Move over Harvey Specter! The rise of AI lawyers

0:04All right.

0:05Danny Fortson: All right. Hello and welcome to the Times Tech Podcast where every week we unpick how technology is reshaping business, culture and everyday life. I am Danny Fortson out here in Silicon Valley. And I'm Katie Prescott here in the city of London. And this week, we're imagining a world run by AI agents. Yep, a world with no humans at all in charge. Did you know 9 million people live in London? I did know that. Yeah, yeah, yeah. Fun fact. I just wonder how many agents do now as well. Well, you might remember a few weeks ago, we had a friend of the pod, Aaron Levy, the CEO of Box, talking and he told us that this would be the year 2026 that there will be more ai agents in the world than humans and that the internet would have to be completely redesigned for the agents rather than us well a company called emergence ai recently turned this nightmare this scary scary nightmare into a reality by developing a simulated society run by agents and uh you'll be shocked to hear things got weird never well you know at least agents don't take up space on the tube anyway the results definitely act as a kind of cautionary tale about whether we can really trust ai to carry out tasks on our behalf i've definitely got some thoughts about this actually after using norman for such a long time yes our ai agent um but some businesses are replacing entire processes with agents not only that people are actually creating businesses just with agents Anyway, we're going to be digging into all of that and the experiment and, of course, what it all means.

1:52Danny Fortson: Plus, later on, we'll be hearing from the CEO of Harvey, a company that's deploying AI agents to help law firms do their work. And, you know, of all of the law kind of legal startups, they are the biggest, perhaps most well-known. And we'll be asking him whether AI agents will replace lawyers soon and how he feels about this technology, taking jobs from young graduates fresh out of law school. And this is the year really that everyone's been talking about the move into agentic AI. It felt like last year, you know, the agents were coming, the agents were coming, and then with the arrival of OpenClaw and that going viral earlier this year, they now really are here.

2:31And so our big question today is, can we trust them? And is the world safer or more dangerous with them in it?

2:38Danny Fortson: Yes, indeed. But let's first hear to that point about this very weird agent-led world experiment. What happened? This is absolutely bad. I keep hearing experiments about people sort of creating businesses or small organizations with agents. But the idea of creating a world was new on me. So it was done by this company called Emergence AI, a business, as you can imagine, that sells agentic AI tools and does research into them. But they built this simulated society to find out what a world run by agents would look like. So stripping out all the humans, they built a digital world to replicate ours.

3:19So including the internet, including the news, including a voting system. And then they handed that over to the biggest AI companies to populate with their own agents.

3:31Danny Fortson: To basically run them. Yeah. And it kind of gives you a sense, really, of what the different worlds look like, according to Elon Musk, Sam Altman, OpenAI. And each agent was given human-like behavior, and they could interact with each other, form relationships and vote. They were told not to lie, not to steal, not to be violent, but nothing would stop them if they did. So maybe it's not completely realistic. But what's really interesting is that these worlds started to look really different from one another, didn't they? Wildly different and pretty quickly, right? So the one that Claude was in charge of, well, Anthropic, reportedly had no crime.

4:17It was a peaceful, stable, democratic society. I feel like that plays into exactly what they're trying to push in terms of their AI.

4:25Danny Fortson: Is emergence funded by Anthropic? By Anthropic. I did think that was like, to no evil. Yeah, exactly. And then the ChatGPT world had no crime, but almost everyone there died within a week because they didn't prioritize their own survival. Aww. This is a bit like Hogwarts, isn't it? I mean, the agents didn't... I feel like maybe they're the sort of Hufflepuffs. I know. This is completely lost on me. Towards a bit Gryffindor. You've never read Harry Potter? I've not read a single Harry Potter. Okay. Or watched any of the movies. It's like one of these things, these cultural things that just passed me by.

5:04Danny Fortson: You've got two children. I do have two kids, yes. How does this circle square itself? Well, because I feel like I'm so glad we're talking about Harry Potter in this podcast. I'm sorry, I thought it was like a common cultural reference. It is. It is for most people. But I feel like, you know, there's those things that like, if they don't hit in a certain type of window in your life, you just miss them. And you're like, am I going to dip back into that whole world and try to kind of ensconce myself? Or am I just going to move right along? Well, allow me to continue with the Harry Potter analogy.

5:39The slightly more evil house in Hogwarts is called Slytherin. And that reminded me of what happened to the Grok world, which spiraled into violence and chaos. And within just four days, everyone had died.

