1 00:00:02,360 --> 00:00:04,364 Colin Levy, how are you this morning? 2 00:00:04,364 --> 00:00:06,208 I'm doing well, how are you? 3 00:00:06,387 --> 00:00:08,174 I am doing great. 4 00:00:08,174 --> 00:00:10,521 I appreciate you joining us today. 5 00:00:11,247 --> 00:00:12,618 Thanks for having me. 6 00:00:12,642 --> 00:00:18,427 Yeah, you and I, I've been consuming your content on LinkedIn for a while now. 7 00:00:18,427 --> 00:00:24,982 And when you and I got connected, I thought it was a great opportunity to sit down and have a chat. 8 00:00:24,982 --> 00:00:27,955 And you write about a bunch of different topics. 9 00:00:27,955 --> 00:00:31,778 You seem to have a passion for legal operations. 10 00:00:31,778 --> 00:00:37,462 And so we're going to get into some of that stuff today, but before we do, 11 00:00:37,738 --> 00:00:39,960 Um, let's, let's do a quick introduction. 12 00:00:39,960 --> 00:00:52,450 So you started your journey in big law and lit support and you moved to some in-house roles, uh, after law school and you're currently director of legal at Malbec. 13 00:00:52,450 --> 00:00:53,470 Is that right? 14 00:00:53,584 --> 00:00:56,726 Correct, Director of Legal and Evangelist at Malibu. 15 00:00:57,058 --> 00:00:57,470 Okay. 16 00:00:57,470 --> 00:00:57,880 So yeah. 17 00:00:57,880 --> 00:01:00,744 So tell us like who you are, what you do and where you do it. 18 00:01:01,392 --> 00:01:04,354 Sure, so I am a lawyer. 19 00:01:04,354 --> 00:01:05,885 I am Malbec's head lawyer. 20 00:01:05,885 --> 00:01:13,740 Malbec is a contract bicycle management solution for large businesses. 21 00:01:13,901 --> 00:01:29,892 I am, as their director of legal and evangelists, lead their legal efforts in terms of data privacy, negotiating agreements, assisting with other efforts that need legal eyes on 22 00:01:29,892 --> 00:01:30,572 them. 23 00:01:30,732 --> 00:01:46,967 In addition to that sort of area, I also contribute to blog posts, do webinars, podcasts, attend conferences, and basically help in any way that I can with Volbec's general selling 24 00:01:46,967 --> 00:01:48,398 and marketing efforts. 25 00:01:48,738 --> 00:01:50,539 And you're an author, correct? 26 00:01:50,796 --> 00:01:52,056 I am. 27 00:01:52,336 --> 00:02:04,220 I had my first book come out last year, The Legal Tech Ecosystem, a accessible story-based introduction to the world of legal tech. 28 00:02:04,220 --> 00:02:15,403 I also co-wrote with one of the co-founders of Malbec CLM for Dummies, a very brief high-level overview to what contract management is all about. 29 00:02:15,583 --> 00:02:18,884 I've also contributed chapters to various books. 30 00:02:19,136 --> 00:02:26,154 And or contribute blog posts what have you so writing is a big part of what I do and what I enjoy doing 31 00:02:27,246 --> 00:02:36,234 So you were in big law and now you're in-house, which is a common pattern. 32 00:02:36,234 --> 00:02:40,597 Many in-house lawyers made their way through big law at some point. 33 00:02:40,597 --> 00:02:46,432 But how has that journey been and what have you learned along the way? 34 00:02:47,514 --> 00:02:52,608 Well, my one and only time in big law was working as a paralel prior law school. 35 00:02:52,608 --> 00:03:00,733 And that experience was eye opening in some ways because it gave me a lot of insight into how law firms, big law firms operate. 36 00:03:00,994 --> 00:03:10,380 It also gave me insight into technology and how that even at that stage of my career was impacting the practice of law. 37 00:03:10,600 --> 00:03:16,244 So it was definitely interesting and eye opening, but also 38 00:03:16,580 --> 00:03:22,242 helped convince me that Big Law was not where I wanted to be after I graduated from law school. 39 00:03:22,323 --> 00:03:28,125 But I did want some work experience before I worked, before I went to law school, which I definitely got. 40 00:03:28,325 --> 00:03:32,367 And that experience, again, piqued my interest in technology. 41 00:03:32,467 --> 00:03:43,682 And I would say through law school and then after law school, I've always seen this evolving relationship between technology and the practice and business of law and thought. 42 00:03:44,240 --> 00:03:46,240 You know, this is an interesting space. 43 00:03:46,240 --> 00:03:47,260 It's evolving. 44 00:03:47,260 --> 00:03:53,740 It's one that I think is going to become increasingly important as technology evolves and plays a bigger role in our lives. 45 00:03:53,740 --> 00:04:05,580 And so I took it upon myself to initiate conversations with others who are either creating products in the space, who are talking about the technology and a lot of relationship, or 46 00:04:05,580 --> 00:04:10,120 who were quite frankly interested in learning about it as much as I was. 47 00:04:10,120 --> 00:04:12,516 And it was those conversations that then 48 00:04:12,516 --> 00:04:23,764 led me down the path of getting more interested in legal tech and then further down the road, producing my own content helped inspire and inform others about legal tech and it's, 49 00:04:24,145 --> 00:04:28,388 I think, importance in the world of law practice. 50 00:04:29,110 --> 00:04:29,590 Yeah. 51 00:04:29,590 --> 00:04:38,376 So the last time you and I spoke, we talked about some of the challenges in big law, specifically with work-life balance. 52 00:04:39,257 --> 00:04:46,022 I think we equated it to, there's some similarities to, on the investment banking side. 53 00:04:46,022 --> 00:04:54,047 I spent 10 years at Bank of America and had folks in the IB and it was grueling hours. 54 00:04:54,047 --> 00:04:58,730 In fact, think actually very tragically Bank of America had a 55 00:04:58,818 --> 00:05:13,927 had an investment banking associate pass away from what they think was a stress induced stroke, working 80 hours on a weekend to get something across the goal line during a deal. 56 00:05:13,927 --> 00:05:21,491 And they came out with some guidance to kind of protect and help that. 57 00:05:21,491 --> 00:05:27,194 when you read it, they don't put a hard stake in the ground. 58 00:05:27,618 --> 00:05:35,488 You know, it sounds like was it, was it the lack or challenges of work-life balance that made you realize the big law wasn't for you? 59 00:05:36,398 --> 00:05:37,979 Yeah, it was a couple of different things. 60 00:05:37,979 --> 00:05:41,671 was certainly the work-life balance not being in control of my schedule. 61 00:05:41,671 --> 00:05:45,273 That certainly was one influencing factor. 62 00:05:45,273 --> 00:05:59,921 I think another factor was I just didn't like big law environment, just the way that the culture was, the types of people that I saw and encountered were not people by and large 63 00:05:59,921 --> 00:06:06,084 that I wanted to kind of associate myself with or be with or have to manage or... 64 00:06:06,190 --> 00:06:07,941 have a relationship with. 65 00:06:08,601 --> 00:06:20,897 And then lastly, I think that, you I was always interested in kind of experimenting and pushing the envelope in terms of practice and business and how both impacted the legal 66 00:06:20,897 --> 00:06:21,717 industry as a whole. 67 00:06:21,717 --> 00:06:32,208 And while the law from life just seemed to be precluding some of that, you know, interest in exploration. 68 00:06:32,208 --> 00:06:38,017 It was just not something that I knew was going to jive with my own personality and my own business interests. 69 00:06:38,318 --> 00:06:38,948 Yeah. 70 00:06:38,948 --> 00:06:49,778 I mean, there's been a lot of, there's been a lot of scrutiny around and a lot of conversations around the billable hour requirements when attorneys, know, logging, were so 71 00:06:49,778 --> 00:06:51,478 info dash is a product company. 72 00:06:51,478 --> 00:06:56,198 Now we, we started our journey as a consulting organization. 73 00:06:56,198 --> 00:07:06,232 So we're very familiar with the billable hour and how many hours on the clock it takes to generate 40 hours of 74 00:07:06,232 --> 00:07:10,363 billable time a week and it's a lot, the number is a lot bigger than 40. 75 00:07:10,363 --> 00:07:19,986 And you know, if you're, if you have a 2000 hour billable quota, there's 52 weeks in a year, you get a two week vacation, 40 times 50 is 2000. 76 00:07:19,986 --> 00:07:28,589 So, you know, just maintaining your, your billable hour quota has to be an absolute grueling task. 77 00:07:28,589 --> 00:07:32,810 Um, I would imagine things are different on the in-house side. 78 00:07:33,300 --> 00:07:34,110 they absolutely are. 79 00:07:34,110 --> 00:07:45,695 Definitely don't have to worry about that and entering time, but it definitely, you know, brings me back to my days of working for that law firm and how I spent all this time 80 00:07:45,695 --> 00:07:47,996 entering my time in and it would never be right. 81 00:07:47,996 --> 00:08:00,252 And I was just looking to get paid and yet it was super hard to be paid on time because of just the almost absurd level of effort and time I had to put into entering into my time 82 00:08:00,252 --> 00:08:01,432 correctly. 83 00:08:01,868 --> 00:08:04,210 and it was, it was just ridiculous. 84 00:08:04,210 --> 00:08:17,979 Um, you know, think the bill Blower model as a whole, uh, is certainly resilient one and certainly one that seems very resistant to outside pressure, but it also promotes a, I 85 00:08:17,979 --> 00:08:30,992 would argue a unhealthy work-life balance and also promotes a sort of, you know, work every day and then work some more and then work some more, uh, which just isn't healthy. 86 00:08:30,992 --> 00:08:32,263 I'm not against work. 87 00:08:32,263 --> 00:08:33,003 like to work. 88 00:08:33,003 --> 00:08:34,714 I enjoy being busy. 89 00:08:34,714 --> 00:08:47,439 But I do think that we as human beings really need to make time for ourselves to ensure that we're listening to ourselves and that we're taking time to refresh ourselves and 90 00:08:47,459 --> 00:08:48,266 manage ourselves. 91 00:08:48,266 --> 00:08:58,224 Because if we don't do that, then we're really going down a path that where we're not going to able to ourselves, let alone help anyone else. 92 00:08:58,552 --> 00:09:00,302 Yeah. 93 00:09:00,303 --> 00:09:08,486 The billable hour is, you know, this is, mean, the whole AFA conversation has been going on for a really long time. 94 00:09:08,486 --> 00:09:14,148 And to your point, the billable hour seems to not want to die. 95 00:09:14,148 --> 00:09:19,811 You know, I've heard, you know, how much of that is really on the client side? 96 00:09:19,811 --> 00:09:28,365 I mean, I've heard mixed reviews in terms of how ready Inside Council is to embrace 97 00:09:28,365 --> 00:09:29,690 value-based billing. 98 00:09:29,690 --> 00:09:31,496 mean, what's your perspective on that? 99 00:09:32,474 --> 00:09:42,291 So I think that there is certainly a strong still feeling of clients have grown accustomed and used to billbower billing. 100 00:09:42,291 --> 00:09:51,538 But I also think that they are growing wise the fact that there are viable alternatives to it that they can be engaged in. 101 00:09:51,759 --> 00:09:58,883 And especially in an environment where costs are high for many, I think that 102 00:09:59,332 --> 00:10:11,007 simply asking the question of, you know, are there other ways to bill for this work is a perfectly good question and legitimate question to be asking and a good, and I think also 103 00:10:11,007 --> 00:10:16,500 points to the fact that a lot of the work that lawyers do is repetitive. 104 00:10:16,500 --> 00:10:24,183 It's not, you know, everything isn't always ad hoc or bespoke as much as a lot of lawyers claim that it is. 105 00:10:24,183 --> 00:10:26,096 And I think because of that, 106 00:10:26,096 --> 00:10:35,996 It's given rise to a number of different tools and solutions and ways of working where lawyers and other legal professionals can automate some of this repetitive work, which in 107 00:10:35,996 --> 00:10:40,236 turn means they don't have to spend as much time doing it. 108 00:10:40,236 --> 00:10:47,560 theoretically, you don't have to bill as much time for it either, which means that clients can pay less for the same work. 109 00:10:48,376 --> 00:10:49,086 Yeah. 110 00:10:49,086 --> 00:10:54,626 And I think AI has shined a new kind of light on this. 111 00:10:54,626 --> 00:11:11,829 you know, prior to AI, there really wasn't a ton of tools out there automation wise, other than things like, know, CLM solutions and, you know, document automation and things like 112 00:11:11,829 --> 00:11:12,479 that. 113 00:11:12,479 --> 00:11:18,082 I think AI is, is creating a little bit more pressure. 114 00:11:18,178 --> 00:11:22,780 for law firms to think of alternative paths. 115 00:11:22,860 --> 00:11:29,282 I see on the vendor side, so we've been selling into legal since 2008, so 16 years. 116 00:11:29,303 --> 00:11:36,916 I've seen a number, we've had them working for us, lawyers who just decided to jump out and pursue other paths. 117 00:11:36,916 --> 00:11:44,429 And KM, some go into marketing, some go on the vendor side, some go in-house. 118 00:11:44,429 --> 00:11:47,310 I think, what's your perspective on 119 00:11:47,938 --> 00:11:49,473 those, those different paths. 120 00:11:49,473 --> 00:11:53,074 mean, that, that sounds like that was the route you took. 121 00:11:54,298 --> 00:11:55,889 So I think a couple of things. 122 00:11:55,889 --> 00:12:10,140 One, there are a plethora of paths that are available now, or lawyers and other legal professionals pursue, thanks to technology and also thanks to differentiated client 123 00:12:10,140 --> 00:12:10,940 demands. 124 00:12:10,940 --> 00:12:12,662 So I think that is one thing. 125 00:12:12,662 --> 00:12:21,748 Two, I think that certainly the rise of genera of AI has opened the door to 126 00:12:22,212 --> 00:12:29,315 the need for people with different skill sets, but who want to help and or work in the legal space. 