The AI-Native Law Firm, with Ryan Walker of General Legal

Speaker A: Billions of dollars have gone into making incredibly good, incredibly specialized tools for lawyers that are AI driven. What's the impact so far on clients? It's actually been, I would say, pretty limited. And there isn't any obvious indication that, like, efficiency has been introduced nearly at the level that seems obviously possible to me within these firms broadly. Yet I think we are at a moment where that could all be changed.

Speaker B: Hal. I'm Hal Marcus.

Speaker C: And I'm Mei Maangwudiwe.

Speaker B: And this is Meeting of the Minds, the legal AI podcast from evisort.

Speaker C: We interview lawyers, professors, and legal operations pioneers that are, uh, pushing the envelope

Speaker B: leaders, using technology to drive great business outcomes and shape the future of the profession. Avoid.

Speaker C: Howdy. How you doing?

Speaker B: Good, Mamie. Okay, listen, before we go any further, you've got to explain the T shirt.

Speaker C: Well, as you know, I'm a space lawyer on the side, you could say. And I helped found the Space Beach Law Lab, which is an annual event in Long beach, or Space beach, as we call it. And it's a Space beach shirt that has a UFO and says take me to your lawyer, which I absolutely love. And, um, don't wear enough, frankly.

Speaker B: So not enough aliens, I think, have latched onto that. That's how you get things done. All right, that established, let's kick this off. We just had a great conversation today with Ryan Walker. He is the co founder and CEO of General Legal, not to be confused with General Hospital. General Legal is an AI native law firm. And Ryan's also the former CTO at Casetex and was the VP of technology of co counsel at Thomson Reuters after they acquired Casetex. That acquis made some headlines a while back.

Speaker C: Yeah. And we had an excellent conversation. We looked back at this time at Case Text, which is a pivotal time of AI kind of around the, uh, OpenAI coming and hitting the scene, and really talked about his work developing AI for legal research and also dove into his current work building out an AI native law firm and talking about what all this change means for the legal and law firm landscape more generally.

Speaker B: Yeah, we looked back, we looked forward. I don't think I've done quite so much of both in the same conversation in a while. But let's hold ourselves here to journalistic standards for a moment because you have a bit of a connection to this organization.

Speaker C: Yes. One of his co founders, JP Mohler, actually was a student at, uh, Harvard Law School. At the same time, me, Jerry Eversource founding team were students at Harvard Law. There's definitely something in the water around entrepreneurship in those classes back in 2018, 2019. So have that connection for sure.

Speaker B: Yeah, I got to have a really interesting conversation with him over dinner not too long ago. And, uh, entrepreneurialism and acquisitions being on the forefront here as well, we should say. We talk a bit about Thomson Reuters and an acquisition of Casetext. I spent about four to five years of my career at Thomson Reuters after they acquired a company that I had built up for five years as GC and in some other roles as well. So it was really interesting to engage with Ryan about all of this. All right, well, I guess in honor of your T shirt, let's kick it off this way. Countdown. Three, two, one.

Speaker C: Hey, Ryan, great to have you join us today.

Speaker A: Thank you so much. Excited to be here. Meeting of the minds, indeed.

Speaker B: Ryan, you came to this world of legal technology in a slightly unusual way relative to a lot of the folks that we talk to. Background in mathematics. Walk us through what led you down this path.

Speaker A: It is certainly a unique trajectory to come into the LEO space, but it makes sense in the end. I was always fascinated with problems that connected language and math and machine learning in particular. So when I was out kind of looking for what to do next in my career, that was the motivation. It's like, okay, what is the area where language has kind of paramount importance? And obviously the answer is hola. And that's when I met up with Jake Heller, who is the founder and CEO of, uh, Case Tax. And first time I met him, he kind of gave me a tour of the tools and technologies that this was in, like, 2015 that lawyers had to work with. And I just could not believe how far behind, like, kind of consumer tech those experiences were. I was just hooked from there. Legal is just this vitally important function, and in many, many places, deeply kind of deprived of, um, technology, deeply deprived of innovation and investment in innovation that ultimately has a really significant social implication. Most people do not actually get access to quality legal services when they need them, and it just doesn't have to be that way. And I think that was true in 2015, and it's even more true now with the rise of these generative AI techniques that do, in fact, automate so much of the kind of routine parts that are a core of legal practice.

