1 00:00:02,816 --> 00:00:05,163 Dan Szabo, how are you this afternoon? 2 00:00:05,166 --> 00:00:05,976 I'm doing great. 3 00:00:05,976 --> 00:00:06,623 Glad to be here. 4 00:00:06,623 --> 00:00:07,436 Thanks for having me. 5 00:00:07,436 --> 00:00:08,076 Awesome, man. 6 00:00:08,076 --> 00:00:10,696 I appreciate you taking a little bit of time. 7 00:00:11,596 --> 00:00:11,696 Yeah. 8 00:00:11,696 --> 00:00:19,376 When I saw the, your post about winning the transformative project of the year from Ilta, I knew I had to reach out. 9 00:00:19,376 --> 00:00:27,776 I'd saw you speak at the inside practice event last spring, spring of 23 and or I get no 24. 10 00:00:27,776 --> 00:00:29,136 Thought you did a great job. 11 00:00:29,136 --> 00:00:31,816 So yeah, man, I'm excited to have you on the podcast. 12 00:00:32,200 --> 00:00:32,611 me too. 13 00:00:32,611 --> 00:00:34,553 I'm actually a long time listener and reader. 14 00:00:34,553 --> 00:00:41,049 uh Yeah, thanks for everything you do to keep minds operating at the cutting edge of the industry. 15 00:00:41,049 --> 00:00:43,462 Really excited to be here and appreciate the invite. 16 00:00:43,462 --> 00:00:44,396 Thanks for having 17 00:00:44,396 --> 00:00:45,056 Awesome, man. 18 00:00:45,056 --> 00:00:46,416 I'm glad to hear that. 19 00:00:46,416 --> 00:00:46,596 Yeah. 20 00:00:46,596 --> 00:00:49,636 I started the podcast, like was never on a bucket list. 21 00:00:49,636 --> 00:00:53,896 I started having conversations like the one you and I had the last time we spoke. 22 00:00:53,896 --> 00:00:55,596 And I was like, man, you know what? 23 00:00:55,596 --> 00:00:59,796 People would, people would listen to this and it just kind of happened. 24 00:00:59,796 --> 00:01:04,516 I did three episodes before Ilta two years ago and released them. 25 00:01:04,516 --> 00:01:06,096 And I was like, man, nobody's going to see this. 26 00:01:06,096 --> 00:01:10,516 And like five, seven people came by the booth and goes, Hey, podcast is awesome. 27 00:01:10,516 --> 00:01:11,096 I was like, wow. 28 00:01:11,096 --> 00:01:13,056 Like people, people will listen. 29 00:01:13,056 --> 00:01:13,572 So 30 00:01:14,306 --> 00:01:14,566 Yeah. 31 00:01:14,566 --> 00:01:16,287 Well, but, on that note, they do. 32 00:01:16,287 --> 00:01:20,002 And congratulations on your award as well, uh from Alta. 33 00:01:20,002 --> 00:01:20,833 That was great news. 34 00:01:20,833 --> 00:01:22,455 was very excited to see it. 35 00:01:22,455 --> 00:01:25,458 They know quality when they see it, right? 36 00:01:25,458 --> 00:01:25,787 Yeah. 37 00:01:25,787 --> 00:01:26,137 man. 38 00:01:26,137 --> 00:01:32,960 I, was shortlisted for that award 10 years ago, 10 years prior and didn't win it and then reapplied. 39 00:01:32,960 --> 00:01:39,603 And, um, I think they would have felt bad if they made me get all dressed up in a suit and go to an awards dinner twice. 40 00:01:41,544 --> 00:01:42,364 But I'll take it. 41 00:01:42,364 --> 00:01:43,564 I'll take it. 42 00:01:43,845 --> 00:01:45,145 well let's get you introduced, man. 43 00:01:45,145 --> 00:01:46,706 So I was looking at your background. 44 00:01:46,706 --> 00:01:51,978 It looks like you studied computer science in, uh, in college and 45 00:01:52,000 --> 00:01:55,343 You had some app dev gigs prior to stepping into legal. 46 00:01:55,343 --> 00:02:03,070 Um, you worked with littler, for a little while and now you're a senior director of innovation at DWT. 47 00:02:03,070 --> 00:02:04,421 Um, fill in the gaps, man. 48 00:02:04,421 --> 00:02:10,638 Like what, tell us a little bit about kind of your role and your day to day and what, know, all that sort of stuff. 49 00:02:10,638 --> 00:02:10,898 Sure. 50 00:02:10,898 --> 00:02:16,903 Well, I actually got into software development when I was in the army across multiple deployments to Iraq. 51 00:02:16,984 --> 00:02:22,749 I was really interested in coding and figuring out how apps were being made. 52 00:02:22,749 --> 00:02:28,003 Smartphones were starting to show up and um I've always been interested in technology. 53 00:02:28,003 --> 00:02:33,750 And so at night between guard duty shifts, I would be studying with a Sam's teacher self book and a flashlight. 54 00:02:33,750 --> 00:02:41,837 And I'm like the tiniest laptop I could find because it needed to fit in my cargo pocket so I could take it with me on guard duty and tours and stuff. 55 00:02:41,837 --> 00:02:44,499 And so, yeah, that's kind of how I cut my teeth on it. 56 00:02:44,499 --> 00:02:53,787 um And then when I got out, I got picked up at Hewlett Packard as a tools developer for consultants and contractors on the ground. 57 00:02:53,787 --> 00:03:00,713 So just like rapid development, um fixing stuff that's broken and building apps for new use cases on the fly. 58 00:03:00,713 --> 00:03:02,094 ah But yeah, then... 59 00:03:02,094 --> 00:03:02,854 um 60 00:03:03,130 --> 00:03:08,384 A friend of a friend told me this law firm in San Francisco was looking at doing something on this platform called KSmart. 61 00:03:08,384 --> 00:03:12,018 They really wanted to go next level with it and they were hiring for it. 62 00:03:12,018 --> 00:03:15,641 And that is how I got into the industry. 63 00:03:15,641 --> 00:03:21,245 was a high volume platform, kind of a first of its kind. 64 00:03:21,245 --> 00:03:25,859 And so they were really navigating like this new cutting edge ground as a law firm. 65 00:03:25,859 --> 00:03:32,206 And what I didn't know at the time is that it was very unusual for law firms to be developing software themselves. 66 00:03:32,206 --> 00:03:33,186 Cause I was an outsider. 67 00:03:33,186 --> 00:03:33,786 I didn't know. 68 00:03:33,786 --> 00:03:36,886 And so it was just always normal to me to be doing that. 69 00:03:36,886 --> 00:03:40,346 And only after being in the industry for a few years that I realized how unique it was. 70 00:03:40,346 --> 00:03:44,486 Well, fast forward to today, uh, DWT wanted to do the same thing. 71 00:03:44,486 --> 00:03:48,246 And, and, um, I was trying to get to the Northwest and so it was a great match. 72 00:03:48,246 --> 00:03:51,746 And here we are, um, senior director of innovation. 73 00:03:52,086 --> 00:03:56,946 We're, uh, cranking out apps that are, you know, frankly, really, really good. 74 00:03:57,666 --> 00:04:01,100 Um, uh, our latest hit, dbt.ai is a, 75 00:04:01,100 --> 00:04:03,361 large language model that's running inside of the platform. 76 00:04:03,361 --> 00:04:12,413 And we're using that as a floor to scaffold new productivity apps on top of, uh like Crescendo that you mentioned earlier. 77 00:04:12,413 --> 00:04:14,228 And so yeah, that's how we got here. 78 00:04:14,629 --> 00:04:16,284 What is that based on? 79 00:04:16,284 --> 00:04:19,944 Is that a llama-based implementation? 80 00:04:20,236 --> 00:04:20,556 Sure. 81 00:04:20,556 --> 00:04:27,793 So dwt.ai is actually a collection of different technologies working to deliver a chat GPT like experience. 82 00:04:27,793 --> 00:04:37,421 So it is based on open AI, but we do pull in other language models just depending on like the kind of like prompts that's being asked or the kind of solution that we're trying to 83 00:04:37,421 --> 00:04:40,202 deliver based on the use case. 84 00:04:40,543 --> 00:04:48,980 so, yeah, it's an amalgam of different specialties that work in concert to deliver a good experience for our attorneys. 85 00:04:49,332 --> 00:04:49,872 Interesting. 86 00:04:49,872 --> 00:04:57,258 So one of the things that struck me about Crescendo, and we're going to talk about that in just a minute, is you guys kind of flip the script. 87 00:04:57,319 --> 00:05:03,984 And before we dive down that rabbit hole, let's talk for a minute about just the limitations. 88 00:05:03,984 --> 00:05:18,455 The current paradigm is you've got a text box and you type in a prompt and it gives you a response and you refine, maybe include some documents. 89 00:05:19,670 --> 00:05:23,346 for rag purposes and you eventually work your way to an answer. 90 00:05:23,346 --> 00:05:31,250 um What are some of the limitations that spurred you to look in other directions with that model? 91 00:05:31,566 --> 00:05:32,426 Sure. 92 00:05:32,526 --> 00:05:35,406 So we've been at this about 18 months now. 93 00:05:35,406 --> 00:05:47,406 It's been in production for about 18 months and we've had a lot of opportunity to watch attorneys in the wild using AI and not just attorneys, but professional staff as well. 94 00:05:47,406 --> 00:05:57,326 the technology is great, but the experience has some subtle limitations that I think we were uniquely keen to because we sort of rushed to the table to figure this out. 95 00:05:57,326 --> 00:05:59,566 The first is that 96 00:05:59,990 --> 00:06:01,552 Uh, it's reactive. 97 00:06:01,552 --> 00:06:10,178 You actually, when you're working on a document or you're doing something, you have to stop what you're doing, go to a browser tab, paste in your prompt or type it in whatever 98 00:06:10,479 --> 00:06:12,241 and, hit go. 99 00:06:12,241 --> 00:06:15,384 And so that's subtly disruptive. 100 00:06:15,384 --> 00:06:19,137 But the, but the real insight is that this is with a large language model. 101 00:06:19,137 --> 00:06:21,959 This is actually, it's not a technical exercise. 102 00:06:21,959 --> 00:06:27,662 It's a trust exercise because you're pasting something into a box with an undetermined response. 103 00:06:27,662 --> 00:06:28,922 anything could come back. 104 00:06:28,922 --> 00:06:32,322 And so you're just kind of hoping that like a good answer comes back. 105 00:06:32,322 --> 00:06:38,322 And there's a trust breach there that creates friction for user adoption, for efficacy of the results. 106 00:06:38,322 --> 00:06:40,082 It invites additional scrutiny. 107 00:06:40,082 --> 00:06:49,142 And so in some situations when you use AI, it actually slows the process down because of the additional layers of review it takes when people know AI was used, right? 108 00:06:49,182 --> 00:06:51,622 And so that's not something anybody has solved. 109 00:06:51,622 --> 00:06:54,162 And the technology will never fully solve it. 110 00:06:54,162 --> 00:06:56,678 We'll never get a 100 % accurate LLM. 111 00:06:57,250 --> 00:07:10,429 So, but one thing that we realized with the tech is that it's actually, it's good at generating answers, but what it's really good at is answering questions or generating 112 00:07:10,429 --> 00:07:12,831 questions for you to answer. 113 00:07:12,831 --> 00:07:16,463 What we realized is in this trust exercise, there's two parties. 114 00:07:16,543 --> 00:07:19,185 One can hallucinate, the other usually doesn't. 115 00:07:19,185 --> 00:07:21,667 One has known good information and the other one doesn't. 116 00:07:21,667 --> 00:07:26,680 So we thought, well, you know, this whole reactive experience is actually sort of working against us on. 117 00:07:26,680 --> 00:07:27,931 tougher use cases. 118 00:07:27,931 --> 00:07:29,692 So what if we create a proactive AI? 119 00:07:29,692 --> 00:07:35,476 What if the AI prompts you and gets the good information from you and then does something useful with that instead? 120 00:07:35,476 --> 00:07:46,143 And that was what unlocked the next level of AI interaction uh and is the premise for the crescendo engine, is the proof in the pudding. 121 00:07:46,143 --> 00:07:48,164 Once we figured that out, it just took off. 122 00:07:48,164 --> 00:07:51,666 um And so that was the unique insight that set it free. 123 00:07:51,980 --> 00:07:52,360 Interesting. 124 00:07:52,360 --> 00:07:55,101 And you see that with some custom GPTs. 125 00:07:55,101 --> 00:07:57,841 um I think they call them actions. 126 00:07:58,222 --> 00:08:02,023 You specify actions and they're essentially questions. 127 00:08:02,023 --> 00:08:15,746 I have one that I use called um CoCEO and I basically put in all of our um core values. 128 00:08:15,746 --> 00:08:18,683 I put in our ideal customer profile information. 129 00:08:18,683 --> 00:08:21,866 I put in the pitch deck that we delivered at TLTF. 130 00:08:21,866 --> 00:08:23,707 I put in our financial deck. 131 00:08:23,707 --> 00:08:31,001 do a monthly financial deck where we have all our information and it is uh extremely useful. 