127 00:12:29,315 --> 00:12:39,319 You know, we need people who can help with developing products, with implementing those products, with connecting those products with other ones that law firms or legal partners 128 00:12:39,319 --> 00:12:40,659 already use. 129 00:12:40,800 --> 00:12:50,233 And then perhaps most importantly, there's a growing need for people who can help connect legal departments and law firms with the right technology as well, because we're all busy 130 00:12:50,233 --> 00:12:52,304 and we need experts who can help us. 131 00:12:52,304 --> 00:13:01,832 sort of connect the dots and figure out A, what our pain points and problems are, and then B, using that information, evaluate potential solutions which may or may not be 132 00:13:01,832 --> 00:13:02,913 tech-based. 133 00:13:02,913 --> 00:13:14,783 So that has certainly given rise to, I think, a number of different types of roles and jobs and industries that now exist all around the larger legal ecosystem. 134 00:13:14,923 --> 00:13:21,006 And I think we'll continue to see that sort of sector of the market grow. 135 00:13:21,006 --> 00:13:28,770 because of generative AI growing more powerful, but also because of technology itself evolving and being able to do more. 136 00:13:29,314 --> 00:13:29,974 Yeah. 137 00:13:29,974 --> 00:13:35,107 So we are, uh, you know, we currently have an intranet offering that's very well established. 138 00:13:35,107 --> 00:13:41,551 We're launching an extranet product in Q1 that's going to help bridge that gap. 139 00:13:41,551 --> 00:13:51,386 You know, the predominant player in that space is HighQ They're fairly well established, but there hasn't been a ton of innovation either on the intranet or extranet side in many 140 00:13:51,386 --> 00:13:52,187 years. 141 00:13:52,187 --> 00:13:53,878 I think there's a lot of opportunity. 142 00:13:53,878 --> 00:13:57,932 You know, when I look at how firms deploy HighQ in 143 00:13:57,932 --> 00:14:01,803 many cases it's as a glorified file share. 144 00:14:02,284 --> 00:14:15,069 There seems to be a reluctance on the law firm's part to share, or maybe it's, you know, there isn't the appetite on the inside council side to share things like, you know, matter 145 00:14:15,069 --> 00:14:20,741 billing detail, you know, actual to budget information about the legal team. 146 00:14:20,741 --> 00:14:23,173 Usually it's a lot of file sharing. 147 00:14:23,173 --> 00:14:26,914 We're putting our chips on the table and 148 00:14:27,238 --> 00:14:37,350 embedding that law firm clients want more than just work product being shuttled through a portal. 149 00:14:38,071 --> 00:14:40,704 Is that your perspective as well? 150 00:14:41,776 --> 00:14:54,920 So I certainly think that there is a tendency, and this is, I think, reflective of the fact that oftentimes law firms and or legal departments don't put enough thought into 151 00:14:54,920 --> 00:15:06,692 really thoroughly understanding the problem and or sort of getting ready for the use of a new tool where they go after a tool like HighQ or something else. 152 00:15:06,692 --> 00:15:17,277 but then don't fully implement it, don't fully use it to its full capabilities because of the fact that they weren't perhaps ready for it, or perhaps they have a culture that's not 153 00:15:17,277 --> 00:15:26,381 fully supportive and on board with this tool, or they haven't really understood exactly what the problem is and they went after something that solves perhaps the problem in part 154 00:15:26,381 --> 00:15:27,781 but not in whole. 155 00:15:27,822 --> 00:15:33,614 So there are a lot of different factors at play that I think influence how a solution 156 00:15:33,700 --> 00:15:37,902 that is purchased and then put into places actually used or not used. 157 00:15:37,902 --> 00:15:48,628 And that speaks to, think that there is this tendency, ironically actually if you think about it, considering lawyers often are thought of as being so skeptical of shiny kin 158 00:15:48,628 --> 00:15:56,823 syndrome, going after a shiny new piece of tech because it exists and they've heard someone else uses it and they want to use it too, when in fact there may or may not be the 159 00:15:56,823 --> 00:15:58,193 right solution for them. 160 00:15:58,193 --> 00:16:03,516 So certainly just because a tool exists and has existed, 161 00:16:03,568 --> 00:16:14,648 or is being used by someone doesn't necessarily mean at all that it's the right solution for you or even in the ballpark of what you should be using, which ends up leading to you 162 00:16:14,648 --> 00:16:21,648 purchasing a solution that then ends up sitting on shelf somewhere, hypothetically speaking, and not being really used. 163 00:16:21,648 --> 00:16:23,928 And that's just a real shame. 164 00:16:23,928 --> 00:16:32,298 And it's not just a shame because it's not being used, but it's also a shame because then it impedes further efforts to implement future technology because 165 00:16:32,400 --> 00:16:36,473 People think back, well, we bought this tool and now he uses it. 166 00:16:36,473 --> 00:16:41,528 So why should we spend money on another tool that likely is going to end up also not being used? 167 00:16:41,794 --> 00:16:42,194 Yeah. 168 00:16:42,194 --> 00:16:44,575 Or heavily underutilized. 169 00:16:44,915 --> 00:16:49,906 Yeah, that absolutely influences buying patterns and motivation. 170 00:16:49,906 --> 00:16:56,318 We've, we've seen that before where, you know, firms have made a big investment and it not work out. 171 00:16:56,318 --> 00:17:02,100 And then, you know, there's a reluctance to, um, to make further investment. 172 00:17:02,360 --> 00:17:05,621 Well, uh, talk a little bit about, legal ops. 173 00:17:05,621 --> 00:17:08,962 Like how did you become, um, 174 00:17:09,324 --> 00:17:14,811 You know, an advocate I see you post quite a bit about the area. 175 00:17:14,811 --> 00:17:18,696 Like how did you become a legal ops advocate? 176 00:17:19,568 --> 00:17:32,768 So I think it stems from the fact that I have long seen this disconnect between technology and law and legal operations really is that bridge between the two worlds. 177 00:17:32,768 --> 00:17:37,108 And it also bridges the legal world, the tech world, and the business world together. 178 00:17:37,108 --> 00:17:45,656 And so that's why I'm a big advocate because legal operations really brings those worlds together and helps ensure that technology 179 00:17:45,722 --> 00:17:50,434 fits into the right processes which then support and enable the business. 180 00:17:50,615 --> 00:18:00,420 And they look at it and really these people are pretty amazing because it's not just a matter of putting in place and evaluating technology, it's also a matter of ensuring that 181 00:18:00,420 --> 00:18:12,097 the technology works well, ensuring that the processes that exist support technology, ensuring that the business and all its various functions and units understands and plays 182 00:18:12,097 --> 00:18:14,800 well with existing tools and future tools and 183 00:18:14,800 --> 00:18:16,860 sort of maintaining those relationships. 184 00:18:16,860 --> 00:18:28,060 So if you think about it, because of that multifaceted role that legal ops plays, it requires people who have a diverse skill set that is, you know, really kind of crosses 185 00:18:28,060 --> 00:18:31,260 over into a variety of traditional areas. 186 00:18:31,260 --> 00:18:40,680 And that I think is exciting because I've always been someone who's been a big fan of multidisciplinary learning and action and legal ops really epitomizes that. 187 00:18:40,940 --> 00:18:48,659 Yeah, you know, I've seen you write about the misconceptions around required qualifications. 188 00:18:48,659 --> 00:18:54,405 And I think you had a post a while back about some of these legal ops roles requiring a JD. 189 00:18:54,405 --> 00:19:02,644 Um, you know, what, what, sort of background really do you need to be effective in a legal ops role? 190 00:19:03,898 --> 00:19:13,977 So, you know, I think that having a JD can potentially help you in a legal ops role, but it's not a necessary requirement at all. 191 00:19:13,977 --> 00:19:23,084 It really depends very much on the type of legal ops role that you're looking to fill and the type of environment and culture that you have in place. 192 00:19:23,285 --> 00:19:29,060 I think that legal ops in general, you you need to have a quantitative and a qualitative background. 193 00:19:29,060 --> 00:19:31,696 So you need to be familiar with numbers and metrics. 194 00:19:31,696 --> 00:19:43,136 but you also need to be really good at evaluating general trends and relationships and understand people both from a emotional as well as a business perspective. 195 00:19:43,136 --> 00:19:46,066 And you really need to kind of understand also technology. 196 00:19:46,066 --> 00:20:00,056 So you need to have some degree of technology aptitude and familiarity and be sort of well connected enough to understand different technologies and how they will work with one 197 00:20:00,056 --> 00:20:00,760 another. 198 00:20:00,760 --> 00:20:04,443 in the context of a business that's seeking to grow and evolve. 199 00:20:04,724 --> 00:20:12,270 Which means that you really need to come at it from a pretty diverse background and have exposure to all these areas. 200 00:20:12,270 --> 00:20:22,499 The good news is like with any role you can learn on the job but at the same time you want to come into it understanding the full nature of the role, its demands and its evolving 201 00:20:22,499 --> 00:20:25,151 demands before you jump over. 202 00:20:25,151 --> 00:20:28,336 But that being said, JD is 203 00:20:28,336 --> 00:20:32,255 by no means a guarantee of success in legal ops at all. 204 00:20:32,255 --> 00:20:43,724 It just is sort of a, I'd say, sometimes a helpful background to have, but definitely not at all helpful in all respects or by any means should be a requirement. 205 00:20:44,110 --> 00:20:44,460 Yeah. 206 00:20:44,460 --> 00:20:46,440 And you know, if you look at like Dr. 207 00:20:46,440 --> 00:20:54,710 Larry Richard's research, like a JD can be a contra indicator to some of the qualities that you just described, like empathy. 208 00:20:55,650 --> 00:20:57,820 I'm going to have Dr. 209 00:20:57,820 --> 00:21:00,730 Richard on the podcast here soon. 210 00:21:00,810 --> 00:21:11,430 And you know, he, he has found that the average empathy score for partners hovers around the 41 percentile. 211 00:21:11,430 --> 00:21:12,266 So 212 00:21:12,266 --> 00:21:26,089 well below average and, you know, sticking somebody with low empathy in a role where you need to understand the perspective of people on the other side of the table, that may not 213 00:21:26,089 --> 00:21:27,230 be a good fit. 214 00:21:28,100 --> 00:21:29,801 Yeah, absolutely. 215 00:21:29,801 --> 00:21:43,722 that number doesn't surprise me at all because I think that law school in general tends to dehumanize people and tends to really focus people's attention and skills on kind of 216 00:21:43,722 --> 00:21:51,878 getting emotion out of the equation when in fact, I think that's quite unhelpful because human beings are naturally emotional creatures. 217 00:21:51,878 --> 00:21:54,468 And so the higher your EQ is, 218 00:21:54,468 --> 00:22:03,083 the better off you'll be in terms of managing people and understanding them and being able to get them to listen to you and want to develop a relationship with you. 219 00:22:03,083 --> 00:22:15,020 Because if you come off as cold and unsympathetic and unempathetic, who's really going to want to be around you or listen to you, especially if they're paying you money to help? 220 00:22:15,692 --> 00:22:16,242 Yeah. 221 00:22:16,242 --> 00:22:26,365 You know, we run, I mean, we've been, so we've been doing this a long time and over our history, over these 17 years now, we've done business with 110 AMLaw firms. 222 00:22:26,365 --> 00:22:30,086 So really good cross-sectional view in big law. 223 00:22:30,126 --> 00:22:34,267 And we've had to negotiate contracts with every one of these big law firms. 224 00:22:34,327 --> 00:22:45,196 And, um, we've had very different experiences and, um, some of them not good where, you know, we start out with a very adversarial, like, you know, 225 00:22:45,196 --> 00:22:54,428 because we've had to negotiate our contracts so many times with law firms, we come to the table with a very friendly document, right? 226 00:22:54,428 --> 00:22:56,739 We know what we're going to get pushed back on. 227 00:22:56,739 --> 00:22:59,430 And sometimes they will redline the whole thing. 228 00:22:59,430 --> 00:23:04,091 Sometimes they'll demand that we use the template, which we almost never say yes to. 229 00:23:04,091 --> 00:23:15,354 And we've actually walked away from deals because it happened recently where there was a, like you said, kind of a cold 230 00:23:15,436 --> 00:23:23,307 You know, this is a chess game as opposed to, Hey, this is where I establish a relationship with a partner. 231 00:23:23,307 --> 00:23:29,752 I mean, people who use our solution are going to be customers for seven to 10 years, almost certainly. 232 00:23:29,792 --> 00:23:33,854 And, know, starting off a relationship like that is not a healthy place. 233 00:23:33,854 --> 00:23:44,268 But, you know, again, I think that sometimes that's, that's the model and it doesn't set the stage for a productive ongoing relationships. 234 00:23:45,018 --> 00:23:46,208 Yeah, I agree. 235 00:23:46,208 --> 00:23:59,936 It doesn't surprise me to hear that, but I think it's just a function of just training and a function of this is just how we want to operate and how we want to do business. 