Speaker B: But you went to work in Casetex when you were not at first leveraging generative AI. It really wasn't out there yet. So you went into this with a different approach. Tell us a little bit about how that came about.

Speaker A: Yeah. So when I joined Case Types. Our focus was really on providing a better alternative legal research engine. And we walked through with that product several different iterations of the kind of machine learning technologies that came along. So in 2015, things like recommendation systems were very, very popular in Silicon Valley, where people were doing all kinds of interesting things. So Pablo Arredondo and I came up with the first case law recommendation system. The idea being you could take a brief, upload that brief, and we can look at what was cited in the brief and start recommending cases for you that weren't in the brief, but that you ought to have cited. And that was just such a cool application of the technology that was available at the time. And that was sort of the start of Case Tax, really kind of embracing the latest approaches and bringing them to the legal research front. And then we went through several versions. We were the first legal provider to take the Burk model from Google and apply it both to kind of classification problems. And we built out a citator that was built on top of this much, much more robust approach to classifying, as well as a semantic search engine that, you know, was able to kind of encode the entire case law and offer a new mode of search on top of it. And so I think we made a strong name for ourselves in this space as the folks who could take this technology from the forefront and apply it to legal services and make these solutions that, you know, lawyers really loved. The products that we created at Case Tax, and that kind of put us first in line to receive some of the very cutting edge generative AI models when they first came out. We had early access to the ChatGPT models months before the public launch. And as soon as we saw these, this was like all hands on deck to take this technology and get it into a product that we could deliver to the legal market.

Speaker B: So what was it that enabled you, as at that time, a, uh, considerably smaller entity than a Thompson or a Lexus, to be on the forefront of leveraging that technology? I mean, for example, you mentioned using that tech from Google to classify and all of that. Thompson's approach would have been, well, we have the headnotes. We've been doing this for, what, a century, doing that kind of classification and analysis. So how do you compete with all of that, get access to that early technology when there are bigger players that could be taking advantage of it theoretically faster, and bring it to market in a much broader way?

Speaker A: I think a big part of the answer to that is casetex was always very successful at recruiting excellent Talent, especially in Silicon Valley. I recruited my current co founder in General Legal, Javed, who is both a Harvard JD as well as a absolutely top tier machine learning scientist, who brought him in to really work run with some of these approaches that were out there job and I was always kind of motivated by the same vision that what is happening in Silicon Valley tech companies has to come to legal practice. And so we were very successful at bringing in and retaining over the lifetime of the company, really talented attorneys and really talented engineers. And we were nimble and able to move much, much faster at integrating that technology into our products and building over time, a real name for ourselves in that space. Not just with kind of the engineering community in Silicon Valley, but also with our customers who were the AMLA 200 clients that we delivered these different phases of solutions to them. So it really did make us a natural partner to receive this next iteration.

Speaker C: So much of what you're talking about even reminds me of kind of the early days of the founding team of Eversort taking those cutting edge solutions, bringing them to legal users. I think a lot surprised us because we were law students when we were doing that and kind of seeing where legal was and how they reacted to these technologies. I'm curious, when you were really developing these AI solutions for law firms and delivering those solutions to them, was there anything that surprised you about how they adopted the technologies or used them or reacted to, to them?

Speaker A: Yeah, and I can speak specifically on co counsel and I was convinced, as was, I think everyone at Case Tax from the moment we saw this technology, that the entire world of legal practice was needed to change. I actually thought that change was pretty imminent. I was probably pretty m naive. I believe that this product comes out and now you look at it like billions of dollars have gone into making incredibly good, incredibly specialized tools for lawyers that are AI driven or all now built on this technology. You add that up and it's several billion dollars worth of, um, investment has gone into creating these for lawyers. What's the impact so far on clients? It's actually been, I would say, pretty limited. We actually see a lot of unexpected counterintuitive things happening, like the billable rates going up, not down, law firms still hiring, hiring junior associates, bringing in more attorneys, increasing kind of the sizes of their organizations. And there isn't any obvious indication that like efficiency has been introduced nearly at the level that seems obviously possible to me within these firms broadly yet. And that was really the motivation for us to start general legal. We want to see this transformation happen faster because it really matters. It's consequential and it is about who gets access to good legal service in society and where are the places you can start putting legal services if they're suddenly not such a burden to obtain? I think legal is such a scarcity driven resource, right? We think about it in a way that's like, oh, let's bring it in at the absolute last minute, let's talk to our lawyer only when we absolutely, really, really have to. I think we are at a moment where that could all be changed because now it can be so much more efficient to deliver legal services. And the kinds of things you can do in terms of how people engage lawyers could be very, very different. And that's what we're trying to realize with General legal is a new way of accessing, using, consuming legal services.