132 00:08:31,081 --> 00:08:39,146 And I use it almost like a, almost like a board member that I can bounce ideas off of. 133 00:08:39,146 --> 00:08:47,550 And, you know, it comes with like four little simple actions, know, analyze data, execute tasks, solve problems, build plans. 134 00:08:47,611 --> 00:08:49,960 And when you click on one of those actions, 135 00:08:49,960 --> 00:08:56,844 it then prompts you for what it needs to conduct some sort of, you know, like analyze data. 136 00:08:56,844 --> 00:09:03,498 um So was that the inspiration or did you guys just kind of think of this on your own? 137 00:09:04,078 --> 00:09:08,380 ah Well, we, we worked backwards from, from the problem. 138 00:09:08,380 --> 00:09:15,023 ah We were looking at like, how can we streamline operations and unlock new markets with this? 139 00:09:15,023 --> 00:09:22,757 And so we were looking at like our client base and a lot of the population of America that, that maybe need legal services, but it's just out of reach. 140 00:09:22,757 --> 00:09:28,719 And we found that there are like three key things that keep vast market segments out of even approaching legal services. 141 00:09:28,719 --> 00:09:30,306 that's ah 142 00:09:30,306 --> 00:09:37,908 time, mobility, and money are just like the three things that are completely out of reach for 80 % of the population that could use a lawyer, right? 143 00:09:38,028 --> 00:09:48,971 And so we thought, well, when you do, when a regular person goes to get legal services, a lot of the cost and time is front-loaded in, and just figuring out like, what does this 144 00:09:48,971 --> 00:09:49,552 person need? 145 00:09:49,552 --> 00:09:50,809 What is their situation? 146 00:09:50,809 --> 00:09:53,373 How can I help them as an attorney, right? 147 00:09:53,513 --> 00:09:57,856 And so the use case that we approached, we realized like at... 148 00:09:57,856 --> 00:09:59,828 At first contact, it's six hours. 149 00:09:59,828 --> 00:10:03,761 It's a six hour interview for like, okay, hi, my name is attorney and you are such great. 150 00:10:03,761 --> 00:10:04,482 Thanks for coming in. 151 00:10:04,482 --> 00:10:05,569 What's going on today? 152 00:10:05,569 --> 00:10:07,454 And we're going to write all this down and figure it out. 153 00:10:07,855 --> 00:10:14,540 And, and we, and every one of those conversations follows a pattern that is unique to the practice or the situation. 154 00:10:14,540 --> 00:10:23,548 And we thought, well, you know, what if, what if we could, what if we could apply some AI there to ask, ask the questions, but not according to a script or maybe according to a 155 00:10:23,548 --> 00:10:26,788 script, but better than following a script like a customer service chat bot. 156 00:10:27,054 --> 00:10:33,174 What if it could actually answer a lot of the tertiary questions that come up in that conversation that an attorney could answer for you? 157 00:10:33,174 --> 00:10:36,554 Here's a small but simple example to sort of prove my point. 158 00:10:36,614 --> 00:10:46,134 If somebody needs to fill out a government form and they've brought it to an attorney to help figure this thing out like immigration or things like that, one of the questions is, 159 00:10:46,134 --> 00:10:50,674 or one of the sections on the form is, please list all children that you have, right? 160 00:10:50,734 --> 00:10:53,814 Well, the first question they ask is including stepchildren? 161 00:10:53,814 --> 00:10:57,058 It's not specified anywhere on the form and the attorney knows in that moment, 162 00:10:57,058 --> 00:10:57,988 whether it's yes or no, right? 163 00:10:57,988 --> 00:11:08,161 So, so what if we could capture all of that too, and then have the AI conduct a conversation with the person to gather all the information it needs. 164 00:11:08,241 --> 00:11:13,853 And then from that unstructured data, pull all of that out and auto generate the form and send it to wherever it needs to go. 165 00:11:13,853 --> 00:11:14,503 Right. 166 00:11:14,503 --> 00:11:22,465 And for this use case, it took, it took like what was a six hour interview where somebody had to drive down to see an attorney to take time out of their day. 167 00:11:22,465 --> 00:11:25,406 Oftentimes as people are working, so they're taking time off of work. 168 00:11:25,646 --> 00:11:28,166 Usually I have a friend because maybe English isn't their first language. 169 00:11:28,166 --> 00:11:34,966 So maybe we need the AI to speak a different language or to be able to parse like broken English at worst. 170 00:11:36,346 --> 00:11:41,705 And I don't know, what do you say we make it free because this stuff is getting cheaper and cheaper every day, right? 171 00:11:41,705 --> 00:11:46,766 And so it took that six hour interview and it it down to one to one hour. 172 00:11:46,766 --> 00:11:54,786 And people that are using the system are able to use it on any device in any language they want at any time of day. 173 00:11:55,156 --> 00:11:57,349 And if they want, they can use voice, right? 174 00:11:57,349 --> 00:11:59,561 Because a lot of these things take a long time to type out. 175 00:11:59,561 --> 00:12:01,894 They can do it on their phone, their iPad, whatever, right? 176 00:12:01,894 --> 00:12:04,177 And so that was how it all came about. 177 00:12:04,177 --> 00:12:07,180 We just worked backwards from who needs a product the most. 178 00:12:07,221 --> 00:12:11,266 And if we do this for them, so too could we do this for the industry. 179 00:12:11,266 --> 00:12:13,588 And so that was how it came about. 180 00:12:13,588 --> 00:12:15,048 That was the inspiration for it. 181 00:12:15,048 --> 00:12:15,710 Interesting. 182 00:12:15,710 --> 00:12:16,050 All right. 183 00:12:16,050 --> 00:12:17,903 So like this is matter. 184 00:12:17,903 --> 00:12:19,626 It's a matter intake. 185 00:12:21,932 --> 00:12:23,002 Cool, right? 186 00:12:23,002 --> 00:12:25,063 that situation, that's right. 187 00:12:25,063 --> 00:12:30,145 But really it could be for anything that follows a general script, right? 188 00:12:30,145 --> 00:12:32,096 Doesn't just have to be matter intake. 189 00:12:32,096 --> 00:12:37,588 too, could it be for screening of applications for anything, you know, that kind of thing. 190 00:12:37,648 --> 00:12:41,910 The application for this technology is vast, right? 191 00:12:41,910 --> 00:12:46,772 But so you're right in this situation is matter intake, but you know, we see opportunity for it everywhere. 192 00:12:46,772 --> 00:12:51,790 I mean, can you imagine how many forms of the DMV could be turned into a 193 00:12:51,790 --> 00:12:53,572 turned into a chatbot conversation, right? 194 00:12:53,572 --> 00:12:56,065 um And so that's sort of over-eyeballed. 195 00:12:56,065 --> 00:12:57,116 Yeah, yeah, yeah. 196 00:12:57,116 --> 00:12:59,034 That's the potential use for this. 197 00:12:59,168 --> 00:13:07,074 Yeah, I was just there the other day and em it's incredible the number of times that you have to go back because you don't have the right documents. 198 00:13:07,074 --> 00:13:13,879 know, one time in particular, just recently I had a, they were requiring like two years in Missouri. 199 00:13:13,879 --> 00:13:15,840 The systems don't talk to each other. 200 00:13:15,840 --> 00:13:19,252 So the tax system doesn't talk to the DMV system. 201 00:13:19,252 --> 00:13:25,447 So you have to print out a piece of paper from the tax office that says no taxes due. 202 00:13:25,447 --> 00:13:27,350 They call it a no tax due certificate. 203 00:13:27,350 --> 00:13:30,081 Well, they wanted two years of no tax due. 204 00:13:30,081 --> 00:13:31,992 I only had one year. 205 00:13:31,992 --> 00:13:33,343 The truck was only one year old. 206 00:13:33,343 --> 00:13:37,424 So I'm literally driving back and forth between the tax office and the DMV. 207 00:13:37,424 --> 00:13:40,385 And what an incredible waste of time. 208 00:13:40,385 --> 00:13:42,376 And it was a frustrating situation. 209 00:13:42,376 --> 00:13:47,180 you know, had something like this existed, it would have greased the skids tremendously. 210 00:13:47,180 --> 00:13:47,920 Yeah, for sure. 211 00:13:47,920 --> 00:13:54,504 mean, at best with the current systems today, it's a website with a deep hierarchy that you're just poking around looking for the answer. 212 00:13:54,504 --> 00:13:59,137 Like how many years, if you even think to ask how many years of tax documents, right? 213 00:13:59,137 --> 00:14:02,719 Whereas the AI can proactively assert that, right? 214 00:14:02,719 --> 00:14:07,922 And generate a checklist for you because it knows all about the process and things like that. 215 00:14:07,922 --> 00:14:12,554 Yeah, so it saves everybody time and increases productivity. 216 00:14:12,554 --> 00:14:16,116 There's just like no downside, right, to doing this 217 00:14:17,004 --> 00:14:20,851 So I see huge applications in the A to J world. 218 00:14:20,851 --> 00:14:26,420 Is that in scope here, or are you using this mainly with corporate clients? 219 00:14:27,126 --> 00:14:30,369 No, we're not ruling anything out at this point. 220 00:14:30,369 --> 00:14:41,719 So far in our market research, there's just demand or um unmet needs everywhere where if we position this properly, there's just unlimited upside. 221 00:14:41,719 --> 00:14:45,842 And so that's the hope for the engine that's driving all of this. 222 00:14:46,380 --> 00:14:51,624 So in that particular scenario, you had a 600 % increase in efficiency. 223 00:14:51,624 --> 00:14:54,396 Is that uniform across the board? 224 00:14:54,396 --> 00:15:02,623 Are you seeing higher, lower efficiency gains in other areas where you've applied this tech, or is that staying pretty consistent? 225 00:15:02,623 --> 00:15:04,844 Well, it's consistent. 226 00:15:05,764 --> 00:15:11,307 It depends on the length of like, for example, the complexity of the intake for that moment. 227 00:15:11,307 --> 00:15:15,588 But there's sort of a second order factor that's hard to quantify, but is profound. 228 00:15:15,588 --> 00:15:17,910 ah It's hard to measure. 229 00:15:17,910 --> 00:15:25,813 When you generate the form or whatever and it gets set, or excuse me, when you construct the form from the conversation, right? 230 00:15:25,813 --> 00:15:28,554 And you send it onto wherever it's going. 231 00:15:28,662 --> 00:15:32,445 It can arrive at that inbox with additional analytics. 232 00:15:33,846 --> 00:15:37,709 For immigration, for example, a lot of those answers are open-ended. 233 00:15:37,709 --> 00:15:39,050 Why are you immigrating? 234 00:15:39,050 --> 00:15:40,241 You know, that kind of thing, right? 235 00:15:40,241 --> 00:15:47,837 Then so um the AI has coached people through like pulling out the best version of themselves to put in this document. 236 00:15:47,837 --> 00:15:54,442 But when it arrives to attorney, it can also arrive with like, this answer is really good, but it looks a little soft here. 237 00:15:54,462 --> 00:15:56,413 this part contradicts what they set up here. 238 00:15:56,413 --> 00:15:59,945 You might double down on that when you do finally meet with them, right? 239 00:15:59,945 --> 00:16:07,319 And the net effect of that is when they do meet client for the first time, they're not start, it's not a cold start with like, what's your name? 240 00:16:07,319 --> 00:16:07,620 Right? 241 00:16:07,620 --> 00:16:10,071 No, they're hitting the starting line at a hundred miles an hour. 242 00:16:10,071 --> 00:16:10,691 Right. 243 00:16:10,691 --> 00:16:20,957 The, and, in our experience, the feedback that we've gotten is the fidelity of the initial conversation is just so much richer than, than otherwise than it otherwise would have been 244 00:16:20,957 --> 00:16:22,914 that, that they're achieving just like 245 00:16:22,914 --> 00:16:29,537 velocity and cruise and like cruising speed way earlier in the engagement with this client. 246 00:16:29,537 --> 00:16:38,961 And so, you know, the system doesn't, systems don't exist to measure that kind of like thing yet, but we can, it's, tangible. 247 00:16:38,961 --> 00:16:49,216 And if we could measure it in, in vibes and feedback and enthusiasm, like that we've received back for that kind of thing. 