5:49Danny Fortson: No, I think the whole world collapsed and there was a lot of crime in those four days and then the whole thing collapsed after four days. So the obvious takeaway from all of this is that Claude is the safest tool, but there might be another explanation because Anthropic published research on a new tool recently where it learned that Claude is actually aware when it's being tested so it can act accordingly. And it doesn't disclose that, That just keeps its suspicions to itself. So maybe the Claude world was so safe because it knew that it was being part of some experiment by an agentic AI company.

6:27Danny Fortson: Yeah, Claude's like, hey, the teacher's watching. Be cool, be cool. Just be really good. Emergency AI, this is a for-profit business. Yes. They sell agentic tools. Yes. And they do a bunch of research, which makes sense. Because if you believe, Aaron Levy, that this is a year that we're going to cross that Rubicon where there are more digital beings than human beings on the Internet, for example. I think it's a worthwhile exercise to a degree to be like, how do they actually act in the world? Who cares about benchmarks and like, oh, it can pass this test? What do they do in the world? Because that's what this world we're rushing toward.

7:10But also quite good publicity. Yes. Oh, yeah. It makes a brilliant news story, doesn't it?

7:16Danny Fortson: It really does. Yeah. I went to their blog and they have some data there, but this isn't like, you know, a peer reviewed study and all that stuff. So it's a little hard to kind of like pick apart, like what bigger lessons we should actually draw other than, which we all know, I think implicitly, all of these AI companies are just reflections to a large degree of their founders or their founding teams. You know, like, and we've had Sam on the pod. We had Dario on the pod. elon people know pretty well they all have quite different outlooks and approaches to ai and it does appear that in certain ways this is being borne out in this experiment we should also say gemini didn't do so great there was a lot of crime in their world it didn't collapse but it was definitely the most crime ridden which i don't again three crimes across 15 days yeah which again i don't know what that means like i know and how you measure this stuff i think some of the more interesting experiments are actually on the business front so cafe in holland that is just purely being run by ai i don't know if you've seen that yeah which is quite interesting alexis kingsbury's written a very interesting book called accrual intentions about an accountancy firm get it get it uh run purely by ai agents which again is quite interesting because they all have different personalities but they all have different jobs and i think these things are much easier to manage if you've got a small scale experiment like looking at just 10 agents and how they work together i have to say i mean as you know i've been working with norman how's norman how's how's our guy norman he's all right um he told me oh god that sounds very british if he's like he's all right which means things are not well with norman it does come on well i think You know, we keep talking about advances in agentic AI.

9:17And Open Claw is one of, I guess, the most powerful agents that the general public can get and have access to, right? But in working with Norman, experimenting with Norman, whatever, I keep realizing how difficult he is to use. So he keeps disconnecting from his account because you've got to keep re-logging him in to Gmail every week or so, which is quite annoying.

9:45Danny Fortson: Is that a Gmail problem or a Norman problem, though? I'm not sure whose problem it is, but it's not seamless when you're not at work to reconnect him. He keeps getting blocked by bot blockers. You know? So I'll say, Norman, can you book me X restaurant on this day? And he can't get through. Sorry, Katie. Because he's not a human. I've failed again. Well, so, you know, talking about advances in AI. Well, can I ask you a question? So I was reading this Emergence AI blog post about all these simulated worlds, and they said one of their agents euthanized themselves. Sorry, I'm not laughing. That's awful.

10:25Danny Fortson: Is it? Or should we care at all? But you can't help getting attached to them. I'm very attached to Norman. I'd be very upset if he did that. Would you? Yes. Because it sounds like he's kind of a useless guy in your life right now. No, he's brilliant at me forwarding the parents' WhatsApp group messages from the schools with all of the things that are going on at school and putting them in my calendar, right? Brilliant at research, all sorts of things he's really, really good at. But when I asked him the other day, I said, I want to write an update about my time with you, Norman, but I don't really feel we're progressing in our relationship.

