I was like, it feels like nothing has changed, right? Like from sort of the early 2000s or the late 90s, it feels like I could have kind of gone back in time. Maybe people have iPhones now.
[0:26:27] But I think there's a healthy tension that exists in some ways, right? There's accountability that the non-tech residents of San Francisco kind of put on
[0:26:36] The technology companies that I don't necessarily think is bad, right? They're like, hey, we're providing a home for you. We just want you to be good citizens, right? We want you to show up, care about the city that you're founded in. We want you to engage in politics in like a healthy, productive, constructive way. We want you to care about the integrity of downtown. And I think there's like a lot more common ground. And I've actually felt maybe this is in my head, but.
[0:26:58] Over the course of the past few years, in particular post-pandemic, there's been a lot more mutual understanding that I think has happened between what I'm describing as kind of old-time San Francisco and tech. I hope to see more of that. I think of Anthropic as like we're like the hometown team. We grew up here. San Francisco is our home. It'll always be our home. And I think there's something very special about being able to get to do what we do in the city we're from. All right, let's shift gears because you mentioned a couple of times like you're not.
[0:27:23] You know, technical background, you went to school for literature. This is like my favorite topic because I was a French major and, you know, now with my partners to help run an investment firm, which I love that story in terms of being a generalist and figuring things out. How did you do that path? Like you went to school for music, right? You played the flute in college, which is really good. Do you still play the flute, by the way? You know, I haven't recently. I still go to the symphony. I like love to. A lot of my best friends are actually still in music, but I have not played flute recently. Do you use your music brain at work?
[0:27:49] I do. I actually think there is a set of skills that you learn around preparation, performance.
[0:27:57] And so I think the concept of like collaboration and understanding where you fit in the larger orchestra and sort of like the notes that you're supposed to play and kind of your awareness of your own role, but also your awareness of like the entirety of the orchestra. I think about that a lot from a team perspective. And also I think in building the leadership team, I think a lot about like, what is everybody's instrument, right? Like what is the position that they play? Not just like, is this the best, you know, oboist, but is this oboist going to like...
[0:28:24] Yeah. Yeah. Yeah.
[0:28:47] Who are the people that are actually solving the problems? What are the problems that need to be solved? How do we take something that's very abstract and really break it down into practical steps? How do you show up for your users? I think the empathy piece is just incredibly important because everybody that is encountering AI, maybe not everybody, but close to everybody is experiencing a combination of like two conflicting emotions.
[0:29:08] One is excitement. If you've ever watched these models, to me, it feels like very similar to watching a person learn, right? You're like, this is incredible. I was like, Claude, build me a website. And Claude just goes and does it. I'm not a developer. I don't know how to build a website. That's incredibly exciting. And then the second is fear. There's a component of anxiety. What is this going to mean, not just for my business, but maybe for my kids? A question I'm asked in meetings with CEOs of the Fortune 500 more often than you would expect is, what should I tell my kid to major in?
[0:29:37] What do you say? I say it doesn't matter so much what they major in. It matters how they treat the people that they work with and the people they're encountering at school. Because I continue to think that the thing AI really can't do is interact with humans the way that humans do. The human relationship, the ability to read people, the ability to work well with others, that is something that we look for more than ever in the employees that we bring into Anthropic. Because I think that empathy, that ability to work well with other people.
[0:30:04] to read the room is going to be more and more important as the technology advances. Do you have a reliable way of screening for that? We have a culture interview that we have perfected over the five years that Anthropic has been... Perfected? Yes, yes, has been in existence. But, you know, we really look for a variety of different characteristics, right? We look for mission alignment, right? So they're here because they care about the public.
[0:30:24] We look for integrity. Have they made difficult decisions in their life to stand up for their values, whatever those are, for things they believe in? We look for collaboration, the ability to work well with other people. Those are just a few. I don't want to give all the interview topics away. I think those are not necessarily things that you would expect.
[0:30:43] To see in an interview at a company like Anthropic, but to us, the integrity of people who work here, their ability to be able to partner well and work through tough topics, that's sort of what we specialize in. And so I think the ability for individuals to be able to do that well is going to be more important worldwide. Is that how you're, I mean, again, not a developer, not a technical background, you're managing a lot of people, that's how they came up. Is that a language translation issue that you have a lot or is that overstated?
[0:31:10] I really feel like I could not be more fortunate in the people that I chose to co-found Anthropic with. I mean, I truly think, you know, over the course of the past five years, it's been like sort of miraculous to just watch how the seven of us and other early employees, like just how aligned we are in our commitment to the mission, right? I think everybody who founded Anthropic, who came to Anthropic early, it was because of this clear North Star. This idea that there are real risks.