248 00:16:49,358 --> 00:16:53,855 uh It's blowing, you know, it's blowing away expectations exceeding exceedingly. 249 00:16:53,855 --> 00:16:57,010 So yeah, so so yeah, that's that's the upside 250 00:16:57,010 --> 00:16:58,174 Vibe intake. 251 00:16:58,174 --> 00:17:00,005 That's, that's what you're doing is right. 252 00:17:00,005 --> 00:17:00,135 it. 253 00:17:00,135 --> 00:17:00,446 Yeah. 254 00:17:00,446 --> 00:17:01,476 Yeah. 255 00:17:03,126 --> 00:17:03,857 hilarious. 256 00:17:03,857 --> 00:17:06,622 um I've seen like vibe lawyering. 257 00:17:06,622 --> 00:17:07,844 um 258 00:17:09,516 --> 00:17:11,196 You know, obviously vibe coding. 259 00:17:11,196 --> 00:17:15,956 That's, that's the new, um, that's the new hot word is, is vibe. 260 00:17:15,956 --> 00:17:29,276 What, what about, so this, this required R and D and you know, that's one of the, I've really been beating this drum with legal clients is to think about, you know, R and D is a 261 00:17:29,276 --> 00:17:31,116 foreign concept of law firms. 262 00:17:31,176 --> 00:17:36,616 Um, on average, they spend 1 % of operating costs on R and D. 263 00:17:36,616 --> 00:17:39,402 The average, the average company. 264 00:17:39,402 --> 00:17:39,622 Right. 265 00:17:39,622 --> 00:17:43,943 This includes, you know, across the across the industries is 4%. 266 00:17:43,943 --> 00:17:46,766 So they spend one for, and that's due to a number of different things. 267 00:17:46,766 --> 00:17:55,781 I think one of the big drivers is the fact that law firms use cash basis accounting, which is actually a small business accounting approach. 268 00:17:55,801 --> 00:18:04,506 IRS has rules where if you're over more than, if you're more than 25 million in revenue, you have to use accrual based accounting and then R and D makes sense. 269 00:18:04,506 --> 00:18:04,816 Right. 270 00:18:04,816 --> 00:18:07,948 You have a mechanism to amortize expense over 271 00:18:08,062 --> 00:18:13,717 over multiple years, but it's completely foreign to law firms and they're going to have to shift that. 272 00:18:13,717 --> 00:18:23,225 I'm not saying they're going to have to, you know, switch to accrual accounting, but they're going to have to shift their mindset to a place where instead of thinking about 273 00:18:23,225 --> 00:18:24,976 ROI, I need ROI. 274 00:18:24,976 --> 00:18:36,936 You know, I hear that from a lot of law firm leaders when they talk about AI investment and it's like, you know, your return on investment, your return sometimes is learning. 275 00:18:37,040 --> 00:18:44,064 or it's the accumulation of intellectual property that allows you to enable capabilities like the ones you guys built. 276 00:18:44,064 --> 00:18:57,431 How did your firm wrap their head around conceptualizing R and D and ultimately getting partners, some of which are, you know, two years from retirement and they're not going to 277 00:18:57,431 --> 00:19:01,633 see the break even on this until maybe further down the road. 278 00:19:01,633 --> 00:19:05,935 How did, how did you build support and change the mindset around that? 279 00:19:06,023 --> 00:19:09,045 Well, it starts with the right leadership. 280 00:19:09,045 --> 00:19:15,051 Our C-suite is pretty forward thinking and I'd say tech interested, if not enthusiastic. 281 00:19:15,051 --> 00:19:17,773 Also, that is a trust exercise as well. 282 00:19:17,773 --> 00:19:25,899 We had to start small and generate small wins such that the firm had the confidence that like dollars they invested into our program were well spent. 283 00:19:26,701 --> 00:19:29,262 And so that's where it started. 284 00:19:29,503 --> 00:19:31,555 But I take your point. 285 00:19:31,555 --> 00:19:33,058 I like what you're saying about like, 286 00:19:33,058 --> 00:19:37,110 This actually R &D is sort of antithetical to the existing model, right? 287 00:19:37,110 --> 00:19:43,106 Like it doesn't really, doesn't really make sense to try to disrupt something that's going so well. 288 00:19:43,286 --> 00:19:55,176 you know, this last generation of technology has really introduced, in my opinion, some existential, you know, threats, if not important conversations that need to be had about 289 00:19:55,176 --> 00:19:55,996 this. 290 00:19:56,738 --> 00:20:01,701 And I think it's because like historically, if you look at like the arc of technology innovation, 291 00:20:02,808 --> 00:20:06,561 The innovations and the disruption rarely come from within any company. 292 00:20:06,561 --> 00:20:19,392 It's more so that the incumbents, the uh existing big players, usually they don't enjoy it so much as they get T-boned by at the intersection of innovation, technology, and market 293 00:20:19,392 --> 00:20:20,432 forces. 294 00:20:21,193 --> 00:20:27,488 So if we take streaming, for example, like... 295 00:20:28,258 --> 00:20:32,959 You know, Blockbuster was never going to invest in a Netflix disruptor, right? 296 00:20:32,959 --> 00:20:36,820 Because their, their existing business was doing just fine, right? 297 00:20:36,820 --> 00:20:40,021 They weren't nobody, there was no interest in like messing with a great thing. 298 00:20:40,021 --> 00:20:47,013 ah CNN was never going to invent YouTube any more than cable was going to invent like streaming, right? 299 00:20:47,013 --> 00:20:58,264 Like, ah and so, uh so to do our leaders think that will be the case for this new and burgeoning technology, law firms are not inherently gauged. 300 00:20:58,264 --> 00:20:59,465 for this kind of activity. 301 00:20:59,465 --> 00:21:02,846 You have to make a conscious effort and really push on it. 302 00:21:02,846 --> 00:21:04,757 And it's not a mayfly project either. 303 00:21:04,757 --> 00:21:11,120 Like this is an initiative and if anything, a huge culture shift has to take place here. 304 00:21:11,120 --> 00:21:20,874 Now to answer your question about how we do that, the answer is uh by starting small and with the leadership in the firm and showing them like, this is what we're doing, this is 305 00:21:20,874 --> 00:21:22,104 how it's useful. 306 00:21:22,104 --> 00:21:26,356 We're not gonna push this into your practice group without your say so like. 307 00:21:26,442 --> 00:21:27,372 All of that stuff, right? 308 00:21:27,372 --> 00:21:36,688 We need everybody to go in eyes wide open about, you know, um the upside to this, but also like the risks that you adopt inherently when you bring something like this into your 309 00:21:36,688 --> 00:21:37,288 practice, right? 310 00:21:37,288 --> 00:21:41,701 And so that's how, that was how GWT was able to make it happen. 311 00:21:41,701 --> 00:21:45,913 And to date, over 50 % of the firm uses the app every day now. 312 00:21:45,913 --> 00:21:48,264 um And that's a lot of people, right? 313 00:21:48,264 --> 00:21:51,606 But that didn't happen overnight, to your point, right? 314 00:21:51,606 --> 00:21:53,037 That was a slow burn. 315 00:21:53,037 --> 00:21:55,078 But yeah, so that's how we did it. 316 00:21:55,134 --> 00:21:55,634 Interesting. 317 00:21:55,634 --> 00:21:55,874 Yeah. 318 00:21:55,874 --> 00:22:00,526 I had a LinkedIn post recently where I mapped out. 319 00:22:00,526 --> 00:22:14,300 you know, my, my position is that AI, it is an extinction level event for the traditional law firm model and product market fit for the traditional model is crumbling beneath our 320 00:22:14,300 --> 00:22:15,130 feet. 321 00:22:15,310 --> 00:22:22,392 And we've got headwinds in the legal industry that are holding us back from 322 00:22:23,350 --> 00:22:35,923 being the Netflix of the world and you know, the, the, the reasons, the, sources of those headwinds I mapped out consensus driven, driven decision-making slows rates of change, 323 00:22:35,923 --> 00:22:37,084 lateral mobility. 324 00:22:37,084 --> 00:22:44,816 So the fact that law firm part, even partners can take their book of business and move down the street also creates challenges. 325 00:22:44,816 --> 00:22:51,408 Why am going to write checks and invest in a, in a capital project when I might be down the street in three years? 326 00:22:51,408 --> 00:22:52,672 Um, 327 00:22:52,672 --> 00:22:56,154 Healthy profit margins make the status quo sticky. 328 00:22:56,154 --> 00:22:59,365 Cash basis accounting and retirement horizons, which we talked about. 329 00:22:59,365 --> 00:23:01,876 Law schools aren't keeping pace. 330 00:23:01,876 --> 00:23:04,577 Only around half even offer AI courses. 331 00:23:04,577 --> 00:23:06,938 Half, which blows my mind. 332 00:23:07,218 --> 00:23:08,999 That number should be in the 90s. 333 00:23:08,999 --> 00:23:16,783 um Empowering non-lawyer managers, the business professionals, that's a tough sell. 334 00:23:16,783 --> 00:23:18,844 um It doesn't always happen. 335 00:23:18,844 --> 00:23:20,224 Risk aversion. 336 00:23:20,460 --> 00:23:26,040 Lawyers are naturally risk avoidant and R &D requires risk. 337 00:23:26,040 --> 00:23:30,980 And then finally, and I think this is a big one, it's lack of diversity within law firm leadership. 338 00:23:30,980 --> 00:23:36,100 If you look at law firm leadership, it's a bunch of old white dudes primarily, right? 339 00:23:36,100 --> 00:23:50,480 I looked at something like 50 % of, I found this stat somewhere on the internet, 50 % of executive committee membership is male, 55 and older. 340 00:23:50,666 --> 00:23:51,016 Right. 341 00:23:51,016 --> 00:23:59,853 The people who really understand this technology best, and this is, there's data on this from McKinsey, it's millennials, right? 342 00:23:59,853 --> 00:24:07,049 They need to have a seat at the leadership table, not just your director of innovation, who's four levels down from the XCOM. 343 00:24:07,049 --> 00:24:16,336 They need to have a seat at the table where conversations are had about capital deployment and it's not happening for the most part today. 344 00:24:16,336 --> 00:24:17,176 So. 345 00:24:17,302 --> 00:24:17,914 I don't know, man. 346 00:24:17,914 --> 00:24:23,531 I feels like the firms that manage these headwinds most effectively are going to be the long, longterm winners. 347 00:24:23,531 --> 00:24:24,521 You agree? 348 00:24:25,544 --> 00:24:27,055 yeah, it's coming. 349 00:24:27,055 --> 00:24:36,259 problem, part of the problem Ted is that, you know, for all of the progress that's been made, this tech has only really been mainstream for the last two years. 350 00:24:36,259 --> 00:24:40,500 Before that, you didn't want to be the guy in the room who's like, no, believe me, computers will talk to you one day. 351 00:24:40,500 --> 00:24:42,621 You know, like it was, it was still a weird thing, right? 352 00:24:42,621 --> 00:24:44,902 um But, but you're right. 353 00:24:44,902 --> 00:24:53,226 Those of us that are in it can, can see clearly what, what is happening, especially given the history of technology and the way it disrupts industries. 354 00:24:53,226 --> 00:24:54,336 It, it, takes. 355 00:24:54,336 --> 00:25:00,529 It gives, but it takes, I love the points in your blog post, by the way. 356 00:25:00,529 --> 00:25:02,809 I want to back up to like models changing. 357 00:25:02,930 --> 00:25:11,813 Part of the problem with like us saying that models change or like business models need to change is the data doesn't support it yet, but we can clearly see it right. 358 00:25:11,813 --> 00:25:13,384 Because the industry is growing. 359 00:25:13,384 --> 00:25:21,437 So legal service spend is, is, is growing as, uh, as our clients are, as they start to adopt this new technology. 360 00:25:21,437 --> 00:25:24,358 You know, that said, there's, um 361 00:25:24,524 --> 00:25:28,016 Something is happening with the tech that I think is going to catch everybody by surprise. 362 00:25:28,016 --> 00:25:35,630 Where it is most suited today is with like large high volume matters that are pretty consistent in the way these things are handled. 363 00:25:35,630 --> 00:25:36,440 Right. 364 00:25:36,440 --> 00:25:41,963 Now the technology is doing great to improve the quality and streamline those services. 365 00:25:41,963 --> 00:25:53,059 It's increasing in efficacy, but ah the barriers to entry and adoption are also decreasing such that you don't actually need an expert lawyer to string together some of these 366 00:25:53,059 --> 00:25:54,698 systems and 367 00:25:54,698 --> 00:26:02,521 And all you really need is a really motivated like BA, business analyst, with some guidance from a supercharged paralegal or an associate partner. 