236 00:23:59,936 --> 00:24:08,141 And it clearly works for some firms, but as you sort of indicated, it doesn't always work. 237 00:24:08,141 --> 00:24:14,344 And oftentimes that leads to unproductive attempts at building a relationship and 238 00:24:15,012 --> 00:24:22,294 that is just an unfortunate but not surprising side effect of that training I've spoken of. 239 00:24:22,424 --> 00:24:24,255 Yeah, agreed. 240 00:24:24,255 --> 00:24:31,940 So what do you see as the future of legal ops as a key function in law firms and legal departments? 241 00:24:31,940 --> 00:24:36,162 What do you see in looking through the looking glass? 242 00:24:37,540 --> 00:24:50,175 Yeah, I think that legal ops continues to play not just the role of the bridge, but the role of the educator in terms of helping to educate law firm personnel and legal 243 00:24:50,175 --> 00:25:02,831 department personnel on how to use existing tools better, as well as how to make better use of future tools that come down the pike, including generative AI. 244 00:25:02,831 --> 00:25:06,222 And I think that education, you know, 245 00:25:06,320 --> 00:25:11,620 sort of skill set really is going to be increasingly important as technology evolves ever faster. 246 00:25:11,620 --> 00:25:18,070 And as we've seen, generative AI, you know, just kind of came on the scene, is now taken off. 247 00:25:18,070 --> 00:25:29,900 And that just points to, how fast technology changes, but also how fast things can suddenly appear, which points to the need to adapt and the need to educate. 248 00:25:30,552 --> 00:25:39,048 You know, that's a great segue because we were going to talk a little bit about AI and legal practice and some of its potential and some of its limitations. 249 00:25:39,048 --> 00:25:52,277 And I think that you have probably done as good a job as anyone documenting the use cases that are compelling today. 250 00:25:52,857 --> 00:26:00,082 Just kind of at a high level, like how do you view the current capabilities of AI and legal work? 251 00:26:01,072 --> 00:26:07,262 So I think, I've talked about this a fair amount in the past and recently as well. 252 00:26:07,262 --> 00:26:19,912 And I think it starts with understanding that generative AI is here to augment and supplement, meaning that it is here to kind of make us be better at our jobs and do our 253 00:26:19,912 --> 00:26:26,952 jobs in ways that are more productive, not just for us, but for our clients as well. 254 00:26:26,952 --> 00:26:29,384 And that points to, I think, the 255 00:26:29,444 --> 00:26:36,089 the of both the current strengths as well as current limitations of generative solutions as exist currently. 256 00:26:36,350 --> 00:26:43,396 Because if you think about it, these solutions are by and large data driven. 257 00:26:43,396 --> 00:26:48,299 So you give it data, it provides you data, it creates data. 258 00:26:48,640 --> 00:26:58,778 So those types of tasks that are particularly data heavy and data dependent are going to be tasks that are best suited for these tools, as well as ones that are 259 00:26:58,778 --> 00:27:04,792 sort of standardizable routine and sort of ripe for automation. 260 00:27:04,792 --> 00:27:12,306 But as we've seen, these growing capabilities are allowing for the creation of new forms of knowledge and new ways to organize knowledge. 261 00:27:12,306 --> 00:27:19,090 So I think knowledge management as well becomes an area that I think General AI is going to help a lot with. 262 00:27:19,090 --> 00:27:26,448 And lawyers and legal professionals in general are not always the best at managing their vast array of knowledge. 263 00:27:26,448 --> 00:27:34,768 And so generative AI tools can really help with that, think, as well, which is something I pointed to in terms of some of the use cases that I've described in the past. 264 00:27:34,768 --> 00:27:39,198 But again, we need to realize that it's still early days for generative AI. 265 00:27:39,198 --> 00:27:43,078 It may seem like it's been here for a while at this point, but it hasn't. 266 00:27:43,078 --> 00:27:51,272 And we're really only still scratching the surface of what these tools will be capable of going forward. 267 00:27:51,714 --> 00:27:51,954 Yeah. 268 00:27:51,954 --> 00:27:55,937 So what do you see as like top use cases today? 269 00:27:55,937 --> 00:28:07,566 I mean, I've seen you list out many, but like for law firms that are really just getting started mapping out their AI strategy, which honestly, that's where most firms are. 270 00:28:07,566 --> 00:28:17,653 If you look at some of the surveys out there, it says otherwise, but based on my observations, those survey results are very aspirational. 271 00:28:18,434 --> 00:28:27,999 The Iltatech survey that just came out said that 74 % of law firms with 700 or more attorneys are using AI and business workflows. 272 00:28:28,179 --> 00:28:30,361 That seems totally aspirational to me. 273 00:28:30,361 --> 00:28:40,166 I think they're evaluating tools and maybe at that level, but I don't see a lot of practice of law use cases being implemented. 274 00:28:40,166 --> 00:28:48,010 So for a firm that's really starting to map out their journey, what do you think are the most compelling areas they should look at first? 275 00:28:48,548 --> 00:28:52,731 Well, my first instinct is to give a very lawyerly answer and say it depends. 276 00:28:52,731 --> 00:29:05,642 getting beyond that, think that, you know, generally I can be very helpful with respect to review documents and drawing up trends, whether it's briefs, whether it's case law 277 00:29:05,642 --> 00:29:16,400 research, draw out analytics to figure out the best lines of argument, the most applicable cases, the best way to structure arguments on the litigation side, on the transactional 278 00:29:16,400 --> 00:29:18,608 side, review of contracts. 279 00:29:18,608 --> 00:29:31,308 review of other documents to find sort of trends or clauses that seem to be the most effective for whatever purpose. 280 00:29:31,408 --> 00:29:34,828 Those types of tasks tend to be very effective for Gen.ai. 281 00:29:34,908 --> 00:29:44,868 I also think that they can help with on the IP side, patent drafting, patent review, patent design. 282 00:29:46,766 --> 00:29:56,369 Lastly, would say that generative value is very helpful with respect to intake of clients and kind of taking in that information and then directing that information to whomever 283 00:29:56,369 --> 00:30:03,971 needs to see it to open up a case file or review a case file or what have you. 284 00:30:03,971 --> 00:30:10,043 So those are types of the use cases that I think are right now really particularly useful. 285 00:30:10,323 --> 00:30:14,614 But as you mentioned yourself, anecdotally in my experience as well, I've 286 00:30:14,628 --> 00:30:20,382 you know, seeing that firms right now are kind of still in their exploratory phase where they're sort of exploring gen. 287 00:30:20,382 --> 00:30:30,118 AI, but they haven't fully integrated into their practice per se, unless we're one of these huge firms where they have developed their own in-house model and are all in on it. 288 00:30:30,118 --> 00:30:34,400 But that's because they have the time, the money and the personnel to be able to do it. 289 00:30:34,744 --> 00:30:35,415 Yeah. 290 00:30:35,415 --> 00:30:47,883 You know, I think that, as is typical with many new tech trends, novel tech trends is there's a, the Gartner hype curve man plays out almost every time perfectly. 291 00:30:47,883 --> 00:31:00,111 And you know, you've got the peak of inflated expectations and I feel like we've kind of crossed over that peak and we're now heading towards the trough of disillusionment because 292 00:31:00,111 --> 00:31:02,652 I think we came out way too optimistic. 293 00:31:02,652 --> 00:31:04,014 You know, the, 294 00:31:04,014 --> 00:31:09,434 the Goldman report that 44 % of legal tasks could be automated by generative AI. 295 00:31:09,434 --> 00:31:14,294 think that was ambitious and certainly based on where the technology is today. 296 00:31:14,294 --> 00:31:30,974 I think the Stanford study did a really good job highlighting a lot of the shortcomings of current state technology, its inability to distinguish between legal actors and its 297 00:31:30,974 --> 00:31:33,606 inability to identify holdings and 298 00:31:33,787 --> 00:31:39,508 Um, you know, I, did you have a chance to look at that Stanford study? 299 00:31:40,080 --> 00:31:42,120 Yeah, I looked at that study. 300 00:31:42,300 --> 00:31:46,320 you know, I've looked at all sorts of surveys and reports on, on Gen. 301 00:31:46,320 --> 00:31:56,200 think the bottom line is, you know, with respect to the hype curve and the study, is it just points to something I said earlier, which is that we're in the early days of using 302 00:31:56,200 --> 00:31:56,570 Gen. 303 00:31:56,570 --> 00:31:59,980 AI, it's both powerful and limited. 304 00:31:59,980 --> 00:32:03,720 And we just need to be realistic about its potential. 305 00:32:03,720 --> 00:32:09,264 And I think that one of the issues I think needs to be kind of dealt with. 306 00:32:09,264 --> 00:32:18,504 and addressed is the fact that artificial intelligence, it's a phrase that carries a lot of weight, carries a lot of sort of built-in assumptions. 307 00:32:18,504 --> 00:32:25,514 And at the end of the day, we're not really talking about intelligence in the way that you and I and most humans think about intelligence. 308 00:32:25,514 --> 00:32:35,964 We're thinking about it when it comes to JNI, we're considering, you know, it's really in terms of just coding and its ability to analyze data faster than we can. 309 00:32:35,964 --> 00:32:38,118 So in that sense, it's intelligent. 310 00:32:38,202 --> 00:32:43,184 but it's not intelligent in the way that you and I think or operate or are aware of ourselves. 311 00:32:43,184 --> 00:32:56,376 So really, I think we have to kind of take that in mind when we consider artificial intelligence as a concept, particularly given that itself is not a new technology. 312 00:32:56,376 --> 00:32:58,320 It's been around for a long time. 313 00:32:58,320 --> 00:32:59,941 Generative AI is new. 314 00:32:59,941 --> 00:33:07,394 Its ability to create things is new, but its ability to analyze boatloads of data and provide analytics is not a new thing. 315 00:33:07,408 --> 00:33:16,108 Um, I often use this analogy where, know, you can think about it when we were sending people to the moon, when we did that sort of thing, that would not have been possible 316 00:33:16,108 --> 00:33:19,968 without rudimentary AI on huge computers. 317 00:33:19,968 --> 00:33:31,088 And we've come a long way from there, but at the same time, you know, we're, we're definitely now again, harking back to those days in terms of use of data and people need 318 00:33:31,088 --> 00:33:36,878 to just, I think, and go into sort of learning about gene AI with eyes wide open and understand that. 319 00:33:36,878 --> 00:33:40,917 Like any technology, it's powerful and limited. 320 00:33:41,890 --> 00:33:48,154 Yeah, you know, there's been a lot of debate over whether generative AI can reason. 321 00:33:48,495 --> 00:33:53,499 And I am on in the camp of that it cannot. 322 00:33:53,499 --> 00:34:00,104 And I think it's it can create the illusion of, of human reasoning. 323 00:34:00,104 --> 00:34:04,627 But there was a, I don't know if you saw it, it literally just came out maybe two weeks, maybe three weeks ago. 324 00:34:04,627 --> 00:34:08,770 Now it was the end of October from, um, the Apple AI team. 325 00:34:09,154 --> 00:34:23,720 where they took a test, the GSM 8K, it's the grade school math test, and they changed some very, they changed the problems, their word problems, and they changed them in very 326 00:34:23,720 --> 00:34:25,061 trivial ways. 327 00:34:25,061 --> 00:34:33,505 One way that they changed it was they would put a sentence into the word problem that had nothing to do with calculating the answer. 328 00:34:33,505 --> 00:34:35,625 You one example was, 329 00:34:37,122 --> 00:34:48,696 where they had a list of prices today and they said inflation has increased by 10 % each year over the last three years, completely through all the models off. 330 00:34:48,696 --> 00:34:55,428 I think it was like a 65 % drop in performance just by throwing an irrelevant detail in there. 331 00:34:55,428 --> 00:35:00,109 Another way that they changed the problems, they changed the names, right? 332 00:35:00,109 --> 00:35:02,730 So instead of Sonya, it would be Colin. 333 00:35:03,768 --> 00:35:10,621 but they did so consistently so that a person looking at that would see that, there's an irrelevant sentence in there or the, the name changed. 334 00:35:10,621 --> 00:35:16,344 But really what it demonstrated is that AI does not understand the problems that it's solving. 335 00:35:16,344 --> 00:35:18,465 It's predicting the next token. 336 00:35:18,465 --> 00:35:22,167 So with that limitation, we have to keep that in mind. 337 00:35:22,167 --> 00:35:26,583 There's still a lot of debate about whether or not they can AI can reason. 338 00:35:26,583 --> 00:35:26,849 don't know. 339 00:35:26,849 --> 00:35:28,660 Do you have any perspective on that? 340 00:35:29,264 --> 00:35:32,804 So I have a couple, I think, thoughts on that. 341 00:35:32,804 --> 00:35:34,728 One is that... 342 00:35:36,558 --> 00:35:41,091 GNI is as good as the data it's been provided with and been trained on. 343 00:35:41,091 --> 00:35:43,382 So there's that, I think, first and foremost. 344 00:35:43,382 --> 00:35:54,960 Secondly, think that it can learn, but only based off of data you give it. 345 00:35:55,280 --> 00:36:01,464 And lastly, it's basically an advanced pattern recognition device. 