00:27:14 · Alex Rampell
[00:27:14] S1: Yeah. And maybe talk about the future of where where things go. Because on the one hand, I can imagine a world where it's like, one of these days, GEICO's gonna get a little bit smarter, and they're probably going to... Like, you see, their deny deny deny plan. That's how they got smart before. Right? Because they realize it is an adversarial system. Like, you know, I lost my house in a fire, and I'm going to claim I had a Picasso in there. And then they're gonna think that I'm claiming that I have a Picasso. They're just gonna deny the claim. Deny. Deny. So each party is kind of fighting each other, but they're going to get superpowers. I mean, you see this playing out a little bit with Muse and all the consumer agents where I want a reservation at this restaurant that's impossible to get, and they have a human answering the phone. I can DDoS them now that I have to pay 1p per hour or something. And then eventually, they're going to realize that they're getting DDoSed, and they're gonna prevent that. So, you know, I guess, on the one hand, like, how do you think about, you know, your your adversaries here? Not not your adversaries, but, like, your clients' adversaries. How are they adapting to a world where it's like, you know, it was great for GEICO where they could say, hey. You have $2,000 of damages. The consumer's like, yeah. I did have maybe $2,500 of damages, but it's like they never really had to worry about that before because of the quantum. And now, unfortunately for them, but fortunately for the Davids of the world, like people that are actually aggrieved and and have been victims, now they can fight back, and you're powering that. So that's kind of one thing. But, also, you mentioned long horizon agents because, you know, what does the practice of law look like when a lot of the stuff can actually be done by AI? You had... You... I think you you framed it as, like, the the attorneys are almost like the data scientists of the future. But, you know, maybe talk about, like, what does the adversary or the adversarial process look like? You know, what what what are the the skate farms and geikos using potentially as a result of you entering the scene? But, also, like, how... Big, big question.
00:29:12 · Alex Rampell
But how does law evolve and emerge just given that you're kind of manipulating words and finding facts and doing all this kind of stuff, or like the humans are not as important? They obviously have an important role of shepherding the case to completion, but like what does the AI do versus not do?
00:29:29 · Jay Madheswaran
[00:29:29] S0: Yeah. I mean, ultimately, my my framework for thinking about this is ultimately when you have an individual, they're gonna need representation. Whether that representation, like who does the work on the representation, you can assume it's 99% AI, maybe 99.9% AI. There's always going to be that little bit that is the human touch. And we do believe that people are going to make a positive difference to the outcomes of the case, and that is exactly what you have. So what do you have on the defense side, or really institution side, is what's always happened, which is they have more resources, they have more money, they have more time, which is actually another weapon they have, which is quite powerful, when individuals are in debt to pay their fees, and that is a very powerful tool they have. And that is the strengths they're working with, and they're trying to rely on centralization and standardization. On the defense side, you have a attorney that is fighting your case, and pushing them to get to litigation. And I think that is going to be what happens. I think a lot more cases are going to have teeth, and all the routine back and forths, I think is going to happen through agents talking to agents. It's a crazy future world, but I think that's where we're headed to. And the difference maker is, what does the attorney understand about that client, that set of facts, and their local environment of who they're going up against locally in that defense firm, and they're using that insight to make a difference for their client. And I don't think that ever goes away. It's in fact something we're seeing already, where many customers on Eve are actually choosing to spend more time on their trial work, because it actually enables that. Previously, going into trial took down your entire firm. Suddenly, you're just spending all your time doing trial prep, interviewing juries.
00:31:29 · Alex Rampell, Jay Madheswaran
[00:31:29] S1: You want things to settle. Exactly. It's more of a settlement motion. [00:31:32] S0: That's exactly right. And instead, I think things are going more into real advocacy. How do I actually make our point known? How do I... You know, my client is against back of the wall. They're doing bad things. They're doing good things. How do I represent them in what actually matters for them?
00:31:49 · Alex Rampell
[00:31:49] S1: Well, I imagine this is kind of the data science side of what you're doing as well with this giant dataset that's probably never been accumulated before. Because as you mentioned, all these things... It's so bespoke. There's no, like, communal repository for, like, all of the settlement amounts. But, like, I've seen this with litigation finance a little bit, where if I'm a lawyer, if I'm a trial attorney, and I'm not getting paid by the hour, by you, my client, well, where do I pay myself and my staff and my office rent and everything else? Well, there are companies that will show up and say, I will fund this case. That's right. Right? And I'm funding this case because I'm counting on you winning it. And, like, they'll do all sorts of clever things like, here's the judge and here's this. Like, they're using data. So outside of... I I think those guys have been very data science forward. But, historically, like, this data just, like, never really lived anywhere. And now that it does, you can make smarter decisions as an attorney. I'm like, do I take it to trial, or do I accept the settlement, or do I push back? Oh, GEICO offered me $12,000. Should I push back and fight for 15? Should I take it to trial and try to win a 100? Like, how do I make those decisions? That's exactly right. Which is why
00:32:56 · Jay Madheswaran, Alex Rampell
[00:32:56] S0: we can help them make the best decision in every single case, and know when an optimal outcome has been achieved. And it's still, I would say, it's still the attorney's responsibility to push it even further. And I think that is what I meant by data science like work, because they're using the power of software to do work you never even thought to do, to improve the outcome. [00:33:16] S1: And I mean, where do [00:33:17] S0: you... [00:33:17] S1: This is a very broad question, of course, but like, where does the legal system go? I was having some some trouble with Wells Fargo. And I'm like, you know what? I've tried, like, for four hours to do this. I'm just going to sue them. So I went to Codex, know, ChatGPT. I was like, sue Wells Fargo. Four hours later, it had sued Wells Fargo. It actually found a process server. I got the notice of cert... Like, we're going to court, but, you know, the date is in February. Like, another kind of similar vein is happening with patent law, where before it's so much work to go file a patent. Now it's less work to file a patent, but you still have the USPTO, which is the bottleneck. So I guess, I mean, if you were to prognosticate, like, where does the legal industry go now that AI is becoming table stakes and you're delivering... You're part of that table, obviously, for plaintiff law. But if you think about the entire practice of law in general, how does it change if you were to fast forward five years? What does it