368 00:26:02,521 --> 00:26:05,963 And they can get really effective with this stuff really fast. 369 00:26:05,963 --> 00:26:13,586 And whether that happens at a law firm or in-house, you know, there's no, there's no like moat saying like that knowledge has to be locked up anywhere. 370 00:26:13,586 --> 00:26:15,006 So that's going to be a thing. 371 00:26:15,006 --> 00:26:16,077 Make of that what you will. 372 00:26:16,077 --> 00:26:24,242 But like that is going to be a thing all law firms will have to navigate is the increasing efficacy and power of the technology. 373 00:26:24,242 --> 00:26:25,933 as it operates in-house, right? 374 00:26:25,933 --> 00:26:31,988 That's gonna be a I also love what you said about uh lateral movement. 375 00:26:31,988 --> 00:26:41,576 um Who would have thought 10 years ago that one of the first questions any lateral asks when they're hiring a new firm is like, well, what's your technology stack like, right? 376 00:26:41,576 --> 00:26:42,577 Like that's a new thing. 377 00:26:42,577 --> 00:26:43,697 Who's your CIO? 378 00:26:43,697 --> 00:26:48,301 know, like that's a, does your firm managing partner stand on like technology adoption, right? 379 00:26:48,301 --> 00:26:49,710 And it doesn't stop there. 380 00:26:49,710 --> 00:26:55,010 you can see a future in which like M &A, these are tough questions that are getting asked upfront, right? 381 00:26:55,250 --> 00:27:05,730 Like when you are looking to bring in 80 attorneys and their tech stack and stuff, so the question will ask, like, do you guys have any, or they will ask the question, where are 382 00:27:05,730 --> 00:27:06,310 you with AI? 383 00:27:06,310 --> 00:27:07,650 Do you have AI systems? 384 00:27:07,650 --> 00:27:08,770 Who are your AI vendors? 385 00:27:08,770 --> 00:27:09,170 Right? 386 00:27:09,170 --> 00:27:16,630 Like it bears mentioning that that will be a first-class citizen concern in all M &A and not just for law firms, but all industries going forward. 387 00:27:16,630 --> 00:27:17,070 Right. 388 00:27:17,070 --> 00:27:18,990 But I think the thing that you said, 389 00:27:19,554 --> 00:27:27,749 you know, about the incoming generation is, it's pointed and it, it, and it is front and center for me lately. 390 00:27:27,749 --> 00:27:35,444 It's on my mind because I had the good fortune of going to a Stanford CodeX hackathon uh a few weeks ago. 391 00:27:35,544 --> 00:27:44,972 CodeX is a, is a program at Stanford University that strategy that it sits between the computer science program and the uh law in the law school, right? 392 00:27:44,972 --> 00:27:50,605 And it's sort of right now it's, acting as a conduit between the two to introduce both to each other with AI. 393 00:27:50,686 --> 00:27:51,947 And it's exceptional. 394 00:27:51,947 --> 00:27:56,370 If you, if you get a chance, your listeners might be interested in learning more about it. 395 00:27:56,370 --> 00:27:58,001 Look at Megan Ma at Stanford. 396 00:27:58,001 --> 00:27:59,662 She's, she's spectacular leader. 397 00:27:59,662 --> 00:28:05,475 She's built this program up to be so good, but we got to go down to their hackathon. 398 00:28:05,496 --> 00:28:08,358 Um, and Ted, I'm getting goosebumps as I even think about it. 399 00:28:08,358 --> 00:28:15,072 You would not believe the things that I saw in the, in the 12 hour hackathon, as we got to mentor and coach these, these kids. 400 00:28:15,124 --> 00:28:23,738 I'm going to give you, if it's okay, I'd love to give you just two examples of the apps that I saw built, but the big thing is about the way these kids did it, which I think is 401 00:28:23,738 --> 00:28:26,198 going to be most interesting to law firms. 402 00:28:26,779 --> 00:28:36,113 In 12 hours with the power of AI, random teams that were assigned, kids that had never met before, sometimes they had a coder, sometimes they didn't, churned out, they had 12 hours 403 00:28:36,113 --> 00:28:37,623 to churn out an AI powered app. 404 00:28:37,623 --> 00:28:38,924 And some of these things were amazing. 405 00:28:38,924 --> 00:28:42,145 The first one was called Claim Hero. 406 00:28:42,145 --> 00:28:43,726 What Claim Hero does is, 407 00:28:44,416 --> 00:28:49,087 It uses AI to help regular people like you and me appeal denied medical claims. 408 00:28:49,127 --> 00:28:49,848 Like it's amazing. 409 00:28:49,848 --> 00:28:50,838 And it was really good. 410 00:28:50,838 --> 00:28:52,658 Like it wasn't like, this is a prototype. 411 00:28:52,658 --> 00:28:53,268 We call it together. 412 00:28:53,268 --> 00:28:53,789 Here's mockups. 413 00:28:53,789 --> 00:28:56,109 No, like it was a full blown prototype. 414 00:28:56,109 --> 00:29:00,040 um These kids were using AI assisted development tools. 415 00:29:00,040 --> 00:29:05,582 were practically talking to a computer and it was building the app that they, that they were inspired to build. 416 00:29:05,582 --> 00:29:06,372 Right. 417 00:29:06,492 --> 00:29:08,053 Excuse me. 418 00:29:08,053 --> 00:29:12,034 The next one, the one that won was called GovMatch. 419 00:29:12,034 --> 00:29:13,294 And what this app does, 420 00:29:13,294 --> 00:29:15,694 This is a team of MBAs and an engineer. 421 00:29:15,694 --> 00:29:25,574 They realize that when you're a small business and you're working on gigs like government contracts or whatever, it's really hard to service a contract and find the new one at the 422 00:29:25,574 --> 00:29:26,074 same time. 423 00:29:26,074 --> 00:29:31,534 What you end up with is like this lurching business model where you're working a gig and you finish it now you've got to find the next gig. 424 00:29:31,534 --> 00:29:32,494 You're not making money. 425 00:29:32,494 --> 00:29:38,194 Then you find it and you start making money again and then you finish that gig and you stop making money while you find the next one. 426 00:29:38,194 --> 00:29:42,342 Well, what they did was they built an agent that 427 00:29:42,390 --> 00:29:51,316 It's just always looking for the next gig and pitching you and filling out the RFPs and submitting your thing and then plugging it in to where it made sense on your calendar. 428 00:29:51,317 --> 00:29:52,468 Ted, and was really good. 429 00:29:52,468 --> 00:29:55,100 Like this wasn't like jakey stuff that kids were putting together. 430 00:29:55,100 --> 00:30:02,465 Like, and so my takeaway there is great software is table stakes now with AI, with AI enabled development teams. 431 00:30:02,465 --> 00:30:06,148 Anybody can build anything and, in record time. 432 00:30:06,148 --> 00:30:07,429 Now, was it production ready? 433 00:30:07,429 --> 00:30:08,490 Of course not. 434 00:30:08,490 --> 00:30:09,206 It was. 435 00:30:09,206 --> 00:30:11,107 It was a product, but it wasn't a company yet. 436 00:30:11,107 --> 00:30:12,968 There's a lot more that goes into it. 437 00:30:13,009 --> 00:30:19,153 but my, My point is like, this tech is enabling people to create as quickly as they can think. 438 00:30:19,153 --> 00:30:19,874 And that's amazing. 439 00:30:19,874 --> 00:30:27,139 But, but how does this relate to law firms in the in coming generation of people to have, we're not ready for it. 440 00:30:27,139 --> 00:30:30,701 No one, no one in our generation is when I, when I was watching. 441 00:30:30,701 --> 00:30:35,744 there was an auditorium and a lot of tables with like engineering teams and kids sitting around doing their thing. 442 00:30:35,885 --> 00:30:38,086 But what I saw is 443 00:30:38,356 --> 00:30:40,628 A, these kids are amazing collaborators. 444 00:30:40,628 --> 00:30:43,450 They grew up in an era of co-authoring. 445 00:30:43,450 --> 00:30:46,872 None of them have used word solo mode like us. 446 00:30:46,872 --> 00:30:52,396 Their entire being has just been co-authoring everything, right? 447 00:30:52,396 --> 00:30:56,638 They've a totally connected world, multiplayer only, right? 448 00:30:56,638 --> 00:31:07,186 That's just, they just collaborate so well with groups of strangers coming together and just being able to mix and match ideas and thoughts and put pen to paper or fingers to 449 00:31:07,186 --> 00:31:07,906 keys or... 450 00:31:07,906 --> 00:31:11,677 voice to AI or whatever the mechanism is, they can do it well at scale. 451 00:31:11,677 --> 00:31:17,349 But the other thing that was interesting is I would watch a team release a really cool feature, right? 452 00:31:17,349 --> 00:31:21,290 And they'd post it to Insta or whatever the social media platform of choices. 453 00:31:21,290 --> 00:31:25,731 And I would watch all the phones light up across the auditorium. 454 00:31:25,731 --> 00:31:28,592 And it was like a beehive kicking into gear. 455 00:31:28,592 --> 00:31:29,532 did you see what they've got? 456 00:31:29,532 --> 00:31:30,732 We've got to add that to ourself. 457 00:31:30,732 --> 00:31:34,463 And table by table, as the idea spread, the whole thing came alive. 458 00:31:34,463 --> 00:31:38,154 And so the rate of information distribution 459 00:31:38,228 --> 00:31:47,905 and assimilation is so much faster than a corporate memo to us would ever matriculate across like a large population of people. 460 00:31:47,905 --> 00:31:53,729 It was a hive mind like operating at a higher level than like we've ever experienced. 461 00:31:53,729 --> 00:32:02,635 And I don't know what that means, but I sense that's profound and that's gonna mean some different things for the industry as these creative like minds come into play. 462 00:32:02,635 --> 00:32:03,256 right? 463 00:32:03,256 --> 00:32:06,870 There's no way, there's no way any hiring recruiter 464 00:32:06,870 --> 00:32:13,456 is gonna make any sense at all to these kids in an interview when they start asking questions about like, what is team collaboration like? 465 00:32:13,456 --> 00:32:15,338 And we're like, well, we schedule meetings. 466 00:32:15,338 --> 00:32:16,338 You know what I mean? 467 00:32:16,338 --> 00:32:19,521 And we circulate a link to a document, right? 468 00:32:19,521 --> 00:32:22,784 And that is gonna look just slow. 469 00:32:22,784 --> 00:32:23,885 That's just gonna look slow to them. 470 00:32:23,885 --> 00:32:27,548 Yeah, so who knows what that means, but it means something. 471 00:32:27,548 --> 00:32:29,830 And we're gonna be here to see it firsthand. 472 00:32:29,830 --> 00:32:32,723 Yeah, that was a soapbox, but you get what I mean, right? 473 00:32:32,723 --> 00:32:33,204 Like. 474 00:32:33,204 --> 00:32:34,134 good stuff, man. 475 00:32:34,134 --> 00:32:35,915 And that's a really good point. 476 00:32:35,915 --> 00:32:37,016 I had another post. 477 00:32:37,016 --> 00:32:43,080 I'm plugging my LinkedIn post here, but I think it's super relevant to what you just talked about. 478 00:32:43,080 --> 00:32:43,720 So Dr. 479 00:32:43,720 --> 00:32:49,754 Larry Richard uh wrote a book called Lawyer Brain and he has conducted like 35 years of research. 480 00:32:49,754 --> 00:32:57,068 He surveyed over 30,000 attorneys and he has a list of traits in which 481 00:32:57,068 --> 00:33:01,788 attorneys score either much higher or much lower than the general population. 482 00:33:02,208 --> 00:33:07,788 So high in skepticism, high in autonomy, high in urgency, high in abstract reasoning. 483 00:33:07,788 --> 00:33:18,168 Few of these are assets to innovation, urgency, abstract reasoning, low sociability, low resilience, low empathy. 484 00:33:18,168 --> 00:33:22,588 Those are inhibitors to innovation. 485 00:33:23,048 --> 00:33:27,168 I heard a podcast with 486 00:33:27,424 --> 00:33:34,606 Um, Andrew Huberman and Mark Andreessen and Mark Andreessen mapped out the five traits of an innovator. 487 00:33:34,606 --> 00:33:37,087 And who knows more about innovation than Mark Andreessen. 488 00:33:37,087 --> 00:33:46,149 mean, that dude invented the web browser literally, and then has spent the last 30 plus years as a VC in Silicon Valley. 489 00:33:46,149 --> 00:33:54,212 He knows he writes checks based on his assessment of a founder's ability to exhibit these traits. 490 00:33:54,212 --> 00:33:56,214 Those traits are open to many new. 491 00:33:56,214 --> 00:34:00,517 kinds of ideas, not lawyers, um, high level of conscientiousness. 