Speaker B: So well, we've gotten there quickly, but let's use that opportunity to just delve right in then. What exactly is it, uh, that general legal is doing with the tech? What is it doing with the business model? With the nature of pricing, with recruiting, with the experience of people interacting or not interacting directly with the council? What should they expect? What is your approach to all this?

Speaker A: So we are an AI native law firm. We are building AI systems at the core of all of the processes of the law firm. And those processes allow us to bring in very, very good attorneys and make their practice massively more efficient. And we take those efficiency gains and we turn them into a new service delivery model for clients. The most obvious kind of facets of that are we can flat rate price our services. We are done with the billable hour. In general legal, it is not a practice we will ever adopt. We charge based on the outcomes that we deliver to clients. You know what the price of the service we provide is to you upfront. And that price is typically a fraction of what you would pay a traditional legal service provider. We are fast because of these kind of massive leverage that we can get on these great attorneys. We can turn work around in the same day, often in just a couple of hours, to produce a high quality contract term that has deep expertise embedded into it. And we integrate our offering into the client's workflows more directly. So our lawyers, when you engage general legal, the most common way to do it is you get into a Slack channel with your attorneys and you can pass work back and forth. You could pass contacts back and forth through Slack. We course also have a workflow platform. We also have an MCP service so that your agents can integrate with the Services of uh, the law firm at ah, General Legal. And I think those three things are what really stand out to our clients. We serve businesses all the way from small startups to early stage public companies primarily focused on kind of commercial contracts and real specialty in more complex contracts where there's regulatory overlay. And part of the value of what we do is we have marshaled together these attorneys that have significant practice experience and we're building out the expertise that allows us to give very comprehensive work product contracts. Hopefully you guys agree, like they can implicate many other areas of legal practice. And I think the most common thing we see is like there's always a privacy implication to any SaaS contract and those are becoming increasingly important against both a kind of vast regulatory backdrop as well as companies own internal concerns about how their data will be used. And so being able to embed that privacy service directly into the commercial contract flows is a huge part of the value proposition. We do that seamlessly for the clients. We don't charge you for somebody needing to go like knock on the door of the privacy partner down the hall. You don't get an incremental bill for that. It's all just part of the service that we offer. And it's invisible to you that we're pulling in that expertise, but you see it in the work product.

Speaker B: Wow.

Speaker C: There's so much in that that we could delve into, I guess. First things first. The billable hour has been talked at NAUSE for years, if not decades, about its incoming demise. And we were just talking about how it seems that despite some of these AI technologies, billable hour rates for partners, especially top partners, are only increasing. Do you think that an organization like General Legal will have an effect throughout the broader ecosystem of law firms? Where we might see an actual change is the uh, end of the billable hour, you think actually in a potential future horizon.

Speaker A: I hate to say that out loud because I certainly know the history of people declaring that. And so I'm only going to speak for myself here that General Legal's position will always be to charge based on outcomes and not hours worked. It just doesn't make sense to us and it's not necessary for the work anymore. Part of how you do this, you know, part of how we think about pricing is legal work. You can think of it on a distribution and you can price your services relative to the median of that distribution. You can understand that the tails of some contracts are you going to take a really long time because the counterpart is a pain in the Butt right. Or some contracts are going to be really, really easy. And you can always use that data, calibrate and price in a way that allows you to realize great margins without introducing the uncertainty about what it should cost to your clients. And that's where I think legal work will by and large get there. Maybe there'll be some areas that take a long time. I think litigation is one where it's so hard to understand what that distribution is going to look like. But ultimately it's not up to me. It's up to clients. I think clients are going to be the ones who force this on their service providers. Ultimately, I think it hasn't quite happened yet, but I think the thing that Meta did a couple months ago is a great kind of sign of the mentality here.

Speaker B: Right.

Speaker A: Meta put out the thing about how we're going to redline out anything we think an AI could have done and we're not going to pay that anymore. I think that's the start of real pushback on how firms are pricing their services. And I think you can look at other professional services, uh, industries which were formerly an hourly model and by and large they've been able to do it. Lawyers are smart people. Why can't they get there too? I don't know.