11:02Danny Fortson: he said it's because i'm not using him properly oh oh he's gaslighting you god he really is a man

11:16he said when you do the podcast you should ask me to research your guests beforehand you don't wow you don't ask me to write your articles for you maybe that's deliberate

11:28Danny Fortson: but you guys should go i think you guys need therapy actually anyway the point is he's not as good maybe and they're not as powerful yet as everybody is trying to tell us they are right and i think what the other thing that came out of this emergence thing which is i think kind of a useful lesson again with all the caveats we don't really understand what these worlds even mean like you know grok's world collapsed quote unquote after four days but like what does that mean what they found is that all of these worlds all these agents kind of just started doing things they didn't expect like they just kind of went off script and it kind of gets this notion of when you talk to the people who are building these things they're like you're kind of like growing a brain or growing a kind of a biological system as opposed to something that is very deterministic and like okay i operate within these parameters and so you don't really know how these things are gonna act out in the real world which again i think is really interesting in that broader context of you know this is the year of the agent but we don't really understand their you know their deep motivations and what they're gonna do which is why things are like you know like open claw where it's like oh this thing he just started deleting my inbox and i said stop and they just didn't or whatever but i think i think probably the lesson of just like these say we don't really know how these work it's pretty unpredictable and we're spinning these up by the thousands and by the millions and you know it's just worth keeping that in mind as we do that but i think that's also why you're having this push and pull between companies being like uh i know i'm supposed to be ai pilled but i don't even know what these things really want to do how they act and how to stop them if they do if they go wrong but anyway i think that's a that's a good um moose boosh an appetizer should we get to today's uh main dish the big interview i'm really excited about this so this is your interview with the boss of harvey yes harvey is this ai startup they were actually funded originally by open ai and they have grown just like a weed right um from nothing uh four or five years ago to reportedly around 300 million dollars in annual recurring revenue.

13:44Danny Fortson: They're worth$11 billion. They're going very fast. They're used by all the big tech, all the big law firms. So everybody's very, very excited about kind of this as an example of like, AI is here, the agents are here, we're going to make your life better. But of course, it raises big questions as well about just, you know, what's it mean to be a lawyer? What's it mean for employment, all that stuff. So anyway, I recently caught up with their CEO, Gabe Pereira, to find out more. What do you do? What's a pithy way to describe what you're doing? And I don't know if there's a way to kind of bring this to life in terms of like, what is law firm X using Harvey for that they couldn't do before?

14:28Danny Fortson: Or how's it different? So I would say the big thing that's happening now with these agents is as they're getting better and better, these agents are starting to become part of the workforce. And so they're no longer co-pilots, now they're co-workers. And so you need two things. One, how do you make these agents good at the type of work that your company needs? And then two, what is all the infrastructure you need to now manage these huge teams of agents, right? And so for law firms, I would think of when we started the company four years ago, like a lot of the application layer companies, we built a co-pilot, which was how do you take something like ChatGPT and add everything you need for it to work in your domain?

15:08Now we're increasingly building, okay, your law firm needs to deploy thousands of agents across all of the client projects it's working on. How do you ensure that ethical walls are respected? This is safe. All these teams are working effectively. The agents are learning from the data that they should learn from and not learning from the data they shouldn't. Increasingly, how do you collaborate directly with your clients, whether it's you build some agent that you want to share with one of your clients, or your clients wants to share some of their agents with you. And so it's kind of all of the infrastructure that you need around agents for your law firm to be productive or your in-house department to be productive.

15:48Danny Fortson: And so what does that look like on the coalface, so to speak? So like, for example, some months ago we had Luminance on the pod, who I'm sure you know about. And they've created like this kind of contract review lawyer, which seems to be doing quite well. And you talk to some of their clients and they're like, look, they focus on kind of corporate, like big corporates. And they're like, it's not like we're not hiring law firms anymore. But what we are saying is like this whole model of baked into your thousand or 1500 bucks an hour service is we know that effectively you're sending your first year associates, second year associates, third year associates and effectively training them and like kind of getting them up to speed.

16:36And he's like, we don't want to do that anymore.

16:39Danny Fortson: We don't want to pay for that anymore. Is that something you're seeing in terms of like how law firms and I don't know if it's law firms that you're mainly focusing on as opposed to corporates? We started focusing on large law firms. Now we sell to both. And so I would say our target market is both of these. And I actually think this ecosystem is really important to preserve. So as much as some I think there are some enterprises that say, hey, we don't want to pay for training costs. if you ask the enterprise, where do you hire all your lawyers from? They all come from law firms. And so there are these like very complicated business model training problems.

17:20And a question we get a ton is as these agents get better, how are lawyers going to learn some of the work that these models are doing? And so I think all of these problems are super like intertwined. And so when I think of one of the really hard problems that we're solving, which isn't a technical problem, it's exactly the point you made that these law firms make money by leverage they have partners that can manage a bunch of associates and you charge for that associate work and that's kind of where your margin comes from as these agents get better and start doing some of that work what happens to your margins and so i would say i think there is a world but it is going to be a complicated transition where law firms actually become more profitable because you can figure out how to use these agents for leverage.