492 00:34:00,517 --> 00:34:03,389 That's lawyers, high and disagreeableness. 493 00:34:03,389 --> 00:34:06,111 That's definitely lawyers, high IQ. 494 00:34:06,111 --> 00:34:07,632 They're definitely smart people. 495 00:34:07,632 --> 00:34:09,553 Um, high in resilience. 496 00:34:09,553 --> 00:34:10,994 That's not lawyers. 497 00:34:11,034 --> 00:34:21,401 So we've got a gap and it's, it's not, I'm not saying like lawyers can't be innovative, but if you look at the bell curve, the ones that are tend to be outliers, they're, they're 498 00:34:21,401 --> 00:34:23,413 really past focus. 499 00:34:23,413 --> 00:34:25,804 Like practicing the law requires 500 00:34:25,898 --> 00:34:28,509 the concept of precedent, right? 501 00:34:28,509 --> 00:34:33,730 And it's a backward looking uh practice or discipline. 502 00:34:33,730 --> 00:34:36,731 Risk orientation, lawyers are risk averse. 503 00:34:36,731 --> 00:34:43,053 uh Outlook, innovators are very optimistic, lawyers are uh skeptic. 504 00:34:43,053 --> 00:34:49,214 uh Comfort with ambiguity, innovators extremely high, lawyers low. 505 00:34:50,075 --> 00:34:53,645 Resilience to setbacks, relationship to status quo. 506 00:34:53,645 --> 00:34:55,990 There's all these different markers 507 00:34:55,990 --> 00:35:00,522 So it's not that, hey, blow up your innovation committee and put a bunch of millennials on there. 508 00:35:00,522 --> 00:35:01,745 I'm not saying that at all. 509 00:35:01,745 --> 00:35:09,191 But what I'm saying is the lawyer perspective is necessary, but not sufficient um for innovation in law firms. 510 00:35:09,191 --> 00:35:10,572 And they need to augment. 511 00:35:10,572 --> 00:35:20,230 They need to bring in business professionals, younger ones who really grasp this technology, those digital natives that have that beehive mindset and bring a different 512 00:35:20,230 --> 00:35:22,582 dimension to the conversation. 513 00:35:22,582 --> 00:35:24,984 Because if we just have innovation, 514 00:35:25,216 --> 00:35:31,741 council or committee of only lawyers, it's not, it's probably we're missing opportunities. 515 00:35:31,741 --> 00:35:36,765 So I think there's real lessons to be learned in what you experienced. 516 00:35:36,765 --> 00:35:45,362 And I don't know how we communicate that like without seeing it firsthand like you did, but it's those, there are lessons there. 517 00:35:46,006 --> 00:35:46,956 Yeah, I agree. 518 00:35:46,956 --> 00:35:59,443 think, I think, um, gosh, I just, get so excited to think about it because if, if channeled correctly, um, it could be a superpower for any firm that has to evolve their, 519 00:35:59,443 --> 00:36:02,915 their platform and their offering faster and faster. 520 00:36:02,915 --> 00:36:11,400 Um, what you can't do, um, is assemble a board of people that sit around just thinking big thoughts and then like inventing things and then go into market and hoping there's a 521 00:36:11,400 --> 00:36:12,290 problem that it solves. 522 00:36:12,290 --> 00:36:12,921 Right. 523 00:36:12,921 --> 00:36:15,724 I think that, I think that the, um, 524 00:36:15,724 --> 00:36:24,948 The problems will be appearing so quickly that you're going to need, you're going to need a culture that can evolve and adapt on the fly and generate new product offerings and new 525 00:36:24,948 --> 00:36:35,742 ways of thinking about services faster and faster because the needs of our clients will be evolving in step with how quickly their core technology offerings are as well. 526 00:36:36,022 --> 00:36:44,962 You can imagine, you know, any large technology company, how different their needs are today than they were a year ago because they can move faster and, um, 527 00:36:44,962 --> 00:36:49,523 get into new territory and new lines of business faster than ever before, right? 528 00:36:49,523 --> 00:36:57,525 And so it might be that your law firm just doesn't have services available for like the new ground that they're covering, right? 529 00:36:57,525 --> 00:37:07,608 But it could, if you have a team of people that can assemble these things and think differently about the offerings or even the new business models that they grew up with. 530 00:37:07,608 --> 00:37:14,156 Like for example, kids today, even saying kids today, I realized like, 531 00:37:14,156 --> 00:37:18,800 where I'm at in my career is, well, I remember being that kid with crazy ideas and no one would listen to it, right? 532 00:37:18,800 --> 00:37:20,351 It's like, no, you don't understand. 533 00:37:20,351 --> 00:37:21,292 I see it every day. 534 00:37:21,292 --> 00:37:26,837 You guys have been locked up in this big building, like heads down doing great work, but things are changing out there and it's coming, right? 535 00:37:26,837 --> 00:37:33,242 um They've grown up in a world with completely different billing models where everything is just a monthly service charge, right? 536 00:37:33,242 --> 00:37:35,464 For all you can eat or at some kind of thing, right? 537 00:37:35,464 --> 00:37:42,956 And so, so maybe like they bring in the ability to see ways of bundling legal services where 538 00:37:42,956 --> 00:37:52,573 Maybe the AFAs are commoditized and done cheaply, but at a higher rate for litigation services and mixing and matching these things to best meet the situation that clients are 539 00:37:52,573 --> 00:37:54,654 now uh navigating, right? 540 00:37:54,654 --> 00:37:58,457 Like, uh I think we're going to need that kind of thing. 541 00:37:58,457 --> 00:38:00,558 And it's not going to happen by default. 542 00:38:00,558 --> 00:38:11,425 I do think this is going to be a conscious decision that leaders make to create environments where that kind of culture can thrive and good ideas can come out of. 543 00:38:11,425 --> 00:38:12,398 uh 544 00:38:12,398 --> 00:38:15,938 Because if you don't, it's someone else will. 545 00:38:15,938 --> 00:38:22,238 Maybe it won't be a law firm, but it will happen to the incumbents one way or another. 546 00:38:22,378 --> 00:38:32,078 I just want to point out, we've had the last, well, for the last 30 years, like it's been the same 30 tech companies that sort of ruled the roost, right? 547 00:38:32,078 --> 00:38:35,578 But they were not the big tech companies 30 years ago. 548 00:38:35,578 --> 00:38:39,734 There was a time when today's companies were small startups. 549 00:38:39,734 --> 00:38:42,535 looking out a way to disrupt existing industries. 550 00:38:42,535 --> 00:38:51,339 Ted, 30 years ago, who were the incumbents, the gigantic companies that nobody thought could ever tumble, right? 551 00:38:51,339 --> 00:38:54,511 The major phone companies, big networking companies, right? 552 00:38:54,511 --> 00:38:58,542 Big faceless, the IBMs, everything, right? 553 00:38:58,542 --> 00:39:02,604 And who would have thought that they could ever be disrupted? 554 00:39:02,604 --> 00:39:03,515 And they didn't. 555 00:39:03,515 --> 00:39:07,146 The internet came along and they didn't disrupt themselves, right? 556 00:39:07,148 --> 00:39:17,661 They used it as a tool to enhance their service offerings, but it wasn't until this generation of natives that the certain like the Googles, the Yahu's that those early 557 00:39:17,661 --> 00:39:23,423 adopters, like the Amazons got out there to Facebook's and MySpaces use this technology. 558 00:39:23,963 --> 00:39:26,684 And they realized like those incumbents were not the ceiling, right? 559 00:39:26,684 --> 00:39:29,925 That was actually the floor that they could build all these new cool services on. 560 00:39:29,925 --> 00:39:32,918 And wouldn't you know it disrupt them at the same time, right? 561 00:39:32,918 --> 00:39:45,067 missed opportunities left and right as this new technology and these new types of companies and ideas started to form that could solve problems for clients that the big 562 00:39:45,067 --> 00:39:50,711 guys were just too big to be nimble enough to maneuver around in ad service offerings for, right? 563 00:39:50,711 --> 00:39:54,863 That is the period that we are approaching with this new technology. 564 00:39:54,863 --> 00:40:01,698 Like the incumbents are the ceiling, but that's not where this technology is just going to smash right through it and you're going to see. 565 00:40:01,716 --> 00:40:03,988 new types of like things being built. 566 00:40:03,988 --> 00:40:14,825 If I had to guess, if I had to forecast like what happens over the next period of time, like with this tech, I legitimately believe the top 10 firms of the 2030s are being 567 00:40:14,825 --> 00:40:19,819 determined right now because these things are happening at hackathons and in garages. 568 00:40:19,819 --> 00:40:23,601 ALSP's are popping up that are AI first, right? 569 00:40:23,601 --> 00:40:29,005 And maybe it's not as good as like a large law firm, but their technology is good enough and it's way cheaper. 570 00:40:29,005 --> 00:40:30,996 So like maybe that's enough to get by. 571 00:40:31,178 --> 00:40:45,110 And so, um you know, if you play, if you just sort of look a little bit into the future, you can see where, um you know, people do some really interesting stuff and invent new 572 00:40:45,110 --> 00:40:46,231 markets with it, right? 573 00:40:46,231 --> 00:40:48,653 Or new ways to interact with customers. 574 00:40:48,653 --> 00:40:50,934 Like it's all within reach now. 575 00:40:51,115 --> 00:40:56,419 And the crazy thing is just like in the 90s, look at what they did with super slow internet. 576 00:40:56,419 --> 00:40:57,340 You know what I mean? 577 00:40:57,340 --> 00:40:59,301 Two kilobits per second? 578 00:40:59,402 --> 00:41:00,332 I mean, 579 00:41:00,438 --> 00:41:08,899 And that's where we are with this tech, like our language models in 10 years that we have today are going to look downright primitive because this technology is only getting 580 00:41:08,899 --> 00:41:09,201 faster. 581 00:41:09,201 --> 00:41:13,362 There's nothing to indicate it's going to slow down in efficacy or ability. 582 00:41:13,362 --> 00:41:14,082 Right. 583 00:41:14,082 --> 00:41:21,634 And so ah I think the real question is who's, who's nimble enough, which of the three firms will you be in the future? 584 00:41:21,634 --> 00:41:24,105 Will you be, will you be a new one? 585 00:41:24,125 --> 00:41:27,316 Will you be one that's merging with a new one? 586 00:41:27,534 --> 00:41:35,634 Or will you be a boutique or purpose-built technology firm that offers some kind of digital service, right? 587 00:41:35,634 --> 00:41:39,954 Because it's going to be the floor is raising for what will be acceptable. 588 00:41:39,954 --> 00:41:43,593 And I think that's what we're looking at over the next 10, 15 years. 589 00:41:43,593 --> 00:41:46,342 The next chapter of law looks just like that. 590 00:41:47,018 --> 00:42:04,197 Yeah, and if you are in that &A scenario where you're merging and you're not the technical leader, you're not adept, your multiple on your business is going to be miserable, right? 591 00:42:04,197 --> 00:42:09,860 You're going to be getting sold at a fire sale price because really, what do you have? 592 00:42:09,860 --> 00:42:11,160 You have people. 593 00:42:11,280 --> 00:42:15,082 And um it's not that people are going away. 594 00:42:15,082 --> 00:42:16,908 I actually, you know, there's a lot of 595 00:42:16,908 --> 00:42:20,568 Chicken Little out there in the marketplace like, the sky's falling. 596 00:42:20,568 --> 00:42:21,768 I don't think that at all. 597 00:42:21,768 --> 00:42:23,608 I think the sky's falling. 598 00:42:23,868 --> 00:42:28,288 If you don't take action, I think there are opportunities. 599 00:42:28,288 --> 00:42:31,928 There's going to be a reshuffling of the deck in the AMLAW. 600 00:42:31,928 --> 00:42:35,088 And I've used this comparison many times. 601 00:42:35,088 --> 00:42:42,508 If you look at the big four, which they're also a partnership model and they have their own issues, but the combined revenue of the big four is 220 billion. 602 00:42:42,508 --> 00:42:47,074 The combined revenue of the AMLAW 100 is like 140 billion. 