[0:31:34] to artificial intelligence. We need to mitigate those risks, but that if we're able to do that, the potential upside is almost unbounded. The ability of these models to solve fundamental problems for humans.
[0:31:47] What does hold light and shade mean?
[0:32:10] Hold light and shade is one of our values. And it's really what I was sort of just talking about, right? It's this concept that the technology itself has great risk and great opportunity. And that that is a very complicated, complex thing to hold, right? There are organizations and businesses that are sort of centered around.
[0:32:27] We view ourselves as stewards of ensuring that that doesn't happen.
[0:32:48] And we have to consider and talk about all of the risks, all the things that could go wrong, while also considering, thinking about, and building towards a world where all of the things go right. There's just a very unusual orientation of any company. It's complex. It's nuanced. It comes up in a lot of decisions we have to make, right? We think about the power and promise of the technology, but also the downsides. Yeah, you're talking about culture in a lot of ways. Everybody's going to tell you that they have a great culture. We think we have a great culture. I think we're all stewards of our culture at Sixth Street.
[0:33:17] There's one of the stewards of the culture, like to really make it concrete and live in the world. That's very hard. How do you think about that? You know, I think that culture is a few things. It's things you say, but it's also things you do, right? It's actions. It's what behaviors are quietly rewarded or sort of quietly not rewarded. And I think something that feels the most important to me about our culture at Anthropic is this concept of integrity, right? We pull.
[0:33:40] Thank you so much.
[0:34:07] All of these things are actual behaviors that you can observe and reinforce, right? You have to talk about them, you have to write them down, but they also have to be baked into the processes for like how we exist with each other, right? To me, low politics just means like having uncomfortable conversations.
[0:34:20] Like a lot of politics is like, I don't want to have this difficult conversation. I'm going to go behind your back, talk to somebody else about it. We have no tolerance for that. If you have something to say, you can find a way to say it respectfully to your colleagues. And I think we work through issues extremely well because it feels like we have to talk about it. Like you said, everything that you're doing is difficult issues. So you have to model like respectful debate where you get along, but you're very direct.
[0:34:41] How do you model that? Like you're doing that at the top of the firm and so everybody sees that or? Yeah, I would say within the leadership team, that's absolutely how we communicate with each other. I have never felt anything than like 100% respect between.
[0:34:53] The leadership of the company. So I think everybody respects each other immensely. But what that means is we're able to raise tough things and say, I actually don't think this is the right decision. Can we talk through how we got to this decision? I don't think it's right. Let's talk about it. There's a flip side to that, which is like sometimes we take longer to do things because we really want to get to the right answer. But I think for us, being able to model those values to the rest of the company is really important. And I think Dario and I also really aim to have a lot of transparency, right, to the degree that we can.
[0:35:20] We have this concept of notebooks in Slack. And they're basically just like an open forum where like Dario and me, but really the entire leadership team, anybody at the company can make one. Just things we're thinking about, things on our mind. So, you know, I post about things related to culture, related to decision making, related to the models. We talk about them. People can comment on them. People can ask about them at an all hands. And I think it's just really important that we show employees like.
[0:35:42] We ourselves don't have all the answers. We don't know. We're all walking into this very uncertain future together. We're going to do that better if we hear from people and if we get more opinions early in the process to be able to make better decisions. I love the idea that the culture doesn't stay the same. Is there a tenet or a principle that you jettisoned at some point? I don't necessarily think I would say we like jettisoned something. I almost think if you think of like a person, if you think of yourself like 20 years ago, would you be like, was there a value that I jettisoned? You might be like, well.
[0:36:12] I think maybe my thinking evolved on how to do something, right? And I think companies are a little bit like people that way where the DNA sort of is what it is, right? Like probably if you looked at yourself 20 years or when you were a kid, you'd probably say like, I recognize that person. It's like I have little kids and I was like, wow, like I probably would recognize my kid 20 years from now. There's some qualities that are probably going to be the same, but their approach to...
[0:36:39] Living those values changes based on the experiences they have. And I think Anthropic has gone through evolutions like that. That's cool. Right? We've said like, okay, holding light and shade before we had a product looks really different than holding light and shade when you serve the Fortune 500. Sure. And so I think really how we've approached challenging situations has just evolved to meet the moment that we're in. Okay. The industry is crazy. Your life must be bananas. You've got to be thoughtful and very intentional about your time. How do you do that?
[0:37:06] I love the idea that I have a perfect formula figured out. It's an evolving process. Of course, yeah, yeah. There's a couple things I would say here. I think the first is it has taken some work for me as someone who's like an operator, an executor. I like to be busy all the time. Oh, interesting. To imagine this concept of like...
[0:37:23] Oh, yeah, yeah.
[0:37:49] Balancing Act, because of course you're missing out on time that you're spending with people in the company or externally. But I think, you know, as much as possible having breaks and sometimes we've even experimented with like no meeting weeks where we've said, look, of course we need to coordinate. There's so much that needs to happen. But for some of the executives, like the ability to just like step back, right? We have hack weeks for developers where we build new things. We're outside of the day-to-day sort of like hustle and bustle. I think there's something important to this concept of sort of building space. And then I think on the personal front, it's like,
[0:38:18] I truly believe that doing a job like this is a marathon. It's not a sprint. And you have to find a way to do it sustainably, right? I have two little kids at home, friends and family. I'm a well-rounded person who likes to do things outside of work. I don't have that much time to do that many things outside of work. But I have to exercise in the morning. I have to get enough sleep, right? Am I perfect about it? Of course not. But I think having worked in the technology industry for almost 15 years now, I've always worked at high-growth technology companies. I've always worked at startups.
[0:38:46] They're always moving 100,000 miles a minute. And there is a little more room, at least psychologically, than I think you can think in your worst moments. To say, actually, half an hour for a jog can make your entire day better. And missing out on that half an hour of meetings is worth it to have a little bit of time to just like.
[0:39:03] Have some space. And I think it's especially important for an industry that can trend insular, right? In the technology industry, we can forget about the world outside of tech. It's important to me that I have relationships from people before my life in tech, right? Some of my closest friends are, like I said, musicians, artists, writers, and being able to talk to them, like, how is this impacting you? How do you feel about the technology? It's not a perfect way of relating to everyone in the world, but I think...
[0:39:29] Having a wider perspective and thinking about how this is impacting real people's lives, that makes me better at my job. And that's a good investment of time. 100%. That's great. We started about talking about the library. What are you reading or what would you, like if you wanted me to pull a book off the shelf and I'll return it, but what would you recommend? Hmm.
[0:39:47] You know, it's funny. I read a lot of science fiction. I read a lot of history. I don't know why those two things are sort of like interesting to me. Just off the cuff, have you read The Guns of August? Yeah. About World War I? Yeah, of course. The Guns of August, I don't know why, feels... It's an incredible book. Incredible book. And I think just...
[0:40:02] The intersection of like the personal experience of people who were sort of thrust into leadership in this very tumultuous time. And then just like the massive impact that their decisions made on an entire continent full of people. That's an incredible call out, that book, because it's these systems that were set up. Why? And then the buttons were pushed and then it just ground millions of people into dust. It's crazy. What an interesting thing to say.
[0:40:30] And it wasn't intentional, right? It was like you looked at, and I mean, that's what I think she does so masterfully, is like you look at every decision.
[0:40:36] Every individual slight, every miscommunication. And you think like, if it had just gone like a, like, was this inevitable? Maybe, maybe if this, you know, the Duke hadn't been assassinated, right? Like maybe things would have gone differently, but was there sort of this pull that like there was going to be a conflict and it was just on the turn? I don't know. But just like feeling the weight of the responsibility of the people that were in those situations, like as individuals, and then just the massive impact that their decisions had.
[0:41:04] I think we can learn a lot from history. And I think the more we study history, like the better decisions we make. And so many things that sort of came out of that and later wars, right? Like we talked about the constitution is trained with the UN Declaration of Human Rights. Where did that come from? It came from extremely painful lessons that humanity had to learn. That's probably the book I would pick to sort of say.
[0:41:26] I think everyone, World War I, not as talked about sometimes as World War II, but I think many salient lessons to be learned. I agree with you. We're going to end it there because we're not going to do better than that. Thank you. Danielle, thanks. Amazing. It was a pleasure. Thank you so much. That was Daniela Amode, the co-founder and president of Anthropic. Thanks once again to Daniela and Anthropic for hosting us at their downtown San Francisco headquarters. I enjoyed the wide-ranging conversation at this very interesting point in time. Thanks for listening.
[0:42:01] You can read more about our guests on 6street.com and subscribe wherever you get your podcasts. If you enjoyed today's podcast, please share it and follow us at 6streetnews on X for more news on the show and our firm. Thanks to 6th Street's production team, Catherine Johnson, Patrick Clifford, Sophia Rose, and Nick Canepa. Our theme song is It's Not Magic, an original creation by Patrick Dyer Wolf. Once again, I'm David Stiepelman. Thanks for listening.
[0:42:30] The views expressed in this podcast are not necessarily those of Sixth Street and Sixth Street is not providing any investing, financial, economic, legal, accounting or tax advice or recommendations in this podcast. Please see additional disclosures on our website for more details.