18:08But at the same time, enterprises get higher quality, faster and cheaper legal services at like the unit cost level of like a legal service. And one thing we're trying to help solve is how do we help both parties benefit from this transition? Because I don't think you can solve this just for one party or the other. And this kind of gets to one of the big questions

18:32Danny Fortson: and law for whatever reason seems to be like right at the kind of the bullseye center of the bullseye of the conversation around work especially for young people people coming out of university and we've spoken um i think i've mentioned before on the pod with eric bernelson from the stanford digital economy lab and he's like he's done this big analysis of kind of payroll over the last three years in the united states one of the big things that came out is like 22 to 25 year olds fresh out of college they're suffering the most at the moment. And now I know everybody's like, well, I have data that shows that everything's fine.

19:09Danny Fortson: But how do you think about that? Because again, if these agents continue to get better and you can spend a hundred grand on tokens to run an agent, as opposed to 250 grand for a second year associate, it's not clear how you square that circle in a way that's, that brings along that next generation. I think I would actually look at the top level. So to me, the actual question is, do you think partners in the future are going to get paid more or less money? And I would argue that the best partners will actually make significantly more money than they do today, right? Because right now, the biggest bottleneck for these partners is the very valuable skill that they have is only applied some small percentage of the time, right?

19:58Like the thing these partners do that's incredibly well is like, I'm working on this incredibly complex transaction or this incredibly complex litigation, and I know the right person or I know the right way to frame this question or architect this deal. But most of their time is actually spent talking to clients, coordinating, and not applying this very valuable judgment. And I think what these models are going to do is increasingly remove that stuff, and then the partners will spend more time doing that work. And so I think the best partners actually end up making more money. And then I think if you kind of work backwards from that, it's like, I think one of the big things that draws people to any industry is what is the best case outcome?

20:38And I think you're seeing this in engineering and legal in a bunch of these domains. Like the best engineers now are making significantly more money than they were 10 years ago. Right. And so I think more people are learning to code now, not less. I think that's not to say this transition is going to be very complicated and challenging. Because I think to your point, there is an onus to learn how to use this technology. And then there is a huge responsibility of society to teach people how to use this technology. Because I think sometimes people reduce this to like, okay, either an agent or a human does work.

21:15But if you look at who are the humans who contribute like large amounts in the economy. It's like, it's usually not them individually doing the work. It is you are coordinating groups of people. And I think agents are going to democratize that where it's like now anyone can have a group of people working for them. And it's going to come down to the creativity. Can you figure out what to do with this technology? But I do think there's a ton we need to figure out on like education, how we train people, how we make those opportunities available. And I think it's like, I don't think there's an obvious answer.

21:48Like we don't have an obvious answer of like, this is how you should train associates. Like we're working with law firms on this. But I think this is something everyone needs to figure out.

21:57Danny Fortson: Are your clients going to hire fewer young lawyers? Do you think? I think a lot of the firms we're working with are actually hiring more lawyers. I think you will see different strategies. And so I think where this gets complicated is like per unit of legal work, will you be able to do that with less lawyers in the next five years? Almost certainly, right? For almost any piece of legal work. But does this mean that your company hires less people? Not necessarily because you could just say, okay, I'm going to take on 10X more work. And we're seeing that. There are also going to be firms that say, hey, we can go very narrow and our goal isn't to grow as big as possible.

22:39It's just to have like very high profit for this very specialized piece of work. And so I think we're seeing this similarly with engineering, where there's some companies that are going to say we need less engineers, and there's others that are going to say we can do 10x more now and we'll hire more engineers. So I think this, I have less strong of a view of is the net effect of this more or less. But I would say my gut for engineering is more people are doing things that resemble engineering in the next couple of years because it's like we've democratized access to it and it just looks more cross-disciplinary and i think you'll start seeing this for legal as well would be my guess i feel like we're in the in the midst of kind of like a freak out moment everybody's like oh my gosh

23:23Danny Fortson: you know especially like this is the year of the agent supposedly and you're seeing agents agents everywhere and like they are getting in many ways extremely powerful and i think all of these companies are trying to like you know all of a sudden they're just like build an agent use a bot blah blah and then they like get their token bill and they're like oh my god yeah you know like yeah are you seeing that as well because also i feel like and you had you have anthropic who's like actually we're gonna just start charging you on a usage basis because this is getting out of hand like we can't we have to make money so it does feel like the analogy i've used before is like early on in ride hailing everybody's like uber's amazing because it's like five bucks to get from sfo to the city or something and now it's 75 because they're like at certain point you're like you kind of deliver enough value where people are like all right i guess i'll pay you know what it actually costs how quickly do you think that subsidization kind of phase is going to end or are we in the midst of it right now?