346 00:36:01,518 --> 00:36:04,209 So it recognizes patterns in data. 347 00:36:04,209 --> 00:36:15,594 And if you change something about a pattern that you give it, that can sometimes throw it completely off because it just completely doesn't match up with the pattern that it had 348 00:36:15,594 --> 00:36:20,816 been using before, which goes to the word problem that you were just describing. 349 00:36:21,336 --> 00:36:24,838 So I think that's important to keep in mind with these tools. 350 00:36:25,118 --> 00:36:30,390 And their ability to reason is less a function of sort 351 00:36:30,702 --> 00:36:40,655 reasoning the way you and I think about reasoning and more a function of just the data it has, the data you've given it, and making those two match up in some way. 352 00:36:40,655 --> 00:36:42,936 And so it will get better for sure. 353 00:36:42,936 --> 00:36:49,058 And it will have the ability to reason a little more on its own. 354 00:36:49,058 --> 00:36:53,539 But data is the big impediment right now. 355 00:36:53,780 --> 00:36:55,340 It needs more data. 356 00:36:55,755 --> 00:36:56,055 Yeah. 357 00:36:56,055 --> 00:37:07,931 There's some, know, like the O one model with the chain of thought and there, there are some mechanisms they're leveraging to improve the reasoning, but it's still in my opinion, 358 00:37:07,931 --> 00:37:17,025 creating the illusion of reasoning as opposed to what us humans think is like reasoning their way to a novel approach to a mathematical proof. 359 00:37:17,025 --> 00:37:19,966 For example, like AI can't do that. 360 00:37:20,012 --> 00:37:20,523 Right. 361 00:37:20,523 --> 00:37:29,069 Um, if it's not in the training set, it's not going to be able to reason its way to a, to a new approach to solving a mathematical proof. 362 00:37:29,110 --> 00:37:35,465 But what are your thoughts about like, um, general versus legal specific AI models? 363 00:37:35,465 --> 00:37:38,788 You know, you've got the Harveys and the Paxton's of the world. 364 00:37:38,788 --> 00:37:45,104 There's lots of players out there that are building, uh, legal specific solutions. 365 00:37:45,104 --> 00:37:47,904 How, how important are 366 00:37:47,904 --> 00:37:55,766 Is it to have a especially trained model versus kind of the general foundational models that are out there today? 367 00:37:56,848 --> 00:37:59,768 I think it's a context driven decision. 368 00:37:59,768 --> 00:38:13,168 If you are operating a law firm or legal department and you have very specific needs and concerns around security, then it makes more sense to try to build a legal specific model 369 00:38:13,168 --> 00:38:16,188 or use one that's specifically for legal. 370 00:38:16,208 --> 00:38:25,796 If you're a legal tech company or a larger company or just company that's not legal specific but supports in some ways or interacts with the legal industry, 371 00:38:25,796 --> 00:38:28,967 then I think you can use some of these other models or partner with them as well. 372 00:38:28,967 --> 00:38:40,262 So I don't think really it's so much a debate as it is really just a matter of what your needs are, what your problems are, and letting those define kind of the type of solution 373 00:38:40,262 --> 00:38:41,623 you want to have. 374 00:38:42,043 --> 00:38:52,658 That being said, a lot of law firms I've talked to have certainly been very eager to have models that are very legal specific because of their concerns around accuracy and 375 00:38:52,658 --> 00:38:53,738 security. 376 00:38:54,274 --> 00:38:54,894 Yeah. 377 00:38:54,894 --> 00:38:57,575 I mean, there's people placing really big bets. 378 00:38:57,575 --> 00:39:08,458 know, Harvey's latest, uh, series C put their valuation at $1.5 billion with approximately 30 million in revenue. 379 00:39:08,458 --> 00:39:19,581 So, you know, the, the, the things that have to happen in order for those bets to pay off the way a venture fund needs them to are quite extraordinary. 380 00:39:19,581 --> 00:39:23,292 Um, you know, the law firm market itself is relatively small. 381 00:39:23,292 --> 00:39:24,332 There's only, 382 00:39:24,650 --> 00:39:35,139 there's no official numbers on this, I, by my calculations, there's about 500 law firms in the world that are over a hundred attorneys, maybe 600, but certainly not more than that. 383 00:39:35,139 --> 00:39:38,942 Um, but I know that they're going to move into, into other areas. 384 00:39:38,942 --> 00:39:50,012 So, you know, it feels like, I don't know if this is your perspective as well, that there is a, there's a lot of money chasing these opportunities in the marketplace. 385 00:39:50,012 --> 00:39:51,993 That's really driving up valuations. 386 00:39:51,993 --> 00:39:53,094 Like that's a, 387 00:39:53,102 --> 00:40:02,745 30 million to 1.5, but that's a 50 X multiple for a company that has really not had a clear strategy. 388 00:40:02,745 --> 00:40:16,279 You know, they tried a raise to acquire VLex and you know, they've been kind of operating in stealth mode and you know, so to put it in their series B was 715 million seven months 389 00:40:16,279 --> 00:40:16,659 earlier. 390 00:40:16,659 --> 00:40:18,810 So they doubled in value in seven months. 391 00:40:18,810 --> 00:40:19,832 Like what 392 00:40:19,832 --> 00:40:24,120 The things that have to happen for a company to double its valuation are quite extraordinary. 393 00:40:24,120 --> 00:40:24,661 So I don't know. 394 00:40:24,661 --> 00:40:26,944 Do you, do feel like we're in a bubble right now? 395 00:40:28,144 --> 00:40:31,024 I think there definitely are signs that a bubble exists. 396 00:40:31,024 --> 00:40:40,524 think there's a lot of just optimism and lot of hype around AI as has always existed with respect to other types of technology. 397 00:40:40,524 --> 00:40:53,864 I think that, you know, where reality will set in over, you know, like six months to a year and perhaps even shorter than that as technology evolves and gets in at the same 398 00:40:53,864 --> 00:40:57,184 time, it gets better, also continues to show its limitations. 399 00:40:57,264 --> 00:41:07,364 But I do think that, you know, there's been a lot of money throwing at AI, I think, because, again, people were very excited and thought there was all this potential and that 400 00:41:07,364 --> 00:41:09,624 potential was going to be realized right off the bat. 401 00:41:09,624 --> 00:41:16,684 When in fact, as has been the case with all sorts of other technologies, is the potential is realized over time. 402 00:41:17,144 --> 00:41:22,084 Sometimes a long period of time, sometimes a shorter period of time, but over time, nevertheless. 403 00:41:22,424 --> 00:41:25,942 And I think that's going to continue to be a theme going forward. 404 00:41:26,060 --> 00:41:34,081 So I do think that these large investments sometimes distorts the perception and the reality of generative AI. 405 00:41:34,520 --> 00:41:35,071 Yeah. 406 00:41:35,071 --> 00:41:48,943 You know, and another thing that I would be considering if I were an investor in that space is, you know, the first mover, the first successful company is rarely the long-term 407 00:41:48,943 --> 00:41:50,504 winner in the marketplace. 408 00:41:50,504 --> 00:41:56,870 mean, ask Netscape, you know, ask Lotus one, two, three, ask WordPerfect, ask BlackBerry. 409 00:41:56,870 --> 00:42:02,474 There's countless examples where, you know, these companies paved the way for the real winner. 410 00:42:02,582 --> 00:42:07,364 in the space who came later or all the search engines relative to Google, right? 411 00:42:07,364 --> 00:42:12,525 There was 50 of them out there, Alta Vista and Yahoo and Excite. 412 00:42:12,665 --> 00:42:14,686 So yeah, I don't know. 413 00:42:14,906 --> 00:42:22,748 It seems like to really throw that much investment this early in the game. 414 00:42:22,748 --> 00:42:23,479 Cause I agree with you. 415 00:42:23,479 --> 00:42:27,070 I think we're in the top of the first inning in the AI baseball game. 416 00:42:27,070 --> 00:42:28,160 I really do. 417 00:42:28,484 --> 00:42:30,185 Yeah, I think that's true. 418 00:42:30,185 --> 00:42:45,195 And I remember, you know, this dates me a little bit, you know, Netscape Navigator was a huge browser back in the day and was very popular and was kind of a legal leader alongside 419 00:42:45,195 --> 00:42:47,637 Yahoo and the search engine space. 420 00:42:47,637 --> 00:42:57,904 But both, I think made a number of decisions that led to them, you know, falling by the wayside in some ways with respect to their respective segments. 421 00:42:57,904 --> 00:43:03,744 Um, and so it'll be interesting to see if that repeats again in this case. 422 00:43:03,744 --> 00:43:09,824 I'm not, you know, I think the jury is still out a little bit, but that definitely remains big danger for sure. 423 00:43:09,824 --> 00:43:18,814 Um, but it's been interesting just to see Google and Apple take a far slower approach to incorporation use of AI. 424 00:43:18,814 --> 00:43:26,320 And I think that's a reflection of not just them being behind the eight ball a little bit, but also a matter of them. 425 00:43:26,320 --> 00:43:36,920 I think perhaps having a better understanding of the limitation of AI and therefore taking a more pragmatic, practical approach where they can roll it out, but in piecemeal, as 426 00:43:36,920 --> 00:43:39,340 opposed to rolling it all out all at once. 427 00:43:39,682 --> 00:43:48,967 Yeah, I mean, you know, with search GPT like Google and perplexity, you know, I use Google less and less these days. 428 00:43:48,967 --> 00:43:50,698 It's still my default search engine. 429 00:43:50,698 --> 00:44:01,624 actually made perplexity my default search engine for a little while, but I still I still type stuff that I need a Google result for, like the name of a business and I want to get 430 00:44:01,624 --> 00:44:04,556 the phone number or I want to see a map of it. 431 00:44:04,556 --> 00:44:09,056 But it is getting closer and closer to that tipping point for me where 432 00:44:09,056 --> 00:44:12,248 All I need is perplexity or now search GPT. 433 00:44:12,248 --> 00:44:15,180 you know, these, I agree with you actually. 434 00:44:15,180 --> 00:44:22,375 think Google, you know, Google has been investing much more so than Apple. 435 00:44:22,616 --> 00:44:30,960 Google has been investing in the technology, but has been much more measured in its rollout, it seems. 436 00:44:30,960 --> 00:44:32,692 yeah, I think that's accurate. 437 00:44:32,692 --> 00:44:46,343 And Apple, I think, I think Apple has been a little distracted, I think, in part by the role of the virtual reality Apple vision, which didn't do well. 438 00:44:46,343 --> 00:44:48,054 And I was not surprised. 439 00:44:48,074 --> 00:44:50,358 And not just because of its high cost. 440 00:44:50,358 --> 00:45:00,494 I high cost is something that goes hand in hand with Apple, but more just because just don't think that technology is where it needs to be for it to be super usable right now. 441 00:45:01,576 --> 00:45:04,459 So yeah, it'll be interesting to how things play out. 442 00:45:04,680 --> 00:45:12,318 But I agree with you, we're definitely in the first inning and I think that's going to be important to keep in mind as we go forward. 443 00:45:12,450 --> 00:45:14,091 Yeah, absolutely. 444 00:45:14,091 --> 00:45:16,633 Well, this has been a really fun conversation. 445 00:45:16,974 --> 00:45:20,837 I appreciate you spending a little bit of time with us today. 446 00:45:20,837 --> 00:45:25,331 How, before we go, you put out some great content. 447 00:45:25,331 --> 00:45:26,392 I really like your stuff. 448 00:45:26,392 --> 00:45:40,394 I think you do a good job creating a human element to, you know, what sometimes is a non-human platform, which is LinkedIn. 449 00:45:40,394 --> 00:45:41,378 You people don't 450 00:45:41,378 --> 00:45:44,616 typically share their political views or their personal challenges. 451 00:45:44,616 --> 00:45:46,712 And I think you do a good job with that. 452 00:45:46,712 --> 00:45:50,932 How do, how do folks who want to follow your content find you? 453 00:45:51,536 --> 00:45:54,578 So there are two key ways to do that. 454 00:45:54,578 --> 00:45:57,820 One is by following me on LinkedIn under my name. 455 00:45:58,021 --> 00:46:00,363 I feel like it almost goes without saying. 456 00:46:00,363 --> 00:46:04,465 And then secondly, visit my website, colonistlevy.com. 457 00:46:05,286 --> 00:46:13,302 And of course, I'd be remiss if I didn't mention checking out my book, The Legal Tech Ecosystem, available on Amazon worldwide. 458 00:46:13,890 --> 00:46:15,341 Yep, I'm an owner of it. 459 00:46:15,341 --> 00:46:17,393 I've enjoyed, I've enjoyed reading it. 460 00:46:17,393 --> 00:46:18,354 I read it in pieces. 461 00:46:18,354 --> 00:46:22,707 I don't have the attention span to go cover to cover, but I have read it. 462 00:46:22,707 --> 00:46:27,280 And in fact, I read your section on legal ops and I learned quite a bit. 463 00:46:28,101 --> 00:46:28,852 So good stuff. 464 00:46:28,852 --> 00:46:30,553 Well, I appreciate you joining. 465 00:46:30,553 --> 00:46:34,636 Are you, are you going to TLTF in a couple of weeks? 466 00:46:35,170 --> 00:46:37,183 Unfortunately, I will not be there now. 467 00:46:37,292 --> 00:46:40,167 Yeah, but maybe we'll. 468 00:46:40,750 --> 00:46:41,681 Yeah, it is. 469 00:46:41,681 --> 00:46:42,644 It's a nice play. 470 00:46:42,644 --> 00:46:48,886 They're doing it in Key Biscayne this year, so South Florida is not a bad place to be in December. 471 00:46:48,886 --> 00:46:57,908 no, I used to have family and keep a skin so it's a nice area but it is a little late in the year with holidays. 472 00:46:58,380 --> 00:46:59,093 Yeah. 473 00:46:59,093 --> 00:46:59,786 Well, good stuff. 474 00:46:59,786 --> 00:47:03,690 I appreciate you joining and maybe we'll see you at legal week. 475 00:47:03,940 --> 00:47:05,753 Thanks again, thanks so much. 476 00:47:05,826 --> 00:47:07,211 All right, take care. 477 00:47:07,556 --> 00:47:08,220 Bye. 00:00:04,364 Colin Levy, how are you this morning? 