603 00:42:47,074 --> 00:42:47,205 Mm. 604 00:42:47,205 --> 00:42:47,904 Mm-hmm. 605 00:42:47,904 --> 00:42:57,387 It's extremely fragmented and there's going to be consolidation as we move into this tech enabled legal services era. 606 00:42:57,407 --> 00:42:57,737 Right. 607 00:42:57,737 --> 00:43:01,428 Because it's not, it's no longer bespoke law. 608 00:43:01,428 --> 00:43:08,069 Legal work is, is moving from, you know, bespoke nature to the assembly line. 609 00:43:08,070 --> 00:43:10,110 And there's still going to be bespoke work. 610 00:43:10,110 --> 00:43:17,164 There there's always going to be, there are special unique needs associated, but man, there is a lot, um, that 611 00:43:17,164 --> 00:43:20,744 can absolutely make its way to the production line. 612 00:43:20,744 --> 00:43:32,664 And if you're just a production line worker, if you're a craftsman, what sort of value are you going to bring to the firm that's acquiring you that has this tech-enabled legal 613 00:43:32,664 --> 00:43:34,104 machine that they invested in? 614 00:43:34,104 --> 00:43:36,196 Probably not a lot of value there. 615 00:43:37,270 --> 00:43:40,632 Yeah, I think, man, I'm on board. 616 00:43:40,632 --> 00:43:41,983 think it hollows out the middle. 617 00:43:41,983 --> 00:43:43,434 Like technology has a habit. 618 00:43:43,434 --> 00:43:47,097 Like when it explodes into an industry, it has a habit of like bifurcating industries. 619 00:43:47,097 --> 00:43:50,939 And what you end up with is a couple winners at the very top. 620 00:43:50,939 --> 00:43:54,742 And then everybody else just fighting for like boutique status just to get noticed, right? 621 00:43:54,742 --> 00:43:56,763 What is your thing that makes you different? 622 00:43:56,923 --> 00:44:05,689 I mean, if we look at, look at the internet today, I mean, Netflix is streaming, Facebook is social, LinkedIn is professional. 623 00:44:05,689 --> 00:44:07,054 ah 624 00:44:07,054 --> 00:44:08,574 Amazon is shopping, right? 625 00:44:08,574 --> 00:44:11,094 There are like 20 websites, tops that actually matter. 626 00:44:11,094 --> 00:44:11,654 You know what I mean? 627 00:44:11,654 --> 00:44:14,814 In terms of like the economy and scale and things like that. 628 00:44:14,814 --> 00:44:20,614 And so if we, you know, if we, if we play that out, like in the industry, you're right. 629 00:44:20,614 --> 00:44:24,534 The real question is like, how do you, how do you get big and achieve scale? 630 00:44:24,554 --> 00:44:26,694 Like how can you leverage a first movers advantage? 631 00:44:26,694 --> 00:44:28,494 Cause that's what they all have in common. 632 00:44:28,494 --> 00:44:35,314 The big ones that, that we have today, those top 30 firms that we, we talked about earlier, they got in there fast. 633 00:44:35,314 --> 00:44:35,798 They, 634 00:44:35,798 --> 00:44:37,209 It wasn't enough to just be first. 635 00:44:37,209 --> 00:44:38,229 That's like the saving grace. 636 00:44:38,229 --> 00:44:39,720 Like you can be first and still get it wrong. 637 00:44:39,720 --> 00:44:41,960 There are a lot of first mice out there, right? 638 00:44:42,561 --> 00:44:44,822 My space is a great example, right? 639 00:44:45,162 --> 00:44:54,045 But whoever shows up in that early pack, maybe second, can demonstrate good enough uh efficiency with the technology, right? 640 00:44:54,426 --> 00:44:57,607 Build a dedicated workforce that understands their customers. 641 00:44:57,607 --> 00:45:04,620 But third, create that moat that sort of, that helps you achieve scale that's almost impossible to penetrate. 642 00:45:04,620 --> 00:45:15,836 Facebook's like button, Amazon's affiliate program, um There are these things that incumbents can do to sort of solidify like the next quarter century of like business for 643 00:45:15,836 --> 00:45:16,296 themselves. 644 00:45:16,296 --> 00:45:25,421 And in my opinion, I think the situation will be the same for any industry that the technology sort of crashes through the wall into. 645 00:45:26,342 --> 00:45:33,736 So that's, you know, I think, but to that point, to your point earlier about R &D and like how does this all tie together. 646 00:45:34,200 --> 00:45:38,093 Well, you don't want to be as a law firm as a forced buyer of technology. 647 00:45:38,093 --> 00:45:41,755 What you don't want to do is wake up and realize the market has caught up to you and it's time to change. 648 00:45:41,755 --> 00:45:45,438 Blockbuster realized that all too late, right? 649 00:45:45,438 --> 00:45:52,823 What you can't start doing, this is a tough sell in any partnership, is at the same time the revenues are going down because you're being chipped away, someone's going to show up 650 00:45:52,823 --> 00:45:58,066 and say, we should invest in R &D at the same time and start eating away at the bottom line from another angle. 651 00:45:58,146 --> 00:46:00,938 That's a bad situation. 652 00:46:00,938 --> 00:46:04,320 That looks more like desperation than innovation. 653 00:46:04,550 --> 00:46:08,512 And so you've got to hedge your bets and you've got to be ready for it. 654 00:46:08,512 --> 00:46:17,856 If not actively doing it, then planning for like, what is the maneuver that your firm um will pull off to stay at the cutting edge and ahead of the pack, right? 655 00:46:17,856 --> 00:46:20,977 um So yeah, yeah. 656 00:46:21,097 --> 00:46:22,104 What do you think? 657 00:46:22,104 --> 00:46:25,246 and we see, I already see early signs. 658 00:46:25,246 --> 00:46:26,766 It is very early. 659 00:46:26,766 --> 00:46:36,850 it's by no way can you pick out winners and losers here, but you're starting to see some early indicators. 660 00:46:36,850 --> 00:46:44,494 um Firms who I talked to a good friend of mine who's a director at innovation about a 400 attorney law firm. 661 00:46:44,494 --> 00:46:48,555 And I asked her what the strategy is with AI. 662 00:46:48,595 --> 00:46:50,156 And she said, well, we're piloting 663 00:46:50,156 --> 00:46:52,018 20 co-pilot licenses. 664 00:46:52,018 --> 00:46:53,759 And I was like, what else? 665 00:46:53,759 --> 00:46:56,301 We'll call her Sarah for this. 666 00:46:56,301 --> 00:46:57,622 What else are you doing, Sarah? 667 00:46:57,622 --> 00:47:04,356 Well, it's a conservative board and they really want to focus on ROI. 668 00:47:04,488 --> 00:47:09,932 And I'm looking at that picture and then I'm looking at what you guys are doing, what Cleary is doing. 669 00:47:09,932 --> 00:47:15,237 There's early signs with like, you look at Cooley and the team that they're assembling at Cooley. 670 00:47:15,237 --> 00:47:18,407 um I'm seeing, again, these are early signs. 671 00:47:18,407 --> 00:47:19,614 It doesn't mean that 672 00:47:19,614 --> 00:47:29,269 everybody who is making these early moves is going to be the ultimate winners, but you're already starting to see this parting of the seas. 673 00:47:29,670 --> 00:47:42,056 man, unless there's some pretty um dramatic course correction, you know, once, once momentum is heads you in a direction, it's really hard, just like you said, to pivot 674 00:47:42,056 --> 00:47:48,800 because again, while times are good, you need to be investing while you have, you know, the 675 00:47:48,800 --> 00:47:59,570 the margin to do it because once things start heading south, it's, you know, the scarcity kicks in and then it's a, it's a race to the exits. 676 00:47:59,570 --> 00:48:04,114 So, um, it's been really cool to see what, you guys are doing there. 677 00:48:04,114 --> 00:48:10,180 I've actually known your firm for a long time, a lot and Penn who she was probably there before. 678 00:48:10,180 --> 00:48:11,240 you know her? 679 00:48:11,374 --> 00:48:13,734 Yeah, I caught the tail end of her stay at DWT. 680 00:48:13,734 --> 00:48:14,574 She was wonderful. 681 00:48:14,574 --> 00:48:16,114 Yeah, yeah, I loved long. 682 00:48:16,274 --> 00:48:16,663 Yeah. 683 00:48:16,663 --> 00:48:27,331 I met her 10 years ago at a lean Six Sigma black belt conference, uh, not black belt, but it was a, it was a Six Sigma event in legal that arc put on. 684 00:48:27,412 --> 00:48:29,894 Um, so yeah, like that was another early sign. 685 00:48:29,894 --> 00:48:35,838 Like honestly, based on the fact of their presence at that event, I would have said, you know what? 686 00:48:35,838 --> 00:48:42,538 These guys are thinking ahead because there's not a lot of, I'm a lean Six Sigma black belt and I, 687 00:48:42,538 --> 00:48:46,173 I pay attention when I see firms adopting methodologies like that. 688 00:48:46,173 --> 00:48:47,264 You don't see it a lot. 689 00:48:47,264 --> 00:48:49,437 It does exist, but it's pretty rare. 690 00:48:49,437 --> 00:48:51,559 Again, outliers, long tail. 691 00:48:51,559 --> 00:48:54,513 um So it's cool to see what you guys are doing. 692 00:48:54,513 --> 00:48:58,598 I know we're running out of time here, but um man, this has been a fun conversation. 693 00:48:58,990 --> 00:49:00,172 Yeah, thanks for having me, Ted. 694 00:49:00,172 --> 00:49:01,374 I really appreciate it. 695 00:49:01,374 --> 00:49:09,168 And I think the work you're doing in the community to, you know, elevate the consciousness, you know, about all of the stuff and where it's all headed. 696 00:49:09,168 --> 00:49:10,630 So yeah, thanks for having me. 697 00:49:10,686 --> 00:49:11,296 Absolutely. 698 00:49:11,296 --> 00:49:15,389 Well, you know, our livelihood is tied exclusively to law firms. 699 00:49:15,389 --> 00:49:18,941 Like we have a hundred percent law firm clients. 700 00:49:18,941 --> 00:49:23,753 like, really want a lot of people, I've gotten feedback before like, man, you're really negative on the industry. 701 00:49:23,753 --> 00:49:24,934 Like, no, I'm not negative at all. 702 00:49:24,934 --> 00:49:26,065 I love this industry. 703 00:49:26,065 --> 00:49:28,026 I've been here almost 20 years. 704 00:49:28,026 --> 00:49:28,926 I love it. 705 00:49:28,926 --> 00:49:30,167 I want to stay in it. 706 00:49:30,167 --> 00:49:34,609 I just, I'm trying to raise the flat, the red flag, like guys, we got to start thinking differently. 707 00:49:34,609 --> 00:49:39,812 So it's good to see, uh, it's good to see firms like DWT. 708 00:49:40,278 --> 00:49:41,760 do it and then get recognized. 709 00:49:41,760 --> 00:49:44,241 So congratulations on the award. 710 00:49:44,241 --> 00:49:45,103 That's a big one, man. 711 00:49:45,103 --> 00:49:51,259 We've had two clients win that award for intranets that we've built for them and we had a front row seat to the process. 712 00:49:51,259 --> 00:49:52,711 It is highly competitive. 713 00:49:52,711 --> 00:49:56,284 So kudos for winning that recognition. 714 00:49:56,600 --> 00:49:57,140 Well, thanks. 715 00:49:57,140 --> 00:49:57,461 Yeah. 716 00:49:57,461 --> 00:50:07,848 And I, I, I appreciate it, but like I tell everybody, I'm just a paint job on, on, on a team that for a team that's doing great work, the engine that, drives this innovation, our 717 00:50:07,848 --> 00:50:10,800 leaders are our engineers, our attorneys. 718 00:50:10,800 --> 00:50:21,937 Um, one thing, if I could, uh, since we're talking about DWT, one of the cool things about the crescendo engine is that, um, it wasn't built in a bubble for the first time in DWT 719 00:50:21,937 --> 00:50:24,649 history, maybe the legal industry, this internal innovation. 720 00:50:24,649 --> 00:50:26,434 Um, they, 721 00:50:26,434 --> 00:50:29,915 They put this up for the entire firm to test before we went live with it. 722 00:50:29,915 --> 00:50:43,279 had over 75 attorneys, councils, paralegals, professional staff show up and commit hours to testing this thing because it had, it's a zero fault, zero tolerance like environment. 723 00:50:43,279 --> 00:50:47,700 Like we can't even risk a single mistake, the system making a single mistake. 724 00:50:47,760 --> 00:50:55,382 And so the firm got behind this, not to put too fine a point on it, but that's a demonstration of culture I have never seen anywhere. 725 00:50:55,382 --> 00:50:55,682 Right? 726 00:50:55,682 --> 00:50:58,326 Like a commitment to innovation and excellence. 727 00:50:58,326 --> 00:51:07,037 And so to that, know, I much gratitude to the firm to make sure that this thing was as bulletproof as possible before we put it into production. 728 00:51:07,037 --> 00:51:14,062 And so just one of the reasons I love working here, because like I said, the leadership is, a huge part of making all of this happen. 