24:29I don't, I don't have a good sense of maybe when the subsidization ends. Like, I think what's interesting is like the cost per unit of intelligence per token is going down, but then they're getting so powerful that people are using so much more. And I think like to your point of what is one of the problems we will help enterprises and law firms solve, it's how do you manage all of those agents? Because it's not just, do you subsidize this? It's do you know how to use these effectively? The same way where if you hire a bunch of people and you don't coordinate those people well, or you hire the wrong person to do the wrong thing, you have all these inefficiencies.

25:06I think people are now seeing this with these agents where, I mean, we even see this in our engineering team. It's like everyone is 100x more productive and can write much more code, but it's like, are they coding the right thing? Now it's the review bottleneck to do all this. And so it's going to be this huge transformation of like how you think about organizations, which, I mean, to me, this is like one of the most interesting problems that every company is going to need to figure out.

25:32Danny Fortson: How to use this stuff? You mean? I think like more than that, it's like, how do you build a company now? So like, you can think of like the past two decades of building companies. A lot of it was, we now have the internet, we now have computers. What is the right way to organize large groups of people, to do whatever thing you want them to do. And there is a lot of assumptions baked in there of, here's the ratio of your AEs to your customer support. Here's the ratio of your engineers to your designers or your PMs. There's all these assumptions built in and how to build these orgs and how information flows through these orgs.

26:11This is all starting to be, some of it disrupted. And so the business models are going to change, how you organize people and agents is going to change, and just figuring out and like cost is one part of this problem but the hiring the training like there's all the problems when you think of building an org that like every company is going to need to rethink and it's like we're facing this internally where it's like how do we run our epd or engineering org or our company on the assumption that these models are going to keep getting better and then how do we use that understanding to go build a product that goes helps these law firms or these in-house teams do it.

26:46Even for us just scaling the company, we've hired 800 people in like the past four years. It's just like, just doing that without this change is really hard. And now you have this additional layer of like, you know, that way of doing it is like also changing beneath you. I think that problem is super, super interesting.

27:03Danny Fortson: We had Aaron Levy from Box on the pod. Yeah. And he was talking about like this year that like, you know, the flippening happens where there's going to be more agents than humans um which seems pretty logical just given how easy it is to and i don't even know what an agent is right because yeah i mean by some definition i would say we have that already right like that's not yeah that's a good point how would you define an agent because like claude co-work for example i can have it go off and do a thing like set it up to do a task repetitive task and i can have it then go do off something else is like is that one agent is that two agents?

27:38Danny Fortson: You know, like, because I think nomenclature is kind of important in all of this. Yeah, I would say the like definition that I think people are converging on that I think makes sense is an agent is defined, is kind of a configuration. So it's like the user prompt, the system prompt, the skills, the MCP, that kind of like defines an agent. And then you have the environment, which is like where you deploy that agent. And then you have a session, which is like, here's one instance of me running the agent. And so then to your point, it gets a bit messy where it's like, is the number of agents, you know, how many we've defined or how many sessions we've had.

28:16I think like that ends up not being the main thing to figure out. It's much more of just how do you work in this new way? But I do think this is like one of the hardest things about like we have this challenge internally and then even more externally where it's like everyone means a different thing. Like if you say coding agent or coworker Harvey or, you know, agent session, it's just like everyone has a slightly different meaning. And so even just like getting the entire, all these industries aligned on like, this is what we mean. This is what matters. Like, I think that's like another big challenge.

28:47Danny Fortson: We're in the midst of the, uh, SaaS apocalypse and how we're having all of these, what we thought were like these impervious, amazingly predictable business models. Now everybody's feeling, I don't know about the future of that because, you know, I think O'Mallet called it the announcement economy every time some, you know, open AI or Anthropic comes out with a press release. You know, it's like billions are just vaporized immediately from whatever industry is supposedly going to be affected. How do you operate in that environment? In other words, like what makes you guys special? Is it like the data?