2 00:00:04,364 --> 00:00:06,208 I'm doing well, how are you? 3 00:00:06,387 --> 00:00:08,174 I am doing great. 4 00:00:08,174 --> 00:00:10,521 I appreciate you joining us today. 5 00:00:11,247 --> 00:00:12,618 Thanks for having me. 6 00:00:12,642 --> 00:00:18,427 Yeah, you and I, I've been consuming your content on LinkedIn for a while now. 7 00:00:18,427 --> 00:00:24,982 And when you and I got connected, I thought it was a great opportunity to sit down and have a chat. 8 00:00:24,982 --> 00:00:27,955 And you write about a bunch of different topics. 9 00:00:27,955 --> 00:00:31,778 You seem to have a passion for legal operations. 10 00:00:31,778 --> 00:00:37,462 And so we're going to get into some of that stuff today, but before we do, 11 00:00:37,738 --> 00:00:39,960 Um, let's, let's do a quick introduction. 12 00:00:39,960 --> 00:00:52,450 So you started your journey in big law and lit support and you moved to some in-house roles, uh, after law school and you're currently director of legal at Malbec. 13 00:00:52,450 --> 00:00:53,470 Is that right? 14 00:00:53,584 --> 00:00:56,726 Correct, Director of Legal and Evangelist at Malibu. 15 00:00:57,058 --> 00:00:57,470 Okay. 16 00:00:57,470 --> 00:00:57,880 So yeah. 17 00:00:57,880 --> 00:01:00,744 So tell us like who you are, what you do and where you do it. 18 00:01:01,392 --> 00:01:04,354 Sure, so I am a lawyer. 19 00:01:04,354 --> 00:01:05,885 I am Malbec's head lawyer. 20 00:01:05,885 --> 00:01:13,740 Malbec is a contract bicycle management solution for large businesses. 21 00:01:13,901 --> 00:01:29,892 I am, as their director of legal and evangelists, lead their legal efforts in terms of data privacy, negotiating agreements, assisting with other efforts that need legal eyes on 22 00:01:29,892 --> 00:01:30,572 them. 23 00:01:30,732 --> 00:01:46,967 In addition to that sort of area, I also contribute to blog posts, do webinars, podcasts, attend conferences, and basically help in any way that I can with Volbec's general selling 24 00:01:46,967 --> 00:01:48,398 and marketing efforts. 25 00:01:48,738 --> 00:01:50,539 And you're an author, correct? 26 00:01:50,796 --> 00:01:52,056 I am. 27 00:01:52,336 --> 00:02:04,220 I had my first book come out last year, The Legal Tech Ecosystem, a accessible story-based introduction to the world of legal tech. 28 00:02:04,220 --> 00:02:15,403 I also co-wrote with one of the co-founders of Malbec CLM for Dummies, a very brief high-level overview to what contract management is all about. 29 00:02:15,583 --> 00:02:18,884 I've also contributed chapters to various books. 30 00:02:19,136 --> 00:02:26,154 And or contribute blog posts what have you so writing is a big part of what I do and what I enjoy doing 31 00:02:27,246 --> 00:02:36,234 So you were in big law and now you're in-house, which is a common pattern. 32 00:02:36,234 --> 00:02:40,597 Many in-house lawyers made their way through big law at some point. 33 00:02:40,597 --> 00:02:46,432 But how has that journey been and what have you learned along the way? 34 00:02:47,514 --> 00:02:52,608 Well, my one and only time in big law was working as a paralel prior law school. 35 00:02:52,608 --> 00:03:00,733 And that experience was eye opening in some ways because it gave me a lot of insight into how law firms, big law firms operate. 36 00:03:00,994 --> 00:03:10,380 It also gave me insight into technology and how that even at that stage of my career was impacting the practice of law. 37 00:03:10,600 --> 00:03:16,244 So it was definitely interesting and eye opening, but also 38 00:03:16,580 --> 00:03:22,242 helped convince me that Big Law was not where I wanted to be after I graduated from law school. 39 00:03:22,323 --> 00:03:28,125 But I did want some work experience before I worked, before I went to law school, which I definitely got. 40 00:03:28,325 --> 00:03:32,367 And that experience, again, piqued my interest in technology. 41 00:03:32,467 --> 00:03:43,682 And I would say through law school and then after law school, I've always seen this evolving relationship between technology and the practice and business of law and thought. 42 00:03:44,240 --> 00:03:46,240 You know, this is an interesting space. 43 00:03:46,240 --> 00:03:47,260 It's evolving. 44 00:03:47,260 --> 00:03:53,740 It's one that I think is going to become increasingly important as technology evolves and plays a bigger role in our lives. 45 00:03:53,740 --> 00:04:05,580 And so I took it upon myself to initiate conversations with others who are either creating products in the space, who are talking about the technology and a lot of relationship, or 46 00:04:05,580 --> 00:04:10,120 who were quite frankly interested in learning about it as much as I was. 47 00:04:10,120 --> 00:04:12,516 And it was those conversations that then 48 00:04:12,516 --> 00:04:23,764 led me down the path of getting more interested in legal tech and then further down the road, producing my own content helped inspire and inform others about legal tech and it's, 49 00:04:24,145 --> 00:04:28,388 I think, importance in the world of law practice. 50 00:04:29,110 --> 00:04:29,590 Yeah. 51 00:04:29,590 --> 00:04:38,376 So the last time you and I spoke, we talked about some of the challenges in big law, specifically with work-life balance. 52 00:04:39,257 --> 00:04:46,022 I think we equated it to, there's some similarities to, on the investment banking side. 53 00:04:46,022 --> 00:04:54,047 I spent 10 years at Bank of America and had folks in the IB and it was grueling hours. 54 00:04:54,047 --> 00:04:58,730 In fact, think actually very tragically Bank of America had a 55 00:04:58,818 --> 00:05:13,927 had an investment banking associate pass away from what they think was a stress induced stroke, working 80 hours on a weekend to get something across the goal line during a deal. 56 00:05:13,927 --> 00:05:21,491 And they came out with some guidance to kind of protect and help that. 57 00:05:21,491 --> 00:05:27,194 when you read it, they don't put a hard stake in the ground. 58 00:05:27,618 --> 00:05:35,488 You know, it sounds like was it, was it the lack or challenges of work-life balance that made you realize the big law wasn't for you? 59 00:05:36,398 --> 00:05:37,979 Yeah, it was a couple of different things. 60 00:05:37,979 --> 00:05:41,671 was certainly the work-life balance not being in control of my schedule. 61 00:05:41,671 --> 00:05:45,273 That certainly was one influencing factor. 62 00:05:45,273 --> 00:05:59,921 I think another factor was I just didn't like big law environment, just the way that the culture was, the types of people that I saw and encountered were not people by and large 63 00:05:59,921 --> 00:06:06,084 that I wanted to kind of associate myself with or be with or have to manage or... 64 00:06:06,190 --> 00:06:07,941 have a relationship with. 65 00:06:08,601 --> 00:06:20,897 And then lastly, I think that, you I was always interested in kind of experimenting and pushing the envelope in terms of practice and business and how both impacted the legal 66 00:06:20,897 --> 00:06:21,717 industry as a whole. 67 00:06:21,717 --> 00:06:32,208 And while the law from life just seemed to be precluding some of that, you know, interest in exploration. 68 00:06:32,208 --> 00:06:38,017 It was just not something that I knew was going to jive with my own personality and my own business interests. 69 00:06:38,318 --> 00:06:38,948 Yeah. 70 00:06:38,948 --> 00:06:49,778 I mean, there's been a lot of, there's been a lot of scrutiny around and a lot of conversations around the billable hour requirements when attorneys, know, logging, were so 71 00:06:49,778 --> 00:06:51,478 info dash is a product company. 72 00:06:51,478 --> 00:06:56,198 Now we, we started our journey as a consulting organization. 73 00:06:56,198 --> 00:07:06,232 So we're very familiar with the billable hour and how many hours on the clock it takes to generate 40 hours of 74 00:07:06,232 --> 00:07:10,363 billable time a week and it's a lot, the number is a lot bigger than 40. 75 00:07:10,363 --> 00:07:19,986 And you know, if you're, if you have a 2000 hour billable quota, there's 52 weeks in a year, you get a two week vacation, 40 times 50 is 2000. 76 00:07:19,986 --> 00:07:28,589 So, you know, just maintaining your, your billable hour quota has to be an absolute grueling task. 77 00:07:28,589 --> 00:07:32,810 Um, I would imagine things are different on the in-house side. 78 00:07:33,300 --> 00:07:34,110 they absolutely are. 79 00:07:34,110 --> 00:07:45,695 Definitely don't have to worry about that and entering time, but it definitely, you know, brings me back to my days of working for that law firm and how I spent all this time 80 00:07:45,695 --> 00:07:47,996 entering my time in and it would never be right. 81 00:07:47,996 --> 00:08:00,252 And I was just looking to get paid and yet it was super hard to be paid on time because of just the almost absurd level of effort and time I had to put into entering into my time 82 00:08:00,252 --> 00:08:01,432 correctly. 83 00:08:01,868 --> 00:08:04,210 and it was, it was just ridiculous. 84 00:08:04,210 --> 00:08:17,979 Um, you know, think the bill Blower model as a whole, uh, is certainly resilient one and certainly one that seems very resistant to outside pressure, but it also promotes a, I 85 00:08:17,979 --> 00:08:30,992 would argue a unhealthy work-life balance and also promotes a sort of, you know, work every day and then work some more and then work some more, uh, which just isn't healthy. 86 00:08:30,992 --> 00:08:32,263 I'm not against work. 87 00:08:32,263 --> 00:08:33,003 like to work. 88 00:08:33,003 --> 00:08:34,714 I enjoy being busy. 89 00:08:34,714 --> 00:08:47,439 But I do think that we as human beings really need to make time for ourselves to ensure that we're listening to ourselves and that we're taking time to refresh ourselves and 90 00:08:47,459 --> 00:08:48,266 manage ourselves. 91 00:08:48,266 --> 00:08:58,224 Because if we don't do that, then we're really going down a path that where we're not going to able to ourselves, let alone help anyone else. 92 00:08:58,552 --> 00:09:00,302 Yeah. 93 00:09:00,303 --> 00:09:08,486 The billable hour is, you know, this is, mean, the whole AFA conversation has been going on for a really long time. 94 00:09:08,486 --> 00:09:14,148 And to your point, the billable hour seems to not want to die. 95 00:09:14,148 --> 00:09:19,811 You know, I've heard, you know, how much of that is really on the client side? 96 00:09:19,811 --> 00:09:28,365 I mean, I've heard mixed reviews in terms of how ready Inside Council is to embrace 97 00:09:28,365 --> 00:09:29,690 value-based billing. 98 00:09:29,690 --> 00:09:31,496 mean, what's your perspective on that? 99 00:09:32,474 --> 00:09:42,291 So I think that there is certainly a strong still feeling of clients have grown accustomed and used to billbower billing. 100 00:09:42,291 --> 00:09:51,538 But I also think that they are growing wise the fact that there are viable alternatives to it that they can be engaged in. 101 00:09:51,759 --> 00:09:58,883 And especially in an environment where costs are high for many, I think that 102 00:09:59,332 --> 00:10:11,007 simply asking the question of, you know, are there other ways to bill for this work is a perfectly good question and legitimate question to be asking and a good, and I think also 103 00:10:11,007 --> 00:10:16,500 points to the fact that a lot of the work that lawyers do is repetitive. 104 00:10:16,500 --> 00:10:24,183 It's not, you know, everything isn't always ad hoc or bespoke as much as a lot of lawyers claim that it is. 105 00:10:24,183 --> 00:10:26,096 And I think because of that, 106 00:10:26,096 --> 00:10:35,996 It's given rise to a number of different tools and solutions and ways of working where lawyers and other legal professionals can automate some of this repetitive work, which in 107 00:10:35,996 --> 00:10:40,236 turn means they don't have to spend as much time doing it. 108 00:10:40,236 --> 00:10:47,560 theoretically, you don't have to bill as much time for it either, which means that clients can pay less for the same work. 109 00:10:48,376 --> 00:10:49,086 Yeah. 110 00:10:49,086 --> 00:10:54,626 And I think AI has shined a new kind of light on this. 111 00:10:54,626 --> 00:11:11,829 you know, prior to AI, there really wasn't a ton of tools out there automation wise, other than things like, know, CLM solutions and, you know, document automation and things like 112 00:11:11,829 --> 00:11:12,479 that. 113 00:11:12,479 --> 00:11:18,082 I think AI is, is creating a little bit more pressure. 114 00:11:18,178 --> 00:11:22,780 for law firms to think of alternative paths. 115 00:11:22,860 --> 00:11:29,282 I see on the vendor side, so we've been selling into legal since 2008, so 16 years. 116 00:11:29,303 --> 00:11:36,916 I've seen a number, we've had them working for us, lawyers who just decided to jump out and pursue other paths. 117 00:11:36,916 --> 00:11:44,429 And KM, some go into marketing, some go on the vendor side, some go in-house. 118 00:11:44,429 --> 00:11:47,310 I think, what's your perspective on 119 00:11:47,938 --> 00:11:49,473 those, those different paths. 120 00:11:49,473 --> 00:11:53,074 mean, that, that sounds like that was the route you took. 121 00:11:54,298 --> 00:11:55,889 So I think a couple of things. 122 00:11:55,889 --> 00:12:10,140 One, there are a plethora of paths that are available now, or lawyers and other legal professionals pursue, thanks to technology and also thanks to differentiated client 123 00:12:10,140 --> 00:12:10,940 demands. 124 00:12:10,940 --> 00:12:12,662 So I think that is one thing. 125 00:12:12,662 --> 00:12:21,748 Two, I think that certainly the rise of genera of AI has opened the door to 126 00:12:22,212 --> 00:12:29,315 the need for people with different skill sets, but who want to help and or work in the legal space. 