[00:00:00] Irene Liu: Welcome to AI Sidebar. I’m Irene Liu, your host and executive director of the AI Initiative at Stanford Law School. Today, I’m delighted to welcome Ryan Daniels, co-founder and CEO of Crosby AI and a Stanford Law School alum. Crosby AI is an AI-native law firm designed to speed up commercial contract timelines and time to signature.

[00:00:22] So today, we’ll discuss what it means to build an AI-native law firm with Ryan and how Crosby’s model differs from a traditional law firm model. We’ll also discuss what Ryan has learned about designing AI products that make lawyers feel empowered. So, with that, let’s jump into my conversation with Ryan Daniels.

[00:00:45] Ryan, thank you so much for returning on campus to join us for the AI Sidebar. 

[00:00:50] Ryan Daniels: Irene, it’s such a pleasure to be back. Thank you so much for having me. 

[00:00:53] Irene Liu: So, Ryan, I can’t believe it, but in 2024, just two years ago and four years after you graduated from Stanford Law School, you started an AI native law firm, and it’s called Crosby AI. And we’ve been hearing this terminology, AI native law firms. So, what exactly is an AI native law firm, and how would you describe it? 

[00:01:11] Ryan Daniels: So, it’s a really good question to start because, in truth, most law firms are using AI in some capacity today. And so, we go back and forth a lot internally on what does this really mean.

[00:01:22] I’d say at the highest level, I’d argue there’s sort of three differentiated qualities about this AI native law firm. It’s corporate structure, their incentives, and then what we think of as a sort of applied lab or encoding machine. I’ll tease these out a bit more. 

[00:01:36] The corporate structure is really simple. Traditional law firms are partnerships. They are built to attract, train, and retain the best talent. I think an AI native law firm has a corporate structure that probably has a C corporation as well, so that you can take outside capital and then lock in capital for longer term investment to do speculative things like building technology. Can’t do that with a typical law firm. 

[00:01:56] The second thing is a business model. The simplest thing here is what business model really incentivizes long-term productivity gains. Probably not billable hours. 

[00:02:03] And then the third, the hardest thing to define because it can look very different, but there should be some core part from a technology perspective that is capturing all of the work that’s happening, all of the decisions lawyers are making, and encoding it for agents to use so that you can offload more and more work to agents. We’re not very picky on what really, you know, an AI native law firm could be lawyers doing most of the work and agents doing a little bit of it, or agents doing a bunch of the work and lawyers doing, you know, just a small percent.

[00:02:31] But I think those core attributes, right? It’s the corporate structure, it’s the incentive model, and the sort of encoding layer define the AI law firm. 

[00:02:39] Irene Liu: And how did you decide to start an AI native law firm instead of a legal tech company? What was the motivation behind that? 

[00:02:46] Ryan Daniels: So, this is a very long searching process. I spent about nine or 10 months before we started the company, so throughout all of 2024. I left my job. I got so animated by how AI would change the legal profession. It became an obsession, and I was just speaking to tons of lawyers. 

[00:03:01] One of the fundamental questions we kept coming back to was the market for legal software is about $30 billion. The market for legal service is about a trillion. And that gap, that it’s about 30 to 1 ratio, is so big, like we were trying to think what explains it. And the more convinced we got about models improving, the more we realized if we could build a law firm that successfully moved some of the work to agents, or actually a lot of it even if things went really well, we could sell into that trillion-dollar market from day one.

[00:03:29] And so that, it was very theoretical, but the more we spoke to people, the more excited we got about the idea. 

[00:03:33] Irene Liu: And you focus on commercial transactions in particular. How did you end up with that focus? And having been a general counsel myself, commercial transactions are so pivotable because it brings in revenue to a company, so you need to make sure that the commercial machine is moving and that it is moving smoothly for your sales team as well as for the business.

[00:03:51] So was that the key idea? That because it is a key engine of a business, that that’s the area that you wanted to focus on? 