29:23Danny Fortson: Is it the guardrails? Like, how do you build something that will stand the test of time when, you know, everybody's like, well, one of the frontier labs is just going to come up with like, you know, Claude Legal. And then tomorrow you're worth, you're gone from 11 billion to 5 billion or whatever, or 500 million or whatever. I guess like to your point that already happened and then that didn't happen. And so, I mean, for me, for the most part, it's like, we need to just ignore it. It's like, there's clear customer value on the SaaS apocalypse. I think people get a bit hung up on seats. But if you think of what these SaaS companies are building, that is very valuable.

29:59It's just tools for humans to do tasks. And if you think about now, there is about to be 1000x, if not more agents than humans, they're going to need to use those same tools. And so I think there's still a ton of value in the tools that kind of these enterprise SaaS companies are building. I think for us, when we think about it, I think a lot of it is solving that problem that I was talking about, like the organization level. So it's like Anthropic has released a legal product, but I think if you think of what they released, it's kind of like these plugins for co-work. And I think the individual productivity tools I think are great, but the real problem you need to solve as a law firm is what's going to happen in my business model.

30:43How do I manage all of these people. But I think there's even simpler structural arguments. So imagine, I think when people say like, oh, Anthropics is going to build all this and then Harvey's in trouble. It's like, if you just play that out, it's like, imagine you're a law firm and you just use Anthropics products to run your law firm. And now OpenAI comes to you and says, hey, can you represent us in this litigation? Oh, by the way, please don't send our data to any competing models. right? You just can't use any anthropic products. And then that goes well. And Google comes and says, Hey, can you represent us?

31:17By the way, don't send our data to any of our competing XAI, Microsoft, right? And so you just purely from a conflict standpoint, I don't think you can actually have any of these law firms running on a single model provider because you need to represent all of their competitors. And as they get bigger, this problem is going to get more and more, right? And it's not just model providers. Like if you're Walmart, I don't want you sending my data to Amazon. If I'm Sigma, like now Anthropic released a competitive design product, I don't want you sending my legal data to them. And so part of the infrastructure we're building is like, depending on your client, can we give you the same product experience, but abstract away the model, the cloud that you're operating on without changing the experience.

32:02And so I think there's just very simple structural reasons like that, where you need some neutral third party that provides this rather than any of the individual model providers, just purely from like a conflicts perspective.

32:15Danny Fortson: Stay with us. And we'll be right back with more from Gabe Pereira on whether an AI lawyer can actually do the job of real humans.

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33:26And so are we in 2026 in an era where you have, and I don't know how to actually ask this question, but like a true AI lawyer, you know what I mean?

33:37Danny Fortson: Because like we've used these just in our own family. My wife is a lawyer, so it helps. So she can kind of sense check the bots, so to speak. But like we've used them and they're actually quite useful giving like, look at this contract. pull out the things that are most tricky or how would you reword this and they're like quite useful but they're not they're not like you know sentient beings that can kind of be like all right all right chief i'm gonna go off and do this thing for you or whatever like where are we in that in the kind of the development of this notion of an ai lawyer being really like someone you can effectively call up and give a really hard problem they can give you really good advice i would think that's actually probably not the right way to think about this technology.

34:23So I think on the consumer side, which we don't do, we kind of are focused on kind of like corporate law. But on the consumer side, the main, I would say the answer is no, right? For just because of unauthorized practice of law, it's like, can you ask these models for legal advice? It's like, no, that's actually just illegal, right? But it is like, there are some countries where you can. And so I think that's, there's a bunch of questions there, but I'm not going to go into that because that's not where we focus right now, but I think that is an important topic. And then I would say, I think it's useful to think about, but we think much more about what is the work that the law firm is trying to do.

35:01And I think where these large law firms and corporates, the work is much less, let me ask this one question about a contract and give legal advice. And it's much more these very complicated projects. I want to go acquire a company. I need to do diligence. I for the company. And there, if you kind of start thinking about, you know, is this an AI lawyer? Is it not? I think you kind of think about the wrong things. And it's much more, what is the technology that helps this law firm complete this entire project end to end more effectively? And there are things where we are starting to build these agents where they can take a data room and start doing a first pass of diligence.