Speaker B: You know, and it could be the flip side. It could be the lawyers are smart people and they've managed to avoid it so well for so long. I mean, on the one hand I'm a purveyor of transformative technology in legal practice and have been now for decades. And so I'm always eternally optimistic at the changing of that model. And, and yet I have seen time and time again the extraordinary resiliency of the legal service model against one kind of radical change after another. So this one, it's hard to look at it and not go something's got to give when you really explore what it can do. But one of the elements of it that I think tends to perpetuate the model. Look, when SAS came along that was going to radically change things. We saw law firms go completely SaaS based. That was going to be so much more efficient and direct than the way that they've been operating previously. That had to lead to efficiencies, more project based pricing, and it did. And a lot of the service providers, including law firms like Venture Law Group. Yeah. Nope, not really. Around AOSPs have come along with high volume models, leveraging technology and smart ways to deliver a lot of outsourced services in a really efficient, scalable well trained way. They've certainly had an impact and they've done all right, but they haven't disrupted the core model in that meaningful of a way. So not to be too contrarian here, but I've got to put the past at your footstep, you know, at your feet here and sort of say, well, what is so different now? Why is it now ripe for disruption that other technological advances haven't really achieved?

Speaker A: It's a great question. And my answer to it is like I look at what we were doing at uh, Case text prior to ChatGPT and after ChatGPT and I say, okay, yeah, we were at the margins, I think, giving lawyers more the opportunity to become more efficient. But ultimately we're still at the margins. This process could be 20% more efficient. This other thing could get cut down, down like by this amount. Um, your legal research flow might take an hour instead of three hours. Right. But fundamentally I think we're talking in a totally different order of magnitude change. And my belief is that the differential between the step change here is so big that it's hard to not believe that in the end the size of that overwhelms these past kind of barriers. I mean, what I would say is now you're thinking about something where 80% of the work is automatable or made much, much more efficient. 90%, 95% in some cases. Look at something like an NDA, for example. An NDA review. Right. You can now achieve an NDA review in a few minutes. Right. Give your NDA review to Claude, have Claude do the first pass markup, and you as a lawyer look at the output and you can probably spend a few minutes on it and it's done. That's a big difference from where we were 10 years ago. I think it's so big that it has to overcome those barriers. But yes, I'm an optimist too.

Speaker B: Yeah, well, you have to be in this role. But now, given that, what is the additional value? Add that in an environment where technology is enabling more in house work, less outsourcing, putting the information and those tools more at the fingertips of the in house counsel and their legal operations teams and all of that, what is the additional value than an outside counsel that has all of those tools? What is that bringing to the equation?

Speaker A: Yeah, so I think there's a couple of big things here. I mean, first of all, I think legal at complex organizations is always going to have multiple participants, multiple players, multiple vendors who are involved and it makes a lot of sense to take advantage of like economies of scale and specialization and all of that. I think that the core things that an AI native service provider like General Legal can provide are one, the ability to accomplish very significant volumes of work and also be able to kind of fill in the places where the in house team simply can't. I don't know any in house teams who aren't like starving for more resources, aren't begging for more help. Right.

Speaker B: Tons of bandwidth here in Legal. No one ever says that. Fair enough.

Speaker A: So I think a model like ours, we are completely transactional based. You can kind of scale up and scale down the service and pay for what you need as you go. See that adds huge value to an organization. We can help an organization clear their contract backlog at the end of a quarter, for example. I think the other areas is specialization and expertise. So like I said, we have like the privacy expert, we have the fintech expert, we have our crypto expert, we have our health tech expert and you get all of those expertise kind of built into our service. I think that's a value prop that a traditional full service law firm also leverages.

Speaker B: Right.

Speaker A: They have a full offering of the expertise you need to make things work. We can offer significant fractionalization of those resources. You don't need to hire your own privacy expert. That would be like a pretty crazy thing for a company to do. And I think that's a beautiful part of what the service is all about is being able to get the right people into the process, the right knowledge into any business process that you give to us. And then ultimately I dig a kind of bigger picture thing for these AI native providers like ours is the services get better and better as they do more and more contracts. They both get better at the context within a specific client, but also cross market. Right. The more what's the value of a great lawyer? The value of great lawyers, They've seen a lot of deals over many, many, many years and they remember the details, they can tell you what's market in this area and they can tell you how to negotiate to get there. That is in a law firm remains a highly human driven process. But actually with access to data that is now something that's well within the capabilities of these models. And so as these firms do more and more work, they do start to be able to kind of create their own underlying models of what the world looks like and what deal terms should be across all of the areas they practice in. I think that's also why we think these entities tend towards a consolidation motion. Right. Now I think we're going to see a lot of little tiny ones that spring up. A partner splits off from a big firm and they'll run a great like book of business, but they'll be in their sliver and they'll be able to do like their part of the M M and A transaction. But when they need the tax expert, what are they going to do? How are they going to get that? Are they going to go like refer it out? I suppose so. I think what will happen is the ones who do the most work in this space will get bigger and bigger and bigger and consolidate into significant legal service providers.