[00:03:57] Ryan Daniels: It’s a really elegant framing, and I don’t even know that we arrived at that initially. I started my practice at a law firm at Cooley. We didn’t see much of commercial contracts. I had no idea how important they were, and I think a lot of what I typically heard from lawyers is, “Oh, these are kind of commoditized. This is not the most pivotal legal work.” 

[00:04:15] The more I spent time with GCs, this was like the bulk of what their team did. And again, from a theoretical perspective, but it makes sense, any economic transaction, let’s call it over $10,000, maybe 20,000, probably has a contract behind it. And so, when you really back out, you realize this is kind of the engine of transactions. It’s the common connector. 

[00:04:33] And so we just did some market math and realized, oh my goodness, this is the thing that every business relies on. As a secondary issue, which is even more interesting, it’s the hardest thing for AI to do well because it’s super subjective. It’s just a negotiation, the redlining process. When you poll most businesses on what’s going well and not well with legal, typically they’ll say contracts take too long. So, we just said, “Okay, let’s just do that and let’s do it really well.” 

[00:04:54] Irene Liu: That’s so interesting. And so, when you’re thinking about that commercial transaction, you said it was commoditized. So how did you decide to price it? I think you price it by task instead of by the hour in- 

[00:05:04] Ryan Daniels: That’s right 

[00:05:04] Irene Liu: … in a typical model. So how did you decide on the pricing model for that? 

[00:05:09] Ryan Daniels: Before we thought about pricing for the task, we’d already agreed, my co-founder, John, and I, let’s start a law firm that doesn’t charge by the hour, and so we’ll have a very strong incentive throughout the company to spend less human time on each task.

[00:05:24] I don’t think lawyers at law firms try to spend more time on each task, but there’s definitely no incentive to spend less time, you know, and you have to submit your hour card each day. 

[00:05:31] And part of the story here is I’d ended up discovering that there’s a big offshore outsourced legal services industry in India. I’d never heard of it before. I ended up going to India, learning more about it in person, and realizing that the emergent sort of skew of work that was trying to be outsourced was contract review. And because it’s so judgment heavy and so context rich, it’s actually not that easy to commoditize. And that was our… We were like, “Okay, this is what we should focus on.” 

[00:05:55] Irene Liu: And then when it’s billed by the task, so is it by contract? 

[00:05:59] Ryan Daniels: So, we do it by deal. Again, we did a lot of first principles thinking. We lost a lot of money on it until we were able to get the pricing right. But we just thought, okay, what really aligns our incentives with our clients?

[00:06:08] Well, the clients wanna close deals quickly. Right? They wanna get to a place where they sign. And if we charge for every turn of a document, then we’re probably gonna be incentivized to be really stubborn and just keep reviewing ’cause we keep making money. So, we just said, let’s charge once, and our incentive is to get this thing signed in as few turns as possible.

[00:06:27] And you know, I think a lot of our clients hear that and say, “Okay, you know, I don’t know that I trust you to get it totally right, but that’s so sincere because you will lose money if you don’t negotiate this well.” 

[00:06:34] Irene Liu: And so, by doing that, by trying to do it as few turns as possible, you’ve been creating some metrics to measure on your end. And one of the metrics that you mentioned that we talked about is the human review time metric. And so, can you tell us more about that metric? Like, how is that different from a billable? 

[00:06:51] Ryan Daniels: So, you know, in early days we started to understand the task that was ahead of us, which was how can we actually know that we’re offloading work from lawyers to agents? That’s the only thing that makes this company, I think, uniquely interesting. Otherwise, we might be a very optimized, efficient law firm. Now, if we looked at revenue per lawyer, which, we can get back to ’cause we’re starting to look at now, in the early days, well, we just charged more money, and that didn’t necessarily mean we’re being more efficient.

[00:07:17] So the core thing we had to see was for some subset of tasks, it’s hard to normalize the data, but assuming we could, could we actually show that a lawyer, month over month, quarter over quarter, was spending fewer minutes on a similar enough task? And if the answer was yes, then they were probably relying more and more on AI and spending less time reviewing it themselves.

[00:07:34] And so, every single week in our all-hands, we religiously track this number. And you know, because we only bill by the document or the negotiation, not by the hour, the whole team, engineers, lawyers, ops teams, are aligned on, “Let’s get that number down.” 