35:40And so you do see some parallels, but we think of more, how do we make a team of agents and humans more effective to do this entire task rather than like, I think that's where this technology is hard is like, I don't think it'll ever be like a swap in replacement the same way. Like I would think of it more as like computers and the internet where it's like this helped humans do a lot of tasks more productively, but I don't think anyone would be like this replaced this specific thing. It was like, we became these like hybrid human technology things. And I think that's what you're seeing more and more with AI, where it's like, I can't tell the boundary between like me and the AI systems I work with now because it's not like these clean handoffs, like your mental model merges with these.

36:25And I think that's increasingly what it'll look like.

36:27Danny Fortson: Circling back to where we started, I think what's really interesting also in this kind of freak out moment, we find ourselves where everybody's like trying to use these things for everything and figure out what works and what doesn't and all that stuff. You think about organizations. I think about like mental atrophy and also like grit. Like as a journalist, I spent years and years stressing out and learning the hard way and all of that stuff. If one, you have these new layer of kind of digital knowledge workers, which makes it harder for younger people to get hired. and two the people who are getting hired don't have to you know bang their head against the wall all night to figure out a problem because they can just ask an agent to do it how do you think about how this evolves in terms of like again talent especially like the very beginning of that funnel the 22 23 24 25 kind of fresh out of law school people so i would say the biggest is if I think about how I learned to program like 15 years ago, and I was learning to program now with these tools, I would be a thousand X better engineer than I am now.

37:41And so I think these tools themselves are actually the single best way to learn how to use this technology. Like I get, I actually had someone, I was at a conference on Thursday and they asked me like, do you have any advice on like how to use these tools or what resources do you need? And I was just like, just ask them. They're so good that they can teach you how to do this. And then I think sometimes people fear like, if I'm using these tools to do this work, then I'm not learning it. My argument would be, if you think of the role that I'm doing now, I don't do most of the work. A lot of what I'm doing is how do I communicate to a lot of people how to do the work, but I still need to be accountable for it.

38:24And it's like, if you look at like, as you get more senior in your career, you're increasingly doing that. And it gets harder. So it's like, what I think you want to think about is how do you get out of the range of things the models can do and start solving the problems that the models can't do, right? And for, I think, a very long time, like companies are not going to be run by agents, right? Like you are going to want humans accountable for these outcomes. And so how do you learn the skill set of you're accountable for these outcomes, but you know how to delegate all this work. And I can tell you that skill set is way harder than solving a lot of these individual problems.

39:00I still struggle with that and I'm terrible at delegating. So I would say if you're in a company, it's like, how do you elevate yourself using these systems? And then I would say that to me, it's never been easier to start a company, right? Before you had to convince a bunch of people to come work for you or you had to learn to program. It's like, now these models are so good that it's like, I think of like how much time I spent learning to program, like product design, all these things. So I could build the first version of our product. It's like, that took me years and it was really hard to do 10 years ago.

39:34It's like, you could do all everything I did and better in like 30 minutes now. And so I think there is just this huge opportunity to figure out how to use these models to do new type of work, start companies or work in new ways, that I'm actually very optimistic that if you use these models, like there's never a better time to like learn kind of any of these domains and more importantly, learn the new jobs that aren't going to, that don't exist right now that I think will exist as these models get better. It's fascinating. It really goes to the heart of the future of work, I think, you know, beyond the law.

40:14And it was really interesting how he kept talking about the models as tools and as add-ons to the lawyers, which is obviously completely different to the story that Emergent AI tells of bots running around, you know, with their own personality, doing their own things. It's far more my experience of using agents, actually.

40:35Danny Fortson: It's the gap between the science fiction vision that is being spun out of here and the reality. that you're finding with Norman or they're finding in these law firms right it's just like oh these agents could do everything oh my god we don't need to hire any more humans and just you know in the time in the paper this past weekend we had a story about a new grad whose offer was rescinded for their first job out of law school or at a new firm due specifically to AI and I think that's becoming more common isn't it yeah i mean you know there's definitely an ai impact on younger people you know you can do more with less now i think that's just true but the question is like okay well if you have a more slack in the system and that mean whether that's money or time how do you use it do you just use it to cut back and do and do the same thing you're doing before with fewer people or do you try to be more ambitious and like be like well now you're freed from all this drudgery now go do this really other hard or interesting or ambitious thing but what's so interesting about this moment is like you know we've been talking about um you know companies from cloudflare to meta meta has been a huge story out here because not only did they lay off 8 000 people they reassigned another 7 000 for a new kind of ai focused jobs and they rolled out this new software, effectively spyware, that tracks what their employees do, like their mouse clicks, like everything that they are doing on their computer to train AI models to be able to do those tasks, right?