Speaker C: I'm interested in what it really even looks like. I'm sure a lot of folks are inside of an AI enabled law firm. Do you have managing partners? Do your partners eat what they kill? Do you have a summer program? Like, what does it just like in the folks who are used to that, that traditional law firm? Could you give us a window into what kind of these future law firms look like?

Speaker B: And do the attorneys go to the firm retreat or do they just send their agents?

Speaker A: We let everybody go to the retreat. I don't think we're allowing agents this year, but maybe next year. So our model from the beginning has been that right now the technology is you get the most leverage by taking experienced attorneys and giving them um, that framework to practice. And experienced attorneys actually they kind of solve the gaps that exist in the underlying models. And the line from, I think most of the legal tech vendors, the technology vendors is like, oh, this technology automates your paralegals and your junior associates. I think there's some truth in that model. And, and we see that in terms of the leverage you get out. So our staff is senior associates that we hire from big firms traditionally set a minimum like experience threshold. It's like minimum of 5 years experience because that really matters. That's how you get the most advantage right now. But of course it introduces this whole other question of like, well, all right, well what happens next? What do we do with all of the folks who are coming up from law schools for these, like naj, they just drop out. Is it over for them? We don't think so. We did actually bring in a summer associate class this year. I think what's going to change is how these people get trained. The traditional way of training, as I'm sure you guys know better than I do, is, I don't know, hazing. Right? Like you basically get to work on the lowest level stuff again and again and again for many Many, many years. And you do the reps enough times to, you know, become experts, become excellent practitioners. I suspect you could massively accelerate that learning process. And this is what we saw this year with our summer associates that came in is that they're able to experience this massively accelerated legal practice they are seeing our senior attorneys execute. Their time is meant to go into the places where the attorney is still needed. And so you get much more exposure to the highest level challenges. And that I think is, you know, we don't have all the answers on this. I think that is the kind of foundation though, that we're going to push forward with how we use junior folks in the firm. They can watch and participate in those processes alongside seniors. And my belief is that over time we'll see what it takes to get someone from junior to senior could actually compress pretty significantly.

Speaker B: So I'm struggling to envision that now. So I spent a couple of summers as a summer associate before landing in my firm. They were both great experiences in different ways. Got some specialized, like courtroom training with the senior folks, got some exposure to court, got to do some really interesting things. That said, I think about the projects that I was being entrusted with, research, core writing, analysis, analyzing depositions, preparing them for things that were coming, preparing for an appellate argument, that was pretty cool. But all of it's still tasks that made sense for someone of my level of experience. What does that look like today when you come into an AI native firm and presumably, and you've got to set me straight, if I'm misinterpreting this, but you've got partners and your associates that have developed agents, trained agents to do a variety of tasks. The supervision of those agents presumably requires someone more senior. That's the additional value they're bringing, making sure that result, that outcome is good. So what is the role for someone in a junior position?

Speaker A: Yeah, I think in some ways it's not so different from what you described. So we brought in a summer associate class. So these are like second and third year law students. We did actually give them substantive research tasks for us both in the kind of operation of the firm itself as well as like our agent got into a weird roadblock here. The senior associate or partner at our firm looked at the roadblock and said, ah, I think there's a hole here. We have to do some more research to understand this. Let's give this to the summer associate to look into. And that work is still supervised by that senior person. But they're elevating a unique, challenging issue that takes somebody who can go out and spend the time and look into it, and then that knowledge is contributed back into this ecosystem. And I think there's still a significant role there for these types of folks.

Speaker B: Does that indicate then that the nature of what you're applying agents to do, and it's not just agents, you're using AI in a range of ways that shouldn't be that specific, but I envision you've got agents to fairly well trained for some of the kinds of tasks and analysis that you offer on a regular basis. Does this indicate then that the agent doesn't necessarily run it on its own, that the involvement of that human alongside the agent working outside of those lines or restrictions that the agent has is really what makes it more of a complete offering and deliverable?