[00:07:46] Irene Liu: And one of the things that you’ve been very candid about is that by optimizing the system and the metrics, sometimes it goes a bit too far, and that sometimes the lawyers can feel a bit more like inputs, huh, and that it could be a little bit demoralizing. 

[00:07:59] And so, one of the things that you mentioned was that you actually try to find product managers that are lawyers and have a lot of empathy for lawyers because you wanted the lawyers to feel empowered. So, what were some of the actions that you took to make sure that the lawyers felt more empowered in this system where measurement is so key?

[00:08:17] Ryan Daniels: There’s a lot of things that we’re doing that are not that novel. We’re selling legal services. But there’s a lot of things that we’re doing that are fairly new, just because AI as a technology and what it can do is new. And one of these things is trying to create a law firm that is really obsessed with reducing the amount of time a human spends on a task. That is very unprecedented in the industry. 

[00:08:34] And one of the first things we did was hired a really good operations team. These are people that come from operationally intensive companies like the data labeling companies, companies like Amazon, DoorDash, you know, that just, like, are really good at optimizing complex supply chains.

[00:08:47] And we kind of just, again, we were figuring it out as we went along and said, “Okay, this is just a complicated logistics problem”, right? Like, we have these inputs and units of work, and how do we optimize those units of work to turn things around faster, to spend less time on some tasks, to reduce the touches?

[00:09:00] It’s probably a little cliché, but when you look at the whole system, you sort of overlook the individual inputs and parts, and those are the lawyers who are full-time employees at our law firm who come from prestigious backgrounds. 

[00:09:10] We recognized it probably a little too late, but we recognized that that was not a great way for a lawyer to work. In other words, the job of a lawyer increasingly became, AI does some review, it serviced a lawyer, and they have to kind of tweak it a little bit and give some input, but it felt like they were working, in some ways, for the agents and for the AI system and constantly being pushed to work, faster and like, to reduce their touch. And that just wasn’t gonna work, so that’s kind of what we had to address quickly. 

[00:09:37] Irene Liu: So, the humans were in the loop, but they felt more like they were being pushed along by the machines instead of the humans pushing along the machines. 

[00:09:43] Ryan Daniels: Totally. And you know, it was a very humbling lesson for me as a leader that when you get obsessed with these high-level metrics ’cause you’re trying to capture the business, you can overlook the smaller pieces and what’s really going on. And with really good intentions, you can have bad consequences.

[00:09:55] I mean, this was not that big of a deal. I still review contracts a couple times a week so I can be in the system and see what our AI looks like and how it’s feeling. And what we started to touch on was from a product perspective, the subtlest changes, like the words of a button or the placement of a button, have a huge difference. And I think historically, you know, like Zoom beat every competitor ’cause it was just easier to use and more delightful. 

[00:10:16] And so we started thinking, “Okay, what feels great as a lawyer?” And I can give a bunch of examples, but the easiest was, how do we make it feel like the agents work for you? Like they are your junior attorneys or your paralegals.

[00:10:27] And it was just, like, finding these kind of little cues to make you feel like you’re in control. Like they’re listening to you, like there’s feedback that the agents get from you. So, I think we’re early, but you know, it’s been a good lesson for, I think a lot of other law firms that will continue down this route that we’re on. You know, the lawyers have to be at the center. That’s kind of been our mantra. 

[00:10:44] Irene Liu: And with the lawyers at the center, what were some of those minimal tweaks that you’ve made in the products just to even make them feel more empowered and excited, and that they’re in control? 

[00:10:53] Ryan Daniels: Yeah, so again, it’s subtle, and you might hear them and think, “Okay, that doesn’t seem like a big deal”, but it really adds up. So, you know, one thing is we had these queues of reviews that were coming into our system. And when you’re a lawyer, you basically said, okay, like, unless you check that you’re offline and unavailable, contracts just come to you. Okay. Trivial, right? Like, that’s a system that we have to optimize. 