729 00:51:14,062 --> 00:51:14,784 Yep. 730 00:51:14,784 --> 00:51:21,767 I think it was Jack Welsh that used to talk to former CEO of GE's talk about the tone at the top, right? 731 00:51:21,767 --> 00:51:24,158 The tone at the top dictates the culture, man. 732 00:51:24,158 --> 00:51:27,129 You got to have that leadership buy-in. 733 00:51:27,809 --> 00:51:37,848 and, another, uh, metaphor is, you know, culture eats strategy for breakfast, right? 734 00:51:37,848 --> 00:51:41,615 It doesn't matter how good your strategy is, if your culture doesn't support it. 735 00:51:41,615 --> 00:51:44,626 So it's good to hear that you guys are doing it right. 736 00:51:44,854 --> 00:51:45,505 Well, cool, man. 737 00:51:45,505 --> 00:51:46,908 It was great talking to you. 738 00:51:46,908 --> 00:51:48,590 Good conversation as always. 739 00:51:48,590 --> 00:51:55,110 um Look forward to seeing you at a conference and finding other ways to collaborate to get the word out. 740 00:51:55,374 --> 00:51:56,094 Yeah, me too. 741 00:51:56,094 --> 00:51:56,698 Thanks a Ted. 742 00:51:56,698 --> 00:51:57,300 Thanks for having me. 743 00:51:57,300 --> 00:51:59,406 Good to see you. 744 00:51:59,406 --> 00:52:00,108 Bye. 00:00:05,163 Dan Szabo, how are you this afternoon? 2 00:00:05,166 --> 00:00:05,976 I'm doing great. 3 00:00:05,976 --> 00:00:06,623 Glad to be here. 4 00:00:06,623 --> 00:00:07,436 Thanks for having me. 5 00:00:07,436 --> 00:00:08,076 Awesome, man. 6 00:00:08,076 --> 00:00:10,696 I appreciate you taking a little bit of time. 7 00:00:11,596 --> 00:00:11,696 Yeah. 8 00:00:11,696 --> 00:00:19,376 When I saw the, your post about winning the transformative project of the year from Ilta, I knew I had to reach out. 9 00:00:19,376 --> 00:00:27,776 I'd saw you speak at the inside practice event last spring, spring of 23 and or I get no 24. 10 00:00:27,776 --> 00:00:29,136 Thought you did a great job. 11 00:00:29,136 --> 00:00:31,816 So yeah, man, I'm excited to have you on the podcast. 12 00:00:32,200 --> 00:00:32,611 me too. 13 00:00:32,611 --> 00:00:34,553 I'm actually a long time listener and reader. 14 00:00:34,553 --> 00:00:41,049 uh Yeah, thanks for everything you do to keep minds operating at the cutting edge of the industry. 15 00:00:41,049 --> 00:00:43,462 Really excited to be here and appreciate the invite. 16 00:00:43,462 --> 00:00:44,396 Thanks for having 17 00:00:44,396 --> 00:00:45,056 Awesome, man. 18 00:00:45,056 --> 00:00:46,416 I'm glad to hear that. 19 00:00:46,416 --> 00:00:46,596 Yeah. 20 00:00:46,596 --> 00:00:49,636 I started the podcast, like was never on a bucket list. 21 00:00:49,636 --> 00:00:53,896 I started having conversations like the one you and I had the last time we spoke. 22 00:00:53,896 --> 00:00:55,596 And I was like, man, you know what? 23 00:00:55,596 --> 00:00:59,796 People would, people would listen to this and it just kind of happened. 24 00:00:59,796 --> 00:01:04,516 I did three episodes before Ilta two years ago and released them. 25 00:01:04,516 --> 00:01:06,096 And I was like, man, nobody's going to see this. 26 00:01:06,096 --> 00:01:10,516 And like five, seven people came by the booth and goes, Hey, podcast is awesome. 27 00:01:10,516 --> 00:01:11,096 I was like, wow. 28 00:01:11,096 --> 00:01:13,056 Like people, people will listen. 29 00:01:13,056 --> 00:01:13,572 So 30 00:01:14,306 --> 00:01:14,566 Yeah. 31 00:01:14,566 --> 00:01:16,287 Well, but, on that note, they do. 32 00:01:16,287 --> 00:01:20,002 And congratulations on your award as well, uh from Alta. 33 00:01:20,002 --> 00:01:20,833 That was great news. 34 00:01:20,833 --> 00:01:22,455 was very excited to see it. 35 00:01:22,455 --> 00:01:25,458 They know quality when they see it, right? 36 00:01:25,458 --> 00:01:25,787 Yeah. 37 00:01:25,787 --> 00:01:26,137 man. 38 00:01:26,137 --> 00:01:32,960 I, was shortlisted for that award 10 years ago, 10 years prior and didn't win it and then reapplied. 39 00:01:32,960 --> 00:01:39,603 And, um, I think they would have felt bad if they made me get all dressed up in a suit and go to an awards dinner twice. 40 00:01:41,544 --> 00:01:42,364 But I'll take it. 41 00:01:42,364 --> 00:01:43,564 I'll take it. 42 00:01:43,845 --> 00:01:45,145 well let's get you introduced, man. 43 00:01:45,145 --> 00:01:46,706 So I was looking at your background. 44 00:01:46,706 --> 00:01:51,978 It looks like you studied computer science in, uh, in college and 45 00:01:52,000 --> 00:01:55,343 You had some app dev gigs prior to stepping into legal. 46 00:01:55,343 --> 00:02:03,070 Um, you worked with littler, for a little while and now you're a senior director of innovation at DWT. 47 00:02:03,070 --> 00:02:04,421 Um, fill in the gaps, man. 48 00:02:04,421 --> 00:02:10,638 Like what, tell us a little bit about kind of your role and your day to day and what, know, all that sort of stuff. 49 00:02:10,638 --> 00:02:10,898 Sure. 50 00:02:10,898 --> 00:02:16,903 Well, I actually got into software development when I was in the army across multiple deployments to Iraq. 51 00:02:16,984 --> 00:02:22,749 I was really interested in coding and figuring out how apps were being made. 52 00:02:22,749 --> 00:02:28,003 Smartphones were starting to show up and um I've always been interested in technology. 53 00:02:28,003 --> 00:02:33,750 And so at night between guard duty shifts, I would be studying with a Sam's teacher self book and a flashlight. 54 00:02:33,750 --> 00:02:41,837 And I'm like the tiniest laptop I could find because it needed to fit in my cargo pocket so I could take it with me on guard duty and tours and stuff. 55 00:02:41,837 --> 00:02:44,499 And so, yeah, that's kind of how I cut my teeth on it. 56 00:02:44,499 --> 00:02:53,787 um And then when I got out, I got picked up at Hewlett Packard as a tools developer for consultants and contractors on the ground. 57 00:02:53,787 --> 00:03:00,713 So just like rapid development, um fixing stuff that's broken and building apps for new use cases on the fly. 58 00:03:00,713 --> 00:03:02,094 ah But yeah, then... 59 00:03:02,094 --> 00:03:02,854 um 60 00:03:03,130 --> 00:03:08,384 A friend of a friend told me this law firm in San Francisco was looking at doing something on this platform called KSmart. 61 00:03:08,384 --> 00:03:12,018 They really wanted to go next level with it and they were hiring for it. 62 00:03:12,018 --> 00:03:15,641 And that is how I got into the industry. 63 00:03:15,641 --> 00:03:21,245 was a high volume platform, kind of a first of its kind. 64 00:03:21,245 --> 00:03:25,859 And so they were really navigating like this new cutting edge ground as a law firm. 65 00:03:25,859 --> 00:03:32,206 And what I didn't know at the time is that it was very unusual for law firms to be developing software themselves. 66 00:03:32,206 --> 00:03:33,186 Cause I was an outsider. 67 00:03:33,186 --> 00:03:33,786 I didn't know. 68 00:03:33,786 --> 00:03:36,886 And so it was just always normal to me to be doing that. 69 00:03:36,886 --> 00:03:40,346 And only after being in the industry for a few years that I realized how unique it was. 70 00:03:40,346 --> 00:03:44,486 Well, fast forward to today, uh, DWT wanted to do the same thing. 71 00:03:44,486 --> 00:03:48,246 And, and, um, I was trying to get to the Northwest and so it was a great match. 72 00:03:48,246 --> 00:03:51,746 And here we are, um, senior director of innovation. 73 00:03:52,086 --> 00:03:56,946 We're, uh, cranking out apps that are, you know, frankly, really, really good. 74 00:03:57,666 --> 00:04:01,100 Um, uh, our latest hit, dbt.ai is a, 75 00:04:01,100 --> 00:04:03,361 large language model that's running inside of the platform. 76 00:04:03,361 --> 00:04:12,413 And we're using that as a floor to scaffold new productivity apps on top of, uh like Crescendo that you mentioned earlier. 77 00:04:12,413 --> 00:04:14,228 And so yeah, that's how we got here. 78 00:04:14,629 --> 00:04:16,284 What is that based on? 79 00:04:16,284 --> 00:04:19,944 Is that a llama-based implementation? 80 00:04:20,236 --> 00:04:20,556 Sure. 81 00:04:20,556 --> 00:04:27,793 So dwt.ai is actually a collection of different technologies working to deliver a chat GPT like experience. 82 00:04:27,793 --> 00:04:37,421 So it is based on open AI, but we do pull in other language models just depending on like the kind of like prompts that's being asked or the kind of solution that we're trying to 83 00:04:37,421 --> 00:04:40,202 deliver based on the use case. 84 00:04:40,543 --> 00:04:48,980 so, yeah, it's an amalgam of different specialties that work in concert to deliver a good experience for our attorneys. 85 00:04:49,332 --> 00:04:49,872 Interesting. 86 00:04:49,872 --> 00:04:57,258 So one of the things that struck me about Crescendo, and we're going to talk about that in just a minute, is you guys kind of flip the script. 87 00:04:57,319 --> 00:05:03,984 And before we dive down that rabbit hole, let's talk for a minute about just the limitations. 88 00:05:03,984 --> 00:05:18,455 The current paradigm is you've got a text box and you type in a prompt and it gives you a response and you refine, maybe include some documents. 89 00:05:19,670 --> 00:05:23,346 for rag purposes and you eventually work your way to an answer. 90 00:05:23,346 --> 00:05:31,250 um What are some of the limitations that spurred you to look in other directions with that model? 91 00:05:31,566 --> 00:05:32,426 Sure. 92 00:05:32,526 --> 00:05:35,406 So we've been at this about 18 months now. 93 00:05:35,406 --> 00:05:47,406 It's been in production for about 18 months and we've had a lot of opportunity to watch attorneys in the wild using AI and not just attorneys, but professional staff as well. 94 00:05:47,406 --> 00:05:57,326 the technology is great, but the experience has some subtle limitations that I think we were uniquely keen to because we sort of rushed to the table to figure this out. 95 00:05:57,326 --> 00:05:59,566 The first is that 96 00:05:59,990 --> 00:06:01,552 Uh, it's reactive. 97 00:06:01,552 --> 00:06:10,178 You actually, when you're working on a document or you're doing something, you have to stop what you're doing, go to a browser tab, paste in your prompt or type it in whatever 98 00:06:10,479 --> 00:06:12,241 and, hit go. 99 00:06:12,241 --> 00:06:15,384 And so that's subtly disruptive. 100 00:06:15,384 --> 00:06:19,137 But the, but the real insight is that this is with a large language model. 101 00:06:19,137 --> 00:06:21,959 This is actually, it's not a technical exercise. 102 00:06:21,959 --> 00:06:27,662 It's a trust exercise because you're pasting something into a box with an undetermined response. 103 00:06:27,662 --> 00:06:28,922 anything could come back. 104 00:06:28,922 --> 00:06:32,322 And so you're just kind of hoping that like a good answer comes back. 105 00:06:32,322 --> 00:06:38,322 And there's a trust breach there that creates friction for user adoption, for efficacy of the results. 106 00:06:38,322 --> 00:06:40,082 It invites additional scrutiny. 107 00:06:40,082 --> 00:06:49,142 And so in some situations when you use AI, it actually slows the process down because of the additional layers of review it takes when people know AI was used, right? 108 00:06:49,182 --> 00:06:51,622 And so that's not something anybody has solved. 109 00:06:51,622 --> 00:06:54,162 And the technology will never fully solve it. 110 00:06:54,162 --> 00:06:56,678 We'll never get a 100 % accurate LLM. 111 00:06:57,250 --> 00:07:10,429 So, but one thing that we realized with the tech is that it's actually, it's good at generating answers, but what it's really good at is answering questions or generating 112 00:07:10,429 --> 00:07:12,831 questions for you to answer. 113 00:07:12,831 --> 00:07:16,463 What we realized is in this trust exercise, there's two parties. 114 00:07:16,543 --> 00:07:19,185 One can hallucinate, the other usually doesn't. 115 00:07:19,185 --> 00:07:21,667 One has known good information and the other one doesn't. 116 00:07:21,667 --> 00:07:26,680 So we thought, well, you know, this whole reactive experience is actually sort of working against us on. 117 00:07:26,680 --> 00:07:27,931 tougher use cases. 