127 00:12:29,315 --> 00:12:39,319 You know, we need people who can help with developing products, with implementing those products, with connecting those products with other ones that law firms or legal partners 128 00:12:39,319 --> 00:12:40,659 already use. 129 00:12:40,800 --> 00:12:50,233 And then perhaps most importantly, there's a growing need for people who can help connect legal departments and law firms with the right technology as well, because we're all busy 130 00:12:50,233 --> 00:12:52,304 and we need experts who can help us. 131 00:12:52,304 --> 00:13:01,832 sort of connect the dots and figure out A, what our pain points and problems are, and then B, using that information, evaluate potential solutions which may or may not be 132 00:13:01,832 --> 00:13:02,913 tech-based. 133 00:13:02,913 --> 00:13:14,783 So that has certainly given rise to, I think, a number of different types of roles and jobs and industries that now exist all around the larger legal ecosystem. 134 00:13:14,923 --> 00:13:21,006 And I think we'll continue to see that sort of sector of the market grow. 135 00:13:21,006 --> 00:13:28,770 because of generative AI growing more powerful, but also because of technology itself evolving and being able to do more. 136 00:13:29,314 --> 00:13:29,974 Yeah. 137 00:13:29,974 --> 00:13:35,107 So we are, uh, you know, we currently have an intranet offering that's very well established. 138 00:13:35,107 --> 00:13:41,551 We're launching an extranet product in Q1 that's going to help bridge that gap. 139 00:13:41,551 --> 00:13:51,386 You know, the predominant player in that space is HighQ They're fairly well established, but there hasn't been a ton of innovation either on the intranet or extranet side in many 140 00:13:51,386 --> 00:13:52,187 years. 141 00:13:52,187 --> 00:13:53,878 I think there's a lot of opportunity. 142 00:13:53,878 --> 00:13:57,932 You know, when I look at how firms deploy HighQ in 143 00:13:57,932 --> 00:14:01,803 many cases it's as a glorified file share. 144 00:14:02,284 --> 00:14:15,069 There seems to be a reluctance on the law firm's part to share, or maybe it's, you know, there isn't the appetite on the inside council side to share things like, you know, matter 145 00:14:15,069 --> 00:14:20,741 billing detail, you know, actual to budget information about the legal team. 146 00:14:20,741 --> 00:14:23,173 Usually it's a lot of file sharing. 147 00:14:23,173 --> 00:14:26,914 We're putting our chips on the table and 148 00:14:27,238 --> 00:14:37,350 embedding that law firm clients want more than just work product being shuttled through a portal. 149 00:14:38,071 --> 00:14:40,704 Is that your perspective as well? 150 00:14:41,776 --> 00:14:54,920 So I certainly think that there is a tendency, and this is, I think, reflective of the fact that oftentimes law firms and or legal departments don't put enough thought into 151 00:14:54,920 --> 00:15:06,692 really thoroughly understanding the problem and or sort of getting ready for the use of a new tool where they go after a tool like HighQ or something else. 152 00:15:06,692 --> 00:15:17,277 but then don't fully implement it, don't fully use it to its full capabilities because of the fact that they weren't perhaps ready for it, or perhaps they have a culture that's not 153 00:15:17,277 --> 00:15:26,381 fully supportive and on board with this tool, or they haven't really understood exactly what the problem is and they went after something that solves perhaps the problem in part 154 00:15:26,381 --> 00:15:27,781 but not in whole. 155 00:15:27,822 --> 00:15:33,614 So there are a lot of different factors at play that I think influence how a solution 156 00:15:33,700 --> 00:15:37,902 that is purchased and then put into places actually used or not used. 157 00:15:37,902 --> 00:15:48,628 And that speaks to, think that there is this tendency, ironically actually if you think about it, considering lawyers often are thought of as being so skeptical of shiny kin 158 00:15:48,628 --> 00:15:56,823 syndrome, going after a shiny new piece of tech because it exists and they've heard someone else uses it and they want to use it too, when in fact there may or may not be the 159 00:15:56,823 --> 00:15:58,193 right solution for them. 160 00:15:58,193 --> 00:16:03,516 So certainly just because a tool exists and has existed, 161 00:16:03,568 --> 00:16:14,648 or is being used by someone doesn't necessarily mean at all that it's the right solution for you or even in the ballpark of what you should be using, which ends up leading to you 162 00:16:14,648 --> 00:16:21,648 purchasing a solution that then ends up sitting on shelf somewhere, hypothetically speaking, and not being really used. 163 00:16:21,648 --> 00:16:23,928 And that's just a real shame. 164 00:16:23,928 --> 00:16:32,298 And it's not just a shame because it's not being used, but it's also a shame because then it impedes further efforts to implement future technology because 165 00:16:32,400 --> 00:16:36,473 People think back, well, we bought this tool and now he uses it. 166 00:16:36,473 --> 00:16:41,528 So why should we spend money on another tool that likely is going to end up also not being used? 167 00:16:41,794 --> 00:16:42,194 Yeah. 168 00:16:42,194 --> 00:16:44,575 Or heavily underutilized. 169 00:16:44,915 --> 00:16:49,906 Yeah, that absolutely influences buying patterns and motivation. 170 00:16:49,906 --> 00:16:56,318 We've, we've seen that before where, you know, firms have made a big investment and it not work out. 171 00:16:56,318 --> 00:17:02,100 And then, you know, there's a reluctance to, um, to make further investment. 172 00:17:02,360 --> 00:17:05,621 Well, uh, talk a little bit about, legal ops. 173 00:17:05,621 --> 00:17:08,962 Like how did you become, um, 174 00:17:09,324 --> 00:17:14,811 You know, an advocate I see you post quite a bit about the area. 175 00:17:14,811 --> 00:17:18,696 Like how did you become a legal ops advocate? 176 00:17:19,568 --> 00:17:32,768 So I think it stems from the fact that I have long seen this disconnect between technology and law and legal operations really is that bridge between the two worlds. 177 00:17:32,768 --> 00:17:37,108 And it also bridges the legal world, the tech world, and the business world together. 178 00:17:37,108 --> 00:17:45,656 And so that's why I'm a big advocate because legal operations really brings those worlds together and helps ensure that technology 179 00:17:45,722 --> 00:17:50,434 fits into the right processes which then support and enable the business. 180 00:17:50,615 --> 00:18:00,420 And they look at it and really these people are pretty amazing because it's not just a matter of putting in place and evaluating technology, it's also a matter of ensuring that 181 00:18:00,420 --> 00:18:12,097 the technology works well, ensuring that the processes that exist support technology, ensuring that the business and all its various functions and units understands and plays 182 00:18:12,097 --> 00:18:14,800 well with existing tools and future tools and 183 00:18:14,800 --> 00:18:16,860 sort of maintaining those relationships. 184 00:18:16,860 --> 00:18:28,060 So if you think about it, because of that multifaceted role that legal ops plays, it requires people who have a diverse skill set that is, you know, really kind of crosses 185 00:18:28,060 --> 00:18:31,260 over into a variety of traditional areas. 186 00:18:31,260 --> 00:18:40,680 And that I think is exciting because I've always been someone who's been a big fan of multidisciplinary learning and action and legal ops really epitomizes that. 187 00:18:40,940 --> 00:18:48,659 Yeah, you know, I've seen you write about the misconceptions around required qualifications. 188 00:18:48,659 --> 00:18:54,405 And I think you had a post a while back about some of these legal ops roles requiring a JD. 189 00:18:54,405 --> 00:19:02,644 Um, you know, what, what, sort of background really do you need to be effective in a legal ops role? 190 00:19:03,898 --> 00:19:13,977 So, you know, I think that having a JD can potentially help you in a legal ops role, but it's not a necessary requirement at all. 191 00:19:13,977 --> 00:19:23,084 It really depends very much on the type of legal ops role that you're looking to fill and the type of environment and culture that you have in place. 192 00:19:23,285 --> 00:19:29,060 I think that legal ops in general, you you need to have a quantitative and a qualitative background. 193 00:19:29,060 --> 00:19:31,696 So you need to be familiar with numbers and metrics. 194 00:19:31,696 --> 00:19:43,136 but you also need to be really good at evaluating general trends and relationships and understand people both from a emotional as well as a business perspective. 195 00:19:43,136 --> 00:19:46,066 And you really need to kind of understand also technology. 196 00:19:46,066 --> 00:20:00,056 So you need to have some degree of technology aptitude and familiarity and be sort of well connected enough to understand different technologies and how they will work with one 197 00:20:00,056 --> 00:20:00,760 another. 198 00:20:00,760 --> 00:20:04,443 in the context of a business that's seeking to grow and evolve. 199 00:20:04,724 --> 00:20:12,270 Which means that you really need to come at it from a pretty diverse background and have exposure to all these areas. 200 00:20:12,270 --> 00:20:22,499 The good news is like with any role you can learn on the job but at the same time you want to come into it understanding the full nature of the role, its demands and its evolving 201 00:20:22,499 --> 00:20:25,151 demands before you jump over. 202 00:20:25,151 --> 00:20:28,336 But that being said, JD is 203 00:20:28,336 --> 00:20:32,255 by no means a guarantee of success in legal ops at all. 204 00:20:32,255 --> 00:20:43,724 It just is sort of a, I'd say, sometimes a helpful background to have, but definitely not at all helpful in all respects or by any means should be a requirement. 205 00:20:44,110 --> 00:20:44,460 Yeah. 206 00:20:44,460 --> 00:20:46,440 And you know, if you look at like Dr. 207 00:20:46,440 --> 00:20:54,710 Larry Richard's research, like a JD can be a contra indicator to some of the qualities that you just described, like empathy. 208 00:20:55,650 --> 00:20:57,820 I'm going to have Dr. 209 00:20:57,820 --> 00:21:00,730 Richard on the podcast here soon. 210 00:21:00,810 --> 00:21:11,430 And you know, he, he has found that the average empathy score for partners hovers around the 41 percentile. 211 00:21:11,430 --> 00:21:12,266 So 212 00:21:12,266 --> 00:21:26,089 well below average and, you know, sticking somebody with low empathy in a role where you need to understand the perspective of people on the other side of the table, that may not 213 00:21:26,089 --> 00:21:27,230 be a good fit. 214 00:21:28,100 --> 00:21:29,801 Yeah, absolutely. 215 00:21:29,801 --> 00:21:43,722 that number doesn't surprise me at all because I think that law school in general tends to dehumanize people and tends to really focus people's attention and skills on kind of 216 00:21:43,722 --> 00:21:51,878 getting emotion out of the equation when in fact, I think that's quite unhelpful because human beings are naturally emotional creatures. 217 00:21:51,878 --> 00:21:54,468 And so the higher your EQ is, 218 00:21:54,468 --> 00:22:03,083 the better off you'll be in terms of managing people and understanding them and being able to get them to listen to you and want to develop a relationship with you. 219 00:22:03,083 --> 00:22:15,020 Because if you come off as cold and unsympathetic and unempathetic, who's really going to want to be around you or listen to you, especially if they're paying you money to help? 220 00:22:15,692 --> 00:22:16,242 Yeah. 221 00:22:16,242 --> 00:22:26,365 You know, we run, I mean, we've been, so we've been doing this a long time and over our history, over these 17 years now, we've done business with 110 AMLaw firms. 222 00:22:26,365 --> 00:22:30,086 So really good cross-sectional view in big law. 223 00:22:30,126 --> 00:22:34,267 And we've had to negotiate contracts with every one of these big law firms. 224 00:22:34,327 --> 00:22:45,196 And, um, we've had very different experiences and, um, some of them not good where, you know, we start out with a very adversarial, like, you know, 225 00:22:45,196 --> 00:22:54,428 because we've had to negotiate our contracts so many times with law firms, we come to the table with a very friendly document, right? 226 00:22:54,428 --> 00:22:56,739 We know what we're going to get pushed back on. 227 00:22:56,739 --> 00:22:59,430 And sometimes they will redline the whole thing. 228 00:22:59,430 --> 00:23:04,091 Sometimes they'll demand that we use the template, which we almost never say yes to. 229 00:23:04,091 --> 00:23:15,354 And we've actually walked away from deals because it happened recently where there was a, like you said, kind of a cold 230 00:23:15,436 --> 00:23:23,307 You know, this is a chess game as opposed to, Hey, this is where I establish a relationship with a partner. 231 00:23:23,307 --> 00:23:29,752 I mean, people who use our solution are going to be customers for seven to 10 years, almost certainly. 232 00:23:29,792 --> 00:23:33,854 And, know, starting off a relationship like that is not a healthy place. 233 00:23:33,854 --> 00:23:44,268 But, you know, again, I think that sometimes that's, that's the model and it doesn't set the stage for a productive ongoing relationships. 234 00:23:45,018 --> 00:23:46,208 Yeah, I agree. 235 00:23:46,208 --> 00:23:59,936 It doesn't surprise me to hear that, but I think it's just a function of just training and a function of this is just how we want to operate and how we want to do business. 