[00:11:12] It’s much more interesting to do the opposite, to say, “I’m online. Start sending me contracts to…” The default is that you’re not available. Okay, so that was a small thing, but otherwise it just felt like you were kind of drowning, and you had to hit stop.

[00:11:23] Another thing was, rather than a contract just coming to you, saying, “Give me another contract, I’m ready for it”, right? Like you can, imagine how that feels. And then the other thing was, like, you have these agents that we have like a sort of orchestration agent that figures out when a review comes in, who should it go to?

[00:11:36] Should it go to a really expert person, to the person who saw it last time, to the person who we think really knows this client well? And giving lawyers some feedback to those agents to say, “Hey, like you kind of keep assigning me these tasks. They’re actually really good for that guy.” Rather than having like an ops team try to orchestrate those. That feeling of being in control really, really makes a difference. 

[00:11:54] Irene Liu: And to create that product experience where the lawyers feel more in control, you were adamant about trying to build a product team that understands lawyers. 

[00:12:02] So, how did you even do that? How did you find lawyers that know the product, or did you have to educate the product managers on what it’s like to be a lawyer? Where did you find the talent to build that empathy to understand the legal talent frame mindset in order to build such a product that works for them? 

[00:12:22] Ryan Daniels: You know, I think that whatever lawyers are feeling, to the extent there’s sort of anxiety about their future careers and what they’ll do, I think engineers are a couple years ahead. Insofar as a lot of engineers have an existential question of, what will my job be if agents are gonna be better than me at writing code?

[00:12:36] One of the things that’s obvious to me at this point is the engineers that have really high empathy with their user, so that they can even identify the most subtle nuance of redlining a contract and, like, why layer track changes are painful to read, do really well. 

[00:12:49] And so we just started screening really aggressively for these high-empathy engineers, with some funny drawbacks, like sometimes the engineers are too high empathy and they’re like, you know, “Contract review is hard.” and we’re like, “Well, yeah, but, you know, this is what we do here,” right? And so- 

[00:13:00] Irene Liu: But that’s the core of your business. 

[00:13:01] Ryan Daniels: Right. And so, but, and so that’s been really special. And we actually sat the engineers and lawyers next to each other in staggered desks for the first year. And I think product managers play a big role, but the engineers actually redline contracts once a week just to feel what that’s like, see what the product’s like, and develop that empathy, and I think that’s been a really good decision. 

[00:13:18] Irene Liu: And have you noticed it with the lawyers on your team? Are they feeling more empowered, and are they continually providing the feedback back to the engineering teams? Is there a, ongoing feedback loop?

[00:13:29] Ryan Daniels: Totally. Yeah, I think a key part of this business was the concern that we always have is, let’s say that human review time is not going down. The concern we’d always have is engineers say, “Well, these lawyers aren’t using what we’re building.” And conversely, lawyers saying, “Well, the engineers aren’t building anything useful.”

[00:13:44] And so, creating a very shared ethic of we’re in this together, we’re one team, we’re collaborating, even to the point of probably being less productive. We have to be in the office every day. We should eat all our meals together. We should spend more time getting to know each other when we could be working, I think probably contributes to that sense of we really wanna help each other.

[00:14:02] Irene Liu: And so, having engineers sit side by side with you as a lawyer, I’m sure that helps with the feedback loop, but is there ongoing product design testing feedback and decision-making that’s happening throughout the day in addition to those lunches? 

[00:14:15] Ryan Daniels: Yeah, it’s gotten to the point where we have to say, “Look, look, we need a roadmap,” because when your end user, being the lawyer, is sitting right next to you, it’s very distracting when you’re like, “I don’t like that button.” it’s like, okay, you can live with it for a week.

[00:14:23] But, but yeah, there’s constant iteration cycles. We constantly have shadowing sessions where an engineer sits with a lawyer and tries to solicit feedback and then compiles them. Now we have a couple of product managers who do the same thing.

[00:14:33] We have a daily sync, or I guess Monday, Wednesday, Friday, where a team of engineers, researchers, and lawyers all sit in a room and go through any review that took over, like, two hours and talk through what went wrong here from a technical perspective or from a usage perspective by the lawyer. And so, it’s just constant, and I think being in one room has been, like, a really, really helpful part of that. 

[00:14:53] Irene Liu: At a traditional law firm, obviously for most businesses and most law firms, the partners and the lawyers often are the most important talent at the law firm. When you’re at an AI native firm and when you’re building an AI native firm, you have a lot of different types of talent that you’re working with. You’re working with lawyers, engineers, product teams. So, how do you work to make sure that you’re not undervaluing one group or another? 

[00:15:17] Ryan Daniels: Look, I don’t think we’ve solved this one yet, and I think we’re still small enough that it’s been okay. But there is an existential question of what are we, right? Like, is the product the software we’re building? Is the product the lawyers who are doing the work? And the answer is yes to both. 

[00:15:30] You can appreciate that, like, at a law firm, we literally called anybody who wasn’t a lawyer support staff. That was just the name, and the lawyers were the show. And there were really no actual bosses. Your lawyers reported to the clients. 

[00:15:43] And so, this is an identity that we’re just trying to forge here. I think we are working on it. I think for the most part, so long as the Engineers build knowing that the lawyers are doing something really valuable. And that as AI can do more and more of the work, which has always been the plan, that the lawyers will probably be the most valuable thing that we have at the company. In terms of like how much people would be willing to pay for that lawyer to look you in the eyes and say, “It’s gonna be okay” in a moment of crisis or get on the phone with you and walk you through a complicated thing.

[00:16:12] Those are the things that I, in my bones believe AI will never do. If engineers appreciate the value that those lawyers will have in the long term, they realize, okay, this is actually a really core asset. Likewise, when lawyers start to feel how much agents are actually making their lives better, that all that crummy kind of repetitive work they used to do they don’t have to do anymore, they really appreciate what the engineers are doing.

[00:16:31] Irene Liu: So, for an AI native law firm, where are you getting the commercial lawyers? Are you getting them from traditional law firms or in-house, or where are you getting the talent? And is there enough talent? I would think so because commercial transactions is such a core bread and butter to every company, so there are a lot of commercial lawyers in general. But where are you getting the talent that’s interested in trying out this new model and working for an AI native law firm? 

[00:16:55] Ryan Daniels: A corollary of a question that we get asked a lot by like investors is, “Why don’t you buy a law firm?” There’s kind of a roll-up play that’s gotten really popular. 

[00:17:02] I think our intuition was correct that it’s way too important to get the lawyers right here, that you don’t wanna just acquire and end up with 10 or 20 or 100 lawyers that you didn’t know before. We rigorously screen every single one. And what’s been amazing is as we have a small brand in certain circles of the legal world, we have a lot of lawyers reaching out and saying like, “I wanna be part of this future. This is exactly what I’ve been looking for. I know where things are going.” 

[00:17:25] And for the first few months we really had to look for those people, but they’re out there, and now they find us, and that’s cool. It feels like you kind of have a band of like pirates that we’re bringing together. 

[00:17:34] So, I think no shortage, but the people who sincerely are comfortable with questioning their like existential role as a lawyer every week or every month as it changes, it’s uncomfortable. But you know, they really embrace the change and having them all together has been great. So, I think finding more and more of those people. 

[00:17:49] Irene Liu: And where are you finding those people? Are they coming more from traditional law firms that wanna experiment with this model, or is it mostly in-house? 

[00:17:55] Ryan Daniels: Total mix. We find a lot from law firms who just happen to be in New York and there’s a lot of big law firms there. They have to go through their own training of learn to be commercial and kind of that classic path. And then a lot of folks from commercial teams who just feel like, “I’m not allowed to spend enough time experimenting and I wanna do more.” So total mix. I’d say probably 60/40 law firm to in-house. 

[00:18:15] Irene Liu: And some people assume that AI, as AI becomes more capable, legal talent will become less important. But you have argued the opposite. 

[00:18:22] Ryan Daniels: Yep. 

[00:18:23] Irene Liu: But why do you believe that great lawyers may become even more valuable, and what skills will distinguish them? 

[00:18:28] Ryan Daniels: I think the easiest thing is just it would be an insane endeavor to build an entire law firm if in a couple of years, we thought like we’re not gonna need these lawyers.

[00:18:36] It’s just so much effort from a regulatory perspective, from hiring management. And it would be, I think, a- totally reasonable company to hire a bunch of contractor data labelers and try to build some of the things we’re doing in coding legal judgment. But I think that’s a less interesting upside opportunity.

[00:18:51] I think what’s more interesting is, we’ve never seen a deal close without, and we’ve done, almost 30,000 deals at this point, without human lawyers weighing in with some judgment that defies every bit of, not for every deal, but for a lot of deals, every bit of logic or ex-ante rules or playbook you came up with, just being human.

[00:19:10] And boy have we tried to, like, teach agents to replicate those judgments and break all the rules and it just, you know, there’s something missing. And sometimes that’s getting on the phone with a counterparty, sometimes that’s just doing something totally unexpected. That’s not going anywhere. And that, to me, is the fun part of being a lawyer. And so, I think that the premium for that gets higher. 

[00:19:27] I also think that more companies than we’d ever appreciated can’t afford decent legal help for commercial contracts. They probably agree to terms they probably shouldn’t. And so, I just think, like, most lawyers today that we speak with will become more and more valuable. But the key is obviously, like, getting comfortable offloading a lot of the repetitive work- to agents and spending all of your time doing some of the more thoughtful work. 

[00:19:50] Irene Liu: And for those clients of yours, that are willing to do that and offload some of those to agents and work with you at Crosby, what incentivizes them to use you versus another fractional general counsel, for example, that they’ve known and they’ve worked with for a while?

[00:20:05] Ryan Daniels: Yeah, I mean, it’s a great question, right? Because to go back to your last question, like, what value do humans provide? You know, what don’t agents have? Like, these are people you know, you trust, they have taste, they have a personality. Some people are really aggressive; some people are really conciliatory and friendly and kind.

[00:20:20] And so, I understand why some of the people we work with are like, “Well look, I’ve worked with that guy for nine years- and they really get me, and they- I match their style.” Again, we like to say we’re long humans, right? 

[00:20:28] Irene Liu: For sure. 

[00:20:29] Ryan Daniels: There’s a reason for that. I think for certain people we work with, the value’s pretty obvious, right? We don’t bill by the hour. And that’s really, really enticing. And we’re really fast. It’s like two, three, four hours. And almost everybody we pitch says, “I don’t really believe it, but I’m willing to try.” And I think we’ve only had one company that didn’t move out of pilot. So, it tends to be pretty compelling.

[00:20:48] I would also say we’ve worked plenty of times with sort of a fractional GC in the loop. But for the most part, people that try this out realize, okay, there’s something here. 

[00:20:53] Irene Liu: And we’re starting to see more AI native law firms emerge. And we’re seeing it in different categories outside of commercial as well too. What do you think is the future of AI native law firms? 

[00:21:02] Ryan Daniels: Look, I think every law firm that is viable and a good business in 10 years will be AI native in some capacity. The task of becoming AI native when you have existing systems, and I mean, it’s, it’s hard to overstate how complex it is to rebuild that. And our bet is we can sort of scale up and build credibility before the really credible 100-year-old law firms can actually become AI native from a technical perspective. 

[00:21:25] I think everybody will look somewhat like us in 10 years. I think it’s an inevitability. Generally speaking, I love the upstarts like us because we raise the floor, I think force the ecosystem to react, and that benefits the consumers quite a bit.

[00:21:37] Irene Liu: And what keeps you up at night when you’re thinking about the market, and if in 10 years every law firm is going to be AI native to a certain degree? 

[00:21:46] Ryan Daniels: I often joke that from an ideological perspective, if this all goes to zero at Crosby, but we are part of, like we’re some really annoying force that makes every law firm adapt, I’ll feel satisfied ’cause that’d be a really worthwhile mission.

[00:22:01] What I worry about is that legal work, it’s hard to verify quality. It’s probably one of, like the big impediments to AI really being helpful for lawyers is five different lawyers, the more senior they can get, will disagree more and more as they get more senior. And as a result, it’s really hard to define quality. In legal work, it’s hard to get AI working well at it. 

[00:22:19] This is what terrifies me is like if we don’t fully crack this, we’ll never realize the true potential for these language models in legal, and so we wanna be, one of the first to crack it for our particular domain. 

[00:22:30] Irene Liu: And just like the question about what keeps you up at night, what wakes you up in the morning? What keeps you excited, and what should we expect from Crosby in the future? 

[00:22:38] Ryan Daniels: You know, like it’s so surreal being back on campus, and I love being back at the law school. I loved law school, and I loved it for the theory. I loved it for the critical thinking about the legal profession and the role of the lawyer and all the cases we read. You become a lawyer and you’re like, “Wait, what am I doing?” 

[00:22:53] And we literally get to critically think about the role of the lawyer, what jobs we should do versus offload to agents. From an intellectual perspective, it’s truly the best job I ever could’ve imagined. It’s so much fun. It’s hard, it’s stressful and everything, but I feel very lucky that I happened to be alive and a recent graduate of law school when LLMs started to explode.

[00:23:11] I think most lawyers who have some inkling of wanting to innovate here or be curious or tinker in the legal domain, it’s such a great time to be practicing. 

[00:23:18] Irene Liu: And as now a CEO of a company, what are some practical tips that you have for any aspiring lawyers as well as aspiring law students that wanna build something during this time of gen AI?

[00:23:29] Ryan Daniels: Well, I think George said it when he was on the podcast, Dean Triantis, a couple weeks ago, which was it’s truly a great time to be an entrepreneur in the legal world, and I, I don’t really think it was 10 years ago. Technology didn’t do too much for lawyers. The ability to do something disruptive and novel was quite limited, and there’s a reason that legal was just not an interesting category in technology.

[00:23:50] And now it’s never been more interesting. It’s probably second to code generation the most interesting service area for models. And so, I think for law students, I’m not a very distinguished lawyer. I can’t give advice on that career. But I can say to try something that seems a little far-fetched right now in the legal domain because of some insight you came across being a naive law student, it’s really great, and I think it’s totally worth like for a semester or two trying something and seeing what happens.

[00:24:14] Irene Liu: What if someone wants to build like you? 

[00:24:16] Ryan Daniels: They should go for it. They should 100% go for it and reach out to me. 

[00:24:19] I remember three years ago, I was back on campus right when we were, I was thinking about starting the company or two and a half years ago, and I’d reached out to a bunch of law students that had backgrounds that looked like they’d be into entrepreneurship, and they looked at me like I had three heads. That’s just changed so much. 

[00:24:32] When I’m back at campus, I keep getting students reach out to me saying, “Hey, we’re thinking of starting something. We’re working a project in Startup Garage.” So, like that’s been really interesting. Very new. 

[00:24:41] Irene Liu: And even the VC market has completely embraced legal tech- 

[00:24:43] Ryan Daniels: Oh my God, yeah.

[00:24:43] Irene Liu: …in ways. And so, what’s your perspective on that? 

[00:24:46] Ryan Daniels: Build now. While you still can. 

[00:24:48] Irene Liu: I love that. Well, that’s such a great note to end on. Thank you so much. I so appreciate you returning back to campus and returning regularly to join us and to share all your knowledge with us. 

[00:24:58] Ryan Daniels: It’s an honor to be here. Thank you, Irene. 

[00:25:00] Irene Liu: Thank you.

[00:25:05] A special thank you to Ryan Daniels for an honest and insightful conversation about lawyer-centered product design and the future of AI native law firms. One of the clearest takeaways from today’s discussion is that better technology is not only about efficiency, but it’s really about trust, control, and designing systems that help lawyers feel more capable and more empowered in their work.

[00:25:28] So thank you so much for tuning in to The AI Sidebar and listening to our conversation today. Please follow the podcast and share the episode with someone who is also exploring how AI is reshaping the legal profession. We’ll be back in two weeks with another thoughtful discussion, and until then, stay curious and keep learning