118 00:07:27,931 --> 00:07:29,692 So what if we create a proactive AI? 119 00:07:29,692 --> 00:07:35,476 What if the AI prompts you and gets the good information from you and then does something useful with that instead? 120 00:07:35,476 --> 00:07:46,143 And that was what unlocked the next level of AI interaction uh and is the premise for the crescendo engine, is the proof in the pudding. 121 00:07:46,143 --> 00:07:48,164 Once we figured that out, it just took off. 122 00:07:48,164 --> 00:07:51,666 um And so that was the unique insight that set it free. 123 00:07:51,980 --> 00:07:52,360 Interesting. 124 00:07:52,360 --> 00:07:55,101 And you see that with some custom GPTs. 125 00:07:55,101 --> 00:07:57,841 um I think they call them actions. 126 00:07:58,222 --> 00:08:02,023 You specify actions and they're essentially questions. 127 00:08:02,023 --> 00:08:15,746 I have one that I use called um CoCEO and I basically put in all of our um core values. 128 00:08:15,746 --> 00:08:18,683 I put in our ideal customer profile information. 129 00:08:18,683 --> 00:08:21,866 I put in the pitch deck that we delivered at TLTF. 130 00:08:21,866 --> 00:08:23,707 I put in our financial deck. 131 00:08:23,707 --> 00:08:31,001 do a monthly financial deck where we have all our information and it is uh extremely useful. 132 00:08:31,081 --> 00:08:39,146 And I use it almost like a, almost like a board member that I can bounce ideas off of. 133 00:08:39,146 --> 00:08:47,550 And, you know, it comes with like four little simple actions, know, analyze data, execute tasks, solve problems, build plans. 134 00:08:47,611 --> 00:08:49,960 And when you click on one of those actions, 135 00:08:49,960 --> 00:08:56,844 it then prompts you for what it needs to conduct some sort of, you know, like analyze data. 136 00:08:56,844 --> 00:09:03,498 um So was that the inspiration or did you guys just kind of think of this on your own? 137 00:09:04,078 --> 00:09:08,380 ah Well, we, we worked backwards from, from the problem. 138 00:09:08,380 --> 00:09:15,023 ah We were looking at like, how can we streamline operations and unlock new markets with this? 139 00:09:15,023 --> 00:09:22,757 And so we were looking at like our client base and a lot of the population of America that, that maybe need legal services, but it's just out of reach. 140 00:09:22,757 --> 00:09:28,719 And we found that there are like three key things that keep vast market segments out of even approaching legal services. 141 00:09:28,719 --> 00:09:30,306 that's ah 142 00:09:30,306 --> 00:09:37,908 time, mobility, and money are just like the three things that are completely out of reach for 80 % of the population that could use a lawyer, right? 143 00:09:38,028 --> 00:09:48,971 And so we thought, well, when you do, when a regular person goes to get legal services, a lot of the cost and time is front-loaded in, and just figuring out like, what does this 144 00:09:48,971 --> 00:09:49,552 person need? 145 00:09:49,552 --> 00:09:50,809 What is their situation? 146 00:09:50,809 --> 00:09:53,373 How can I help them as an attorney, right? 147 00:09:53,513 --> 00:09:57,856 And so the use case that we approached, we realized like at... 148 00:09:57,856 --> 00:09:59,828 At first contact, it's six hours. 149 00:09:59,828 --> 00:10:03,761 It's a six hour interview for like, okay, hi, my name is attorney and you are such great. 150 00:10:03,761 --> 00:10:04,482 Thanks for coming in. 151 00:10:04,482 --> 00:10:05,569 What's going on today? 152 00:10:05,569 --> 00:10:07,454 And we're going to write all this down and figure it out. 153 00:10:07,855 --> 00:10:14,540 And, and we, and every one of those conversations follows a pattern that is unique to the practice or the situation. 154 00:10:14,540 --> 00:10:23,548 And we thought, well, you know, what if, what if we could, what if we could apply some AI there to ask, ask the questions, but not according to a script or maybe according to a 155 00:10:23,548 --> 00:10:26,788 script, but better than following a script like a customer service chat bot. 156 00:10:27,054 --> 00:10:33,174 What if it could actually answer a lot of the tertiary questions that come up in that conversation that an attorney could answer for you? 157 00:10:33,174 --> 00:10:36,554 Here's a small but simple example to sort of prove my point. 158 00:10:36,614 --> 00:10:46,134 If somebody needs to fill out a government form and they've brought it to an attorney to help figure this thing out like immigration or things like that, one of the questions is, 159 00:10:46,134 --> 00:10:50,674 or one of the sections on the form is, please list all children that you have, right? 160 00:10:50,734 --> 00:10:53,814 Well, the first question they ask is including stepchildren? 161 00:10:53,814 --> 00:10:57,058 It's not specified anywhere on the form and the attorney knows in that moment, 162 00:10:57,058 --> 00:10:57,988 whether it's yes or no, right? 163 00:10:57,988 --> 00:11:08,161 So, so what if we could capture all of that too, and then have the AI conduct a conversation with the person to gather all the information it needs. 164 00:11:08,241 --> 00:11:13,853 And then from that unstructured data, pull all of that out and auto generate the form and send it to wherever it needs to go. 165 00:11:13,853 --> 00:11:14,503 Right. 166 00:11:14,503 --> 00:11:22,465 And for this use case, it took, it took like what was a six hour interview where somebody had to drive down to see an attorney to take time out of their day. 167 00:11:22,465 --> 00:11:25,406 Oftentimes as people are working, so they're taking time off of work. 168 00:11:25,646 --> 00:11:28,166 Usually I have a friend because maybe English isn't their first language. 169 00:11:28,166 --> 00:11:34,966 So maybe we need the AI to speak a different language or to be able to parse like broken English at worst. 170 00:11:36,346 --> 00:11:41,705 And I don't know, what do you say we make it free because this stuff is getting cheaper and cheaper every day, right? 171 00:11:41,705 --> 00:11:46,766 And so it took that six hour interview and it it down to one to one hour. 172 00:11:46,766 --> 00:11:54,786 And people that are using the system are able to use it on any device in any language they want at any time of day. 173 00:11:55,156 --> 00:11:57,349 And if they want, they can use voice, right? 174 00:11:57,349 --> 00:11:59,561 Because a lot of these things take a long time to type out. 175 00:11:59,561 --> 00:12:01,894 They can do it on their phone, their iPad, whatever, right? 176 00:12:01,894 --> 00:12:04,177 And so that was how it all came about. 177 00:12:04,177 --> 00:12:07,180 We just worked backwards from who needs a product the most. 178 00:12:07,221 --> 00:12:11,266 And if we do this for them, so too could we do this for the industry. 179 00:12:11,266 --> 00:12:13,588 And so that was how it came about. 180 00:12:13,588 --> 00:12:15,048 That was the inspiration for it. 181 00:12:15,048 --> 00:12:15,710 Interesting. 182 00:12:15,710 --> 00:12:16,050 All right. 183 00:12:16,050 --> 00:12:17,903 So like this is matter. 184 00:12:17,903 --> 00:12:19,626 It's a matter intake. 185 00:12:21,932 --> 00:12:23,002 Cool, right? 186 00:12:23,002 --> 00:12:25,063 that situation, that's right. 187 00:12:25,063 --> 00:12:30,145 But really it could be for anything that follows a general script, right? 188 00:12:30,145 --> 00:12:32,096 Doesn't just have to be matter intake. 189 00:12:32,096 --> 00:12:37,588 too, could it be for screening of applications for anything, you know, that kind of thing. 190 00:12:37,648 --> 00:12:41,910 The application for this technology is vast, right? 191 00:12:41,910 --> 00:12:46,772 But so you're right in this situation is matter intake, but you know, we see opportunity for it everywhere. 192 00:12:46,772 --> 00:12:51,790 I mean, can you imagine how many forms of the DMV could be turned into a 193 00:12:51,790 --> 00:12:53,572 turned into a chatbot conversation, right? 194 00:12:53,572 --> 00:12:56,065 um And so that's sort of over-eyeballed. 195 00:12:56,065 --> 00:12:57,116 Yeah, yeah, yeah. 196 00:12:57,116 --> 00:12:59,034 That's the potential use for this. 197 00:12:59,168 --> 00:13:07,074 Yeah, I was just there the other day and em it's incredible the number of times that you have to go back because you don't have the right documents. 198 00:13:07,074 --> 00:13:13,879 know, one time in particular, just recently I had a, they were requiring like two years in Missouri. 199 00:13:13,879 --> 00:13:15,840 The systems don't talk to each other. 200 00:13:15,840 --> 00:13:19,252 So the tax system doesn't talk to the DMV system. 201 00:13:19,252 --> 00:13:25,447 So you have to print out a piece of paper from the tax office that says no taxes due. 202 00:13:25,447 --> 00:13:27,350 They call it a no tax due certificate. 203 00:13:27,350 --> 00:13:30,081 Well, they wanted two years of no tax due. 204 00:13:30,081 --> 00:13:31,992 I only had one year. 205 00:13:31,992 --> 00:13:33,343 The truck was only one year old. 206 00:13:33,343 --> 00:13:37,424 So I'm literally driving back and forth between the tax office and the DMV. 207 00:13:37,424 --> 00:13:40,385 And what an incredible waste of time. 208 00:13:40,385 --> 00:13:42,376 And it was a frustrating situation. 209 00:13:42,376 --> 00:13:47,180 you know, had something like this existed, it would have greased the skids tremendously. 210 00:13:47,180 --> 00:13:47,920 Yeah, for sure. 211 00:13:47,920 --> 00:13:54,504 mean, at best with the current systems today, it's a website with a deep hierarchy that you're just poking around looking for the answer. 212 00:13:54,504 --> 00:13:59,137 Like how many years, if you even think to ask how many years of tax documents, right? 213 00:13:59,137 --> 00:14:02,719 Whereas the AI can proactively assert that, right? 214 00:14:02,719 --> 00:14:07,922 And generate a checklist for you because it knows all about the process and things like that. 215 00:14:07,922 --> 00:14:12,554 Yeah, so it saves everybody time and increases productivity. 216 00:14:12,554 --> 00:14:16,116 There's just like no downside, right, to doing this 217 00:14:17,004 --> 00:14:20,851 So I see huge applications in the A to J world. 218 00:14:20,851 --> 00:14:26,420 Is that in scope here, or are you using this mainly with corporate clients? 219 00:14:27,126 --> 00:14:30,369 No, we're not ruling anything out at this point. 220 00:14:30,369 --> 00:14:41,719 So far in our market research, there's just demand or um unmet needs everywhere where if we position this properly, there's just unlimited upside. 221 00:14:41,719 --> 00:14:45,842 And so that's the hope for the engine that's driving all of this. 222 00:14:46,380 --> 00:14:51,624 So in that particular scenario, you had a 600 % increase in efficiency. 223 00:14:51,624 --> 00:14:54,396 Is that uniform across the board? 224 00:14:54,396 --> 00:15:02,623 Are you seeing higher, lower efficiency gains in other areas where you've applied this tech, or is that staying pretty consistent? 225 00:15:02,623 --> 00:15:04,844 Well, it's consistent. 226 00:15:05,764 --> 00:15:11,307 It depends on the length of like, for example, the complexity of the intake for that moment. 227 00:15:11,307 --> 00:15:15,588 But there's sort of a second order factor that's hard to quantify, but is profound. 228 00:15:15,588 --> 00:15:17,910 ah It's hard to measure. 229 00:15:17,910 --> 00:15:25,813 When you generate the form or whatever and it gets set, or excuse me, when you construct the form from the conversation, right? 230 00:15:25,813 --> 00:15:28,554 And you send it onto wherever it's going. 231 00:15:28,662 --> 00:15:32,445 It can arrive at that inbox with additional analytics. 232 00:15:33,846 --> 00:15:37,709 For immigration, for example, a lot of those answers are open-ended. 233 00:15:37,709 --> 00:15:39,050 Why are you immigrating? 234 00:15:39,050 --> 00:15:40,241 You know, that kind of thing, right? 235 00:15:40,241 --> 00:15:47,837 Then so um the AI has coached people through like pulling out the best version of themselves to put in this document. 236 00:15:47,837 --> 00:15:54,442 But when it arrives to attorney, it can also arrive with like, this answer is really good, but it looks a little soft here. 237 00:15:54,462 --> 00:15:56,413 this part contradicts what they set up here. 238