236 00:23:59,936 --> 00:24:08,141 And it clearly works for some firms, but as you sort of indicated, it doesn't always work. 237 00:24:08,141 --> 00:24:14,344 And oftentimes that leads to unproductive attempts at building a relationship and 238 00:24:15,012 --> 00:24:22,294 that is just an unfortunate but not surprising side effect of that training I've spoken of. 239 00:24:22,424 --> 00:24:24,255 Yeah, agreed. 240 00:24:24,255 --> 00:24:31,940 So what do you see as the future of legal ops as a key function in law firms and legal departments? 241 00:24:31,940 --> 00:24:36,162 What do you see in looking through the looking glass? 242 00:24:37,540 --> 00:24:50,175 Yeah, I think that legal ops continues to play not just the role of the bridge, but the role of the educator in terms of helping to educate law firm personnel and legal 243 00:24:50,175 --> 00:25:02,831 department personnel on how to use existing tools better, as well as how to make better use of future tools that come down the pike, including generative AI. 244 00:25:02,831 --> 00:25:06,222 And I think that education, you know, 245 00:25:06,320 --> 00:25:11,620 sort of skill set really is going to be increasingly important as technology evolves ever faster. 246 00:25:11,620 --> 00:25:18,070 And as we've seen, generative AI, you know, just kind of came on the scene, is now taken off. 247 00:25:18,070 --> 00:25:29,900 And that just points to, how fast technology changes, but also how fast things can suddenly appear, which points to the need to adapt and the need to educate. 248 00:25:30,552 --> 00:25:39,048 You know, that's a great segue because we were going to talk a little bit about AI and legal practice and some of its potential and some of its limitations. 249 00:25:39,048 --> 00:25:52,277 And I think that you have probably done as good a job as anyone documenting the use cases that are compelling today. 250 00:25:52,857 --> 00:26:00,082 Just kind of at a high level, like how do you view the current capabilities of AI and legal work? 251 00:26:01,072 --> 00:26:07,262 So I think, I've talked about this a fair amount in the past and recently as well. 252 00:26:07,262 --> 00:26:19,912 And I think it starts with understanding that generative AI is here to augment and supplement, meaning that it is here to kind of make us be better at our jobs and do our 253 00:26:19,912 --> 00:26:26,952 jobs in ways that are more productive, not just for us, but for our clients as well. 254 00:26:26,952 --> 00:26:29,384 And that points to, I think, the 255 00:26:29,444 --> 00:26:36,089 the of both the current strengths as well as current limitations of generative solutions as exist currently. 256 00:26:36,350 --> 00:26:43,396 Because if you think about it, these solutions are by and large data driven. 257 00:26:43,396 --> 00:26:48,299 So you give it data, it provides you data, it creates data. 258 00:26:48,640 --> 00:26:58,778 So those types of tasks that are particularly data heavy and data dependent are going to be tasks that are best suited for these tools, as well as ones that are 259 00:26:58,778 --> 00:27:04,792 sort of standardizable routine and sort of ripe for automation. 260 00:27:04,792 --> 00:27:12,306 But as we've seen, these growing capabilities are allowing for the creation of new forms of knowledge and new ways to organize knowledge. 261 00:27:12,306 --> 00:27:19,090 So I think knowledge management as well becomes an area that I think General AI is going to help a lot with. 262 00:27:19,090 --> 00:27:26,448 And lawyers and legal professionals in general are not always the best at managing their vast array of knowledge. 263 00:27:26,448 --> 00:27:34,768 And so generative AI tools can really help with that, think, as well, which is something I pointed to in terms of some of the use cases that I've described in the past. 264 00:27:34,768 --> 00:27:39,198 But again, we need to realize that it's still early days for generative AI. 265 00:27:39,198 --> 00:27:43,078 It may seem like it's been here for a while at this point, but it hasn't. 266 00:27:43,078 --> 00:27:51,272 And we're really only still scratching the surface of what these tools will be capable of going forward. 267 00:27:51,714 --> 00:27:51,954 Yeah. 268 00:27:51,954 --> 00:27:55,937 So what do you see as like top use cases today? 269 00:27:55,937 --> 00:28:07,566 I mean, I've seen you list out many, but like for law firms that are really just getting started mapping out their AI strategy, which honestly, that's where most firms are. 270 00:28:07,566 --> 00:28:17,653 If you look at some of the surveys out there, it says otherwise, but based on my observations, those survey results are very aspirational. 271 00:28:18,434 --> 00:28:27,999 The Iltatech survey that just came out said that 74 % of law firms with 700 or more attorneys are using AI and business workflows. 272 00:28:28,179 --> 00:28:30,361 That seems totally aspirational to me. 273 00:28:30,361 --> 00:28:40,166 I think they're evaluating tools and maybe at that level, but I don't see a lot of practice of law use cases being implemented. 274 00:28:40,166 --> 00:28:48,010 So for a firm that's really starting to map out their journey, what do you think are the most compelling areas they should look at first? 275 00:28:48,548 --> 00:28:52,731 Well, my first instinct is to give a very lawyerly answer and say it depends. 276 00:28:52,731 --> 00:29:05,642 getting beyond that, think that, you know, generally I can be very helpful with respect to review documents and drawing up trends, whether it's briefs, whether it's case law 277 00:29:05,642 --> 00:29:16,400 research, draw out analytics to figure out the best lines of argument, the most applicable cases, the best way to structure arguments on the litigation side, on the transactional 278 00:29:16,400 --> 00:29:18,608 side, review of contracts. 279 00:29:18,608 --> 00:29:31,308 review of other documents to find sort of trends or clauses that seem to be the most effective for whatever purpose. 280 00:29:31,408 --> 00:29:34,828 Those types of tasks tend to be very effective for Gen.ai. 281 00:29:34,908 --> 00:29:44,868 I also think that they can help with on the IP side, patent drafting, patent review, patent design. 282 00:29:46,766 --> 00:29:56,369 Lastly, would say that generative value is very helpful with respect to intake of clients and kind of taking in that information and then directing that information to whomever 283 00:29:56,369 --> 00:30:03,971 needs to see it to open up a case file or review a case file or what have you. 284 00:30:03,971 --> 00:30:10,043 So those are types of the use cases that I think are right now really particularly useful. 285 00:30:10,323 --> 00:30:14,614 But as you mentioned yourself, anecdotally in my experience as well, I've 286 00:30:14,628 --> 00:30:20,382 you know, seeing that firms right now are kind of still in their exploratory phase where they're sort of exploring gen. 287 00:30:20,382 --> 00:30:30,118 AI, but they haven't fully integrated into their practice per se, unless we're one of these huge firms where they have developed their own in-house model and are all in on it. 288 00:30:30,118 --> 00:30:34,400 But that's because they have the time, the money and the personnel to be able to do it. 289 00:30:34,744 --> 00:30:35,415 Yeah. 290 00:30:35,415 --> 00:30:47,883 You know, I think that, as is typical with many new tech trends, novel tech trends is there's a, the Gartner hype curve man plays out almost every time perfectly. 291 00:30:47,883 --> 00:31:00,111 And you know, you've got the peak of inflated expectations and I feel like we've kind of crossed over that peak and we're now heading towards the trough of disillusionment because 292 00:31:00,111 --> 00:31:02,652 I think we came out way too optimistic. 293 00:31:02,652 --> 00:31:04,014 You know, the, 294 00:31:04,014 --> 00:31:09,434 the Goldman report that 44 % of legal tasks could be automated by generative AI. 295 00:31:09,434 --> 00:31:14,294 think that was ambitious and certainly based on where the technology is today. 296 00:31:14,294 --> 00:31:30,974 I think the Stanford study did a really good job highlighting a lot of the shortcomings of current state technology, its inability to distinguish between legal actors and its 297 00:31:30,974 --> 00:31:33,606 inability to identify holdings and 298 00:31:33,787 --> 00:31:39,508 Um, you know, I, did you have a chance to look at that Stanford study? 299 00:31:40,080 --> 00:31:42,120 Yeah, I looked at that study. 300 00:31:42,300 --> 00:31:46,320 you know, I've looked at all sorts of surveys and reports on, on Gen. 301 00:31:46,320 --> 00:31:56,200 think the bottom line is, you know, with respect to the hype curve and the study, is it just points to something I said earlier, which is that we're in the early days of using 302 00:31:56,200 --> 00:31:56,570 Gen. 303 00:31:56,570 --> 00:31:59,980 AI, it's both powerful and limited. 304 00:31:59,980 --> 00:32:03,720 And we just need to be realistic about its potential. 305 00:32:03,720 --> 00:32:09,264 And I think that one of the issues I think needs to be kind of dealt with. 306 00:32:09,264 --> 00:32:18,504 and addressed is the fact that artificial intelligence, it's a phrase that carries a lot of weight, carries a lot of sort of built-in assumptions. 307 00:32:18,504 --> 00:32:25,514 And at the end of the day, we're not really talking about intelligence in the way that you and I and most humans think about intelligence. 308 00:32:25,514 --> 00:32:35,964 We're thinking about it when it comes to JNI, we're considering, you know, it's really in terms of just coding and its ability to analyze data faster than we can. 309 00:32:35,964 --> 00:32:38,118 So in that sense, it's intelligent. 310 00:32:38,202 --> 00:32:43,184 but it's not intelligent in the way that you and I think or operate or are aware of ourselves. 311 00:32:43,184 --> 00:32:56,376 So really, I think we have to kind of take that in mind when we consider artificial intelligence as a concept, particularly given that itself is not a new technology. 312 00:32:56,376 --> 00:32:58,320 It's been around for a long time. 313 00:32:58,320 --> 00:32:59,941 Generative AI is new. 314 00:32:59,941 --> 00:33:07,394 Its ability to create things is new, but its ability to analyze boatloads of data and provide analytics is not a new thing. 315 00:33:07,408 --> 00:33:16,108 Um, I often use this analogy where, know, you can think about it when we were sending people to the moon, when we did that sort of thing, that would not have been possible 316 00:33:16,108 --> 00:33:19,968 without rudimentary AI on huge computers. 317 00:33:19,968 --> 00:33:31,088 And we've come a long way from there, but at the same time, you know, we're, we're definitely now again, harking back to those days in terms of use of data and people need 318 00:33:31,088 --> 00:33:36,878 to just, I think, and go into sort of learning about gene AI with eyes wide open and understand that. 319 00:33:36,878 --> 00:33:40,917 Like any technology, it's powerful and limited. 320 00:33:41,890 --> 00:33:48,154 Yeah, you know, there's been a lot of debate over whether generative AI can reason. 321 00:33:48,495 --> 00:33:53,499 And I am on in the camp of that it cannot. 322 00:33:53,499 --> 00:34:00,104 And I think it's it can create the illusion of, of human reasoning. 323 00:34:00,104 --> 00:34:04,627 But there was a, I don't know if you saw it, it literally just came out maybe two weeks, maybe three weeks ago. 324 00:34:04,627 --> 00:34:08,770 Now it was the end of October from, um, the Apple AI team. 325 00:34:09,154 --> 00:34:23,720 where they took a test, the GSM 8K, it's the grade school math test, and they changed some very, they changed the problems, their word problems, and they changed them in very 326 00:34:23,720 --> 00:34:25,061 trivial ways. 327 00:34:25,061 --> 00:34:33,505 One way that they changed it was they would put a sentence into the word problem that had nothing to do with calculating the answer. 328 00:34:33,505 --> 00:34:35,625 You one example was, 329 00:34:37,122 --> 00:34:48,696 where they had a list of prices today and they said inflation has increased by 10 % each year over the last three years, completely through all the models off. 330 00:34:48,696 --> 00:34:55,428 I think it was like a 65 % drop in performance just by throwing an irrelevant detail in there. 331 00:34:55,428 --> 00:35:00,109 Another way that they changed the problems, they changed the names, right? 332 00:35:00,109 --> 00:35:02,730 So instead of Sonya, it would be Colin. 333 00:35:03,768 --> 00:35:10,621 but they did so consistently so that a person looking at that would see that, there's an irrelevant sentence in there or the, the name changed. 334 00:35:10,621 --> 00:35:16,344 But really what it demonstrated is that AI does not understand the problems that it's solving. 335 00:35:16,344 --> 00:35:18,465 It's predicting the next token. 336 00:35:18,465 --> 00:35:22,167 So with that limitation, we have to keep that in mind. 337 00:35:22,167 --> 00:35:26,583 There's still a lot of debate about whether or not they can AI can reason. 338 00:35:26,583 --> 00:35:26,849 don't know. 339 00:35:26,849 --> 00:35:28,660 Do you have any perspective on that? 340 00:35:29,264 --> 00:35:32,804 So I have a couple, I think, thoughts on that. 341 00:35:32,804 --> 00:35:34,728 One is that... 342 00:35:36,558 --> 00:35:41,091 GNI is as good as the data it's been provided with and been trained on. 343 00:35:41,091 --> 00:35:43,382 So there's that, I think, first and foremost. 344 00:35:43,382 --> 00:35:54,960 Secondly, think that it can learn, but only based off of data you give it. 345 00:35:55,280 --> 00:36:01,464 And lastly, it's basically an advanced pattern recognition device. 