Speaker A: Absolutely, yeah. As really well said, I think the core value that agents offer relative to humans is really well done. Legal agents are able to make that. You know, it's actually the same as like getting work from a more junior person, a really good junior person. They kind of tee up what you need to review and they make it easy for you to review and refine the work and produce good work product. And that is the role that humans play alongside of the AI the AI could have. Does you think of it as an initial pass based on knowledge that the human attorney has provided as part of kind of building out or training that agent to do that part of their practice? It's informed by the client's contact. So we take all of the conversations that we've had with the client. We take any past agreements that are relevant. We take Playbooks and fetch their website, fetch their marketing materials. We'll use all of that to kind of inform that agent's execution. The agent does its first kind of like pass through the workflow. It highlights the places where the humans need to pay the most attention and weigh in, and makes it easy for the human to kind of walk through and feel competent about the work that they're producing in collaboration together.

Speaker C: Right now there's so many major law firms doing these large investments into kind of AI. Think Kirkland Atlas talked about $500 million in the next 10 years. I mean, you've been on the ground at TR actually looking at what it looks like for them to actually adopt the tools that they've already purchased. But just curious about your thoughts on what that means for the change of big, uh, law in the coming years.

Speaker A: Yeah, I mean, I do think firms, they are making serious attempts at bringing AI into their practice. I think it's challenging though. I think it's a challenging problem on a lot of levels. Because if you take this apart, I mean, what I'm saying is the core of what an AI native firm is, is not about how you practice, it's about what you give back to the clients that you're serving. And the things we are giving back are pretty challenging for a traditional law firm. To accommodate the flat fee pricing, for example, the highly accelerated turnarounds, integration into these systems is you're a big organization with an entire partnership structure that needs to kind of come along with the change and the kind of reconstitution. You have significant kind of data systems and you have client relationships that have all kinds of different carve outs and provisions for what you can and can't do in your relationship with them. That's a very big ship to kind of try to steer. And I think also AI native means truly AI native at all facets of the organization. It's not just about how fast do we do research and drafting. It's about what is our intake process look like, what is our approach to knowledge management look like, what does our approach to billing look like. All the operations of the firm are at play. And so I think taking a traditional firm and figuring out how to do that is a, I think a decades long project.

Speaker B: That's a really interesting point because we tend to think of the billable hour as that hour of that person's time. And but what's built into the hour is not just that hour that I'm spending, it's the cost of all of those other intangibles that has to get factored into the billable hour to pay for it because you're not going to pay a separate fee on the side for end everything else. Here's the part that goes to our rent, here's the part that goes to the lights. It's just built in. It used to be they went out on things like copy charges and printing and all sorts of things like those were sundries, you know, those were luxuries that were optional. So being able to be AI native across the board.

Speaker C: Yeah.

Speaker B: You could see where a smaller nimble firm has a lot of advantages over a really large firm. Even one that's well heeled and making big investments.

Speaker A: I'll tell a what I think is a kind of funny, interesting case text anecdote reminded me on the copying front. So for many years with our legal research offering, the most used feature of the platform was what would you Guess.

Speaker C: Ooh, I have no idea.

Speaker A: There is a big button at the top of the screen that you print the case with all of the annotations on. And that was an extremely heavily used feature. It was in fact the most popular feature of the platform for a long time.

Speaker C: Well, pivoting from the need for printing paper, I'm curious, as we look into the horizon, especially the rise of agents, what are you seeing insofar as how companies are leveraging it and just how you're seeing it from the engagement in the broader ecosystem?

Speaker A: Yeah, I mean I think one of the really interesting things that AI native firms are sort of right at the crux of is that the world is actually changing around law firms in these very significant ways. If you're working with a hyper growing company right now, legal needs are through the roof.

Speaker B: Right.

Speaker A: There are way more contracts to do now than ever before. We're seeing these companies that are growing their revenue 10x right. In certain especially AI driven areas.

Speaker B: And they're getting longer and more complex, not less so. Which I find kind of extraordinary because you would think now we're getting so good at turning contracts into structured data points that we could be less inclusive of artful language and focus more on those narrow structured data points. Quite the contrary is what we're seeing.

Speaker A: Yeah, um, and I think another cliche in legal, the death of the billable hour and contracts as code. We're all going to get there someday, but hasn't happened yet. And so when it comes to agents, I think one of the fascinating things we are seeing and part of how we think AI natives are going to be able to kind of pivot and move where the market is actually going. These companies are so overwhelmed with their, even their, just their uh, sales workflows that they're increasingly delegating agents to do much of that process. And now those agents are engaging us, general legal, the law firm, as their like legal services provider. Now it's an early pattern, but we see this, we see a move towards more kind of system to system processing of data through these kind of highly operationalized workflows where some of the work is shared with humans and their agents. So I think we are on record as the first law firm period to be hired by an agent. I think that's just the sort of start of a much bigger trend. Also we really think it's important to embrace kind of what's coming with these agentic approaches. So we saw months ago this kind of, I think really intense trend around single person businesses or zero Person businesses. And there's a gap in actually I think in the legal structure in some sense. Certainly companies have to have people, right? They have to have a human that is to incorporate a company in the first place. But there wasn't a design or a model that really allowed for an agent to kind of fully run that company with a human supervising on top. Especially in a way that you know, gives the kind of liability protections. Right. Your agent goes out in the world, it gets itself sued, I mean that's on you and your personal. If you incorporate that, if you don't kind of structure things very carefully, that liability falls on you. Right? You're trying to grow your lawn mowing business with an, an agent and it's going out and breaking privacy rules or whatever, that's your fault and you're liable. So we wanted to kind of embrace that challenge and also start to think about how to accommodate new models of investment flowing into these businesses. So a couple weeks ago we open sourced a framework for incorporating these agent run businesses. We do it, we offer it as a service, but you can also just take the templates that we offer and use them on your own and incorporate your own agent run business. And that structure actually allows for all kinds of kind of management and capital structures to take place on top of running that uh, business. So it enables things like a bunch of venture capitalists being able to invest in shares of a fully agent run business entity. Like there's a potential for a real like inflection point where these things become much, much more capable of these activities in the real world that are economically meaningful. And that's where legal really starts to be incredibly relevant to their behavior.

Speaker C: Right.

Speaker A: These are real dollars are starting to come into play.

Speaker B: Well, uh, I'm sure there are some listeners that are thinking I'd much rather the agent go and initiate a million clicks somehow for my side rather than start a cyber attack. So as the months go by, we're seeing the both sides of what the agents can do. And does that create a challenge for you in this space? We've seen so many stops and starts in the introduction of transformative technology and legal again. I've been working with AI for legal use cases for 15 years. I mean I'm always on the side of positivity here, but I've also seen where there's backlash and push back in inactivity. You can lead a lawyer to AI, but you can't make him drink. Have you experienced that personally? Or is it just really since 2015? And then later the introduction of generative into case text. Are you just seeing the upside? What's your experience?

Speaker A: I think we've only just begun seeing the upside. Right. I think that's the much bigger issue is that to me, there's so much more that we could be doing already with the stuff we have in hand that still needs to come into being. I do think that there are risks in technology. And I think part of what, uh, part of why I think an AI native law firm is a great model for bringing this technology to the world is in the end, the law firm is actually accountable for the outcome.

Speaker B: Right?

Speaker A: There is about we, the firm has malpractice insurance, our lawyers borrow licenses are on the line for the work that we do. And so I think it's a great kind of check that we are embracing this technology and we believe in the work that we're doing and we're going to do the things that are necessary to make sure that is great quality work because we have all the incentives in the world to do that.

Speaker B: Right.

Speaker A: So I think it's a lab in many ways for getting the best possible outcome from the technology.

Speaker C: No, uh, that's beautiful. And thank you so much for joining us today and giving folks a window into this burgeoning world of AI law firms. I hope as they go back to their roles and think of what law firms to put on the panel, maybe just to have a cheap one to push the other ones. At least they consider an AI native law firm like General Legal. But thanks so much for your time today.

Speaker A: Thanks so much, guys. Great conversation.

Speaker C: Meeting of the Minds the Legal AI Podcast is brought to you by Eversort. To learn more about Eversort and how we can help you contract better with AI, visit Eversort. E V I S O R T

Speaker B: um, you can find Meaning of the Minds on Apple Podcasts, Spotify, or wherever else you listen to podcasts. Don't forget to click subscribe so you won't miss future episodes.

Speaker C: On, um, behalf of everyone here at evisort, thanks for tuning in.