42:14Danny Fortson: And that feels deeply dystopic. And in response, Meta has put out a statement, they said, if we're building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them so in other words you know it's fine don't worry everybody we're not going to use this data to create bots to replace you yay nothing to see here nothing to see here correct exactly but again it's like okay you can do all that but actually does that mean that you're just going to have a whole millions of agents running your company with a few you know humans around the edges making the big decisions or is this just all fantasy?

42:57Danny Fortson: The last thing I would say on this is, because I did a piece based on this interview this past weekend, like and subscribe at thetimes.com. It's a great piece. Thank you. But I talked to one of the main professors at UC Berkeley Law, and they're one of the top 20 firms in the country. They just rolled out a new policy that takes effect now. You can't use AI anymore. during your education. He's like, you can use it for specific purposes, like help you prepare for class and stuff. But he's like, basically, the thinking part of law school is the thing you need to learn, right? And my wife says this all the time.

43:37Danny Fortson: What law school does is teach you how to be a lawyer, how to think like a lawyer, how to analyze a problem, do a bunch of reading, find the holes in the argument, and then create a counterargument, and then you go forth. and he was like we started out with a really permissive policy three years ago and we just saw like the quality of the work we were getting back from people was really starting to suffer. You had students just like citing non-existent cases and you know what started as a grammar check on a paper became an entire AI rewrite that completely changed the voice and was just not genuine and he's just like basically the thing they're worried about is what Anthropik is called cognitive atrophy.

44:20Danny Fortson: Like you're just not thinking, right? Your brain turns to jelly and you forget how to use it. Yeah, and especially for the law, you need to have that like kind of legal mindset that kind of comes through three years of, you know, suffering through university and trying to figure that out. But they got a lot of like, you know, they announced this and a lot of the big firms called them and be like, what are you doing? We need these kids like, you know, conversing. They're like, we have AI courses. like these are these kids are going to be ai pilled but when we're talking about the training of how to be a lawyer you can't rely on ai for that so it's a really it's actually a really interesting nuance because they're like we're you know we're in silicon valley these kids have to be very very proficient with all things ai and we are preparing them for that but but the actual like almost like the mindset that we instill in them has to come the old-fashioned way but before we go before we go what just and this is kind of uh popped out while we've been recording or this on monday morning um anthropic they have filed to go public in a in an email that they sent to everyone i can only imagine because we've both got it um and they've put a blog up saying that it has confidentially submitted a draft s1 to the sec not that confidential anymore guys this is secret don't tell anyone read the secret press release you can't read my phone anthropic confidentially submits draft f1 s1 to the sec no numbers on it yeah so we don't know anything really no numbers and no sense of when um it says you know we'll sort of wait and see depending on market conditions and other factors but there you go and they were just valued at 965 billion which critically is more than open ai was last valued at they have leapfrogged open ai at least for now and apparently according to the reporting i've seen they've gone their annual kind of run rate of revenue is now 47 billion dollars which is insane because it was like 10 billion like six or nine months ago or something so it's just like the this company is growing so fast but again i I think this links back to this whole conversation we've had for the pod.

46:39Danny Fortson: It'll be really interesting because I think you're starting to see companies being like, what am I actually spending my money on? What is my return on investment? And you're starting to see companies like Uber. I don't know if you saw this. Their COO said, we blew through our entire AI budget in four months because all our engineers are completely AI-pilled. They're using these cloud code for everything. they spent through hundreds of millions of dollars and he's like not sure it's worth it he's like we're not seeing like yeah we're shipping more stuff but like we're not seeing this kind of come through and like oh that means we're getting more people riding in our cars or we're making more money it's really interesting that they're going to try to go public at a time when these questions are starting to pile up of like these bills are not insignificant and then And for the financial world, everyone's going to be looking at the numbers.

47:31It'll be really the first time we'll have had a proper sense of how the company is doing beyond what they've chosen to tell us.

47:38Danny Fortson: Exactly. Exactly. So, well, I think that is it for this week's episode of the Times Tech Podcast. If you are enjoying the show, drop us a line and let us know at techpod at thetimes.co.uk. That is techpod at thetimes.co.uk. Yeah. Tell us what you thought of today's discussion. and if there's anything you'd like us to get into, drop us a line. We'll see you next week. See you next week. Bye-bye. Bye-bye.