346 00:36:01,518 --> 00:36:04,209 So it recognizes patterns in data. 347 00:36:04,209 --> 00:36:15,594 And if you change something about a pattern that you give it, that can sometimes throw it completely off because it just completely doesn't match up with the pattern that it had 348 00:36:15,594 --> 00:36:20,816 been using before, which goes to the word problem that you were just describing. 349 00:36:21,336 --> 00:36:24,838 So I think that's important to keep in mind with these tools. 350 00:36:25,118 --> 00:36:30,390 And their ability to reason is less a function of sort 351 00:36:30,702 --> 00:36:40,655 reasoning the way you and I think about reasoning and more a function of just the data it has, the data you've given it, and making those two match up in some way. 352 00:36:40,655 --> 00:36:42,936 And so it will get better for sure. 353 00:36:42,936 --> 00:36:49,058 And it will have the ability to reason a little more on its own. 354 00:36:49,058 --> 00:36:53,539 But data is the big impediment right now. 355 00:36:53,780 --> 00:36:55,340 It needs more data. 356 00:36:55,755 --> 00:36:56,055 Yeah. 357 00:36:56,055 --> 00:37:07,931 There's some, know, like the O one model with the chain of thought and there, there are some mechanisms they're leveraging to improve the reasoning, but it's still in my opinion, 358 00:37:07,931 --> 00:37:17,025 creating the illusion of reasoning as opposed to what us humans think is like reasoning their way to a novel approach to a mathematical proof. 359 00:37:17,025 --> 00:37:19,966 For example, like AI can't do that. 360 00:37:20,012 --> 00:37:20,523 Right. 361 00:37:20,523 --> 00:37:29,069 Um, if it's not in the training set, it's not going to be able to reason its way to a, to a new approach to solving a mathematical proof. 362 00:37:29,110 --> 00:37:35,465 But what are your thoughts about like, um, general versus legal specific AI models? 363 00:37:35,465 --> 00:37:38,788 You know, you've got the Harveys and the Paxton's of the world. 364 00:37:38,788 --> 00:37:45,104 There's lots of players out there that are building, uh, legal specific solutions. 365 00:37:45,104 --> 00:37:47,904 How, how important are 366 00:37:47,904 --> 00:37:55,766 Is it to have a especially trained model versus kind of the general foundational models that are out there today? 367 00:37:56,848 --> 00:37:59,768 I think it's a context driven decision. 368 00:37:59,768 --> 00:38:13,168 If you are operating a law firm or legal department and you have very specific needs and concerns around security, then it makes more sense to try to build a legal specific model 369 00:38:13,168 --> 00:38:16,188 or use one that's specifically for legal. 370 00:38:16,208 --> 00:38:25,796 If you're a legal tech company or a larger company or just company that's not legal specific but supports in some ways or interacts with the legal industry, 371 00:38:25,796 --> 00:38:28,967 then I think you can use some of these other models or partner with them as well. 372 00:38:28,967 --> 00:38:40,262 So I don't think really it's so much a debate as it is really just a matter of what your needs are, what your problems are, and letting those define kind of the type of solution 373 00:38:40,262 --> 00:38:41,623 you want to have. 374 00:38:42,043 --> 00:38:52,658 That being said, a lot of law firms I've talked to have certainly been very eager to have models that are very legal specific because of their concerns around accuracy and 375 00:38:52,658 --> 00:38:53,738 security. 376 00:38:54,274 --> 00:38:54,894 Yeah. 377 00:38:54,894 --> 00:38:57,575 I mean, there's people placing really big bets. 378 00:38:57,575 --> 00:39:08,458 know, Harvey's latest, uh, series C put their valuation at $1.5 billion with approximately 30 million in revenue. 379 00:39:08,458 --> 00:39:19,581 So, you know, the, the, the things that have to happen in order for those bets to pay off the way a venture fund needs them to are quite extraordinary. 380 00:39:19,581 --> 00:39:23,292 Um, you know, the law firm market itself is relatively small. 381 00:39:23,292 --> 00:39:24,332 There's only, 382 00:39:24,650 --> 00:39:35,139 there's no official numbers on this, I, by my calculations, there's about 500 law firms in the world that are over a hundred attorneys, maybe 600, but certainly not more than that. 383 00:39:35,139 --> 00:39:38,942 Um, but I know that they're going to move into, into other areas. 384 00:39:38,942 --> 00:39:50,012 So, you know, it feels like, I don't know if this is your perspective as well, that there is a, there's a lot of money chasing these opportunities in the marketplace. 385 00:39:50,012 --> 00:39:51,993 That's really driving up valuations. 386 00:39:51,993 --> 00:39:53,094 Like that's a, 387 00:39:53,102 --> 00:40:02,745 30 million to 1.5, but that's a 50 X multiple for a company that has really not had a clear strategy. 388 00:40:02,745 --> 00:40:16,279 You know, they tried a raise to acquire VLex and you know, they've been kind of operating in stealth mode and you know, so to put it in their series B was 715 million seven months 389 00:40:16,279 --> 00:40:16,659 earlier. 390 00:40:16,659 --> 00:40:18,810 So they doubled in value in seven months. 391 00:40:18,810 --> 00:40:19,832 Like what 392 00:40:19,832 --> 00:40:24,120 The things that have to happen for a company to double its valuation are quite extraordinary. 393 00:40:24,120 --> 00:40:24,661 So I don't know. 394 00:40:24,661 --> 00:40:26,944 Do you, do feel like we're in a bubble right now? 395 00:40:28,144 --> 00:40:31,024 I think there definitely are signs that a bubble exists. 396 00:40:31,024 --> 00:40:40,524 think there's a lot of just optimism and lot of hype around AI as has always existed with respect to other types of technology. 397 00:40:40,524 --> 00:40:53,864 I think that, you know, where reality will set in over, you know, like six months to a year and perhaps even shorter than that as technology evolves and gets in at the same 398 00:40:53,864 --> 00:40:57,184 time, it gets better, also continues to show its limitations. 399 00:40:57,264 --> 00:41:07,364 But I do think that, you know, there's been a lot of money throwing at AI, I think, because, again, people were very excited and thought there was all this potential and that 400 00:41:07,364 --> 00:41:09,624 potential was going to be realized right off the bat. 401 00:41:09,624 --> 00:41:16,684 When in fact, as has been the case with all sorts of other technologies, is the potential is realized over time. 402 00:41:17,144 --> 00:41:22,084 Sometimes a long period of time, sometimes a shorter period of time, but over time, nevertheless. 403 00:41:22,424 --> 00:41:25,942 And I think that's going to continue to be a theme going forward. 404 00:41:26,060 --> 00:41:34,081 So I do think that these large investments sometimes distorts the perception and the reality of generative AI. 405 00:41:34,520 --> 00:41:35,071 Yeah. 406 00:41:35,071 --> 00:41:48,943 You know, and another thing that I would be considering if I were an investor in that space is, you know, the first mover, the first successful company is rarely the long-term 407 00:41:48,943 --> 00:41:50,504 winner in the marketplace. 408 00:41:50,504 --> 00:41:56,870 mean, ask Netscape, you know, ask Lotus one, two, three, ask WordPerfect, ask BlackBerry. 409 00:41:56,870 --> 00:42:02,474 There's countless examples where, you know, these companies paved the way for the real winner. 410 00:42:02,582 --> 00:42:07,364 in the space who came later or all the search engines relative to Google, right? 411 00:42:07,364 --> 00:42:12,525 There was 50 of them out there, Alta Vista and Yahoo and Excite. 412 00:42:12,665 --> 00:42:14,686 So yeah, I don't know. 413 00:42:14,906 --> 00:42:22,748 It seems like to really throw that much investment this early in the game. 414 00:42:22,748 --> 00:42:23,479 Cause I agree with you. 415 00:42:23,479 --> 00:42:27,070 I think we're in the top of the first inning in the AI baseball game. 416 00:42:27,070 --> 00:42:28,160 I really do. 417 00:42:28,484 --> 00:42:30,185 Yeah, I think that's true. 418 00:42:30,185 --> 00:42:45,195 And I remember, you know, this dates me a little bit, you know, Netscape Navigator was a huge browser back in the day and was very popular and was kind of a legal leader alongside 419 00:42:45,195 --> 00:42:47,637 Yahoo and the search engine space. 420 00:42:47,637 --> 00:42:57,904 But both, I think made a number of decisions that led to them, you know, falling by the wayside in some ways with respect to their respective segments. 421 00:42:57,904 --> 00:43:03,744 Um, and so it'll be interesting to see if that repeats again in this case. 422 00:43:03,744 --> 00:43:09,824 I'm not, you know, I think the jury is still out a little bit, but that definitely remains big danger for sure. 423 00:43:09,824 --> 00:43:18,814 Um, but it's been interesting just to see Google and Apple take a far slower approach to incorporation use of AI. 424 00:43:18,814 --> 00:43:26,320 And I think that's a reflection of not just them being behind the eight ball a little bit, but also a matter of them. 425 00:43:26,320 --> 00:43:36,920 I think perhaps having a better understanding of the limitation of AI and therefore taking a more pragmatic, practical approach where they can roll it out, but in piecemeal, as 426 00:43:36,920 --> 00:43:39,340 opposed to rolling it all out all at once. 427 00:43:39,682 --> 00:43:48,967 Yeah, I mean, you know, with search GPT like Google and perplexity, you know, I use Google less and less these days. 428 00:43:48,967 --> 00:43:50,698 It's still my default search engine. 429 00:43:50,698 --> 00:44:01,624 actually made perplexity my default search engine for a little while, but I still I still type stuff that I need a Google result for, like the name of a business and I want to get 430 00:44:01,624 --> 00:44:04,556 the phone number or I want to see a map of it. 431 00:44:04,556 --> 00:44:09,056 But it is getting closer and closer to that tipping point for me where 432 00:44:09,056 --> 00:44:12,248 All I need is perplexity or now search GPT. 433 00:44:12,248 --> 00:44:15,180 you know, these, I agree with you actually. 434 00:44:15,180 --> 00:44:22,375 think Google, you know, Google has been investing much more so than Apple. 435 00:44:22,616 --> 00:44:30,960 Google has been investing in the technology, but has been much more measured in its rollout, it seems. 436 00:44:30,960 --> 00:44:32,692 yeah, I think that's accurate. 437 00:44:32,692 --> 00:44:46,343 And Apple, I think, I think Apple has been a little distracted, I think, in part by the role of the virtual reality Apple vision, which didn't do well. 438 00:44:46,343 --> 00:44:48,054 And I was not surprised. 439 00:44:48,074 --> 00:44:50,358 And not just because of its high cost. 440 00:44:50,358 --> 00:45:00,494 I high cost is something that goes hand in hand with Apple, but more just because just don't think that technology is where it needs to be for it to be super usable right now. 441 00:45:01,576 --> 00:45:04,459 So yeah, it'll be interesting to how things play out. 442 00:45:04,680 --> 00:45:12,318 But I agree with you, we're definitely in the first inning and I think that's going to be important to keep in mind as we go forward. 443 00:45:12,450 --> 00:45:14,091 Yeah, absolutely. 444 00:45:14,091 --> 00:45:16,633 Well, this has been a really fun conversation. 445 00:45:16,974 --> 00:45:20,837 I appreciate you spending a little bit of time with us today. 446 00:45:20,837 --> 00:45:25,331 How, before we go, you put out some great content. 447 00:45:25,331 --> 00:45:26,392 I really like your stuff. 448 00:45:26,392 --> 00:45:40,394 I think you do a good job creating a human element to, you know, what sometimes is a non-human platform, which is LinkedIn. 449 00:45:40,394 --> 00:45:41,378 You people don't 450 00:45:41,378 --> 00:45:44,616 typically share their political views or their personal challenges. 451 00:45:44,616 --> 00:45:46,712 And I think you do a good job with that. 452 00:45:46,712 --> 00:45:50,932 How do, how do folks who want to follow your content find you? 453 00:45:51,536 --> 00:45:54,578 So there are two key ways to do that. 454 00:45:54,578 --> 00:45:57,820 One is by following me on LinkedIn under my name. 455 00:45:58,021 --> 00:46:00,363 I feel like it almost goes without saying. 456 00:46:00,363 --> 00:46:04,465 And then secondly, visit my website, colonistlevy.com. 457 00:46:05,286 --> 00:46:13,302 And of course, I'd be remiss if I didn't mention checking out my book, The Legal Tech Ecosystem, available on Amazon worldwide. 458 00:46:13,890 --> 00:46:15,341 Yep, I'm an owner of it. 459 00:46:15,341 --> 00:46:17,393 I've enjoyed, I've enjoyed reading it. 460 00:46:17,393 --> 00:46:18,354 I read it in pieces. 461 00:46:18,354 --> 00:46:22,707 I don't have the attention span to go cover to cover, but I have read it. 462 00:46:22,707 --> 00:46:27,280 And in fact, I read your section on legal ops and I learned quite a bit. 463 00:46:28,101 --> 00:46:28,852 So good stuff. 464 00:46:28,852 --> 00:46:30,553 Well, I appreciate you joining. 465 00:46:30,553 --> 00:46:34,636 Are you, are you going to TLTF in a couple of weeks? 466 00:46:35,170 --> 00:46:37,183 Unfortunately, I will not be there now. 467 00:46:37,292 --> 00:46:40,167 Yeah, but maybe we'll. 468 00:46:40,750 --> 00:46:41,681 Yeah, it is. 469 00:46:41,681 --> 00:46:42,644 It's a nice play. 470 00:46:42,644 --> 00:46:48,886 They're doing it in Key Biscayne this year, so South Florida is not a bad place to be in December. 471 00:46:48,886 --> 00:46:57,908 no, I used to have family and keep a skin so it's a nice area but it is a little late in the year with holidays. 472 00:46:58,380 --> 00:46:59,093 Yeah. 473 00:46:59,093 --> 00:46:59,786 Well, good stuff. 474 00:46:59,786 --> 00:47:03,690 I appreciate you joining and maybe we'll see you at legal week. 475 00:47:03,940 --> 00:47:05,753 Thanks again, thanks so much. 476 00:47:05,826 --> 00:47:07,211 All right, take care. 477 00:47:07,556 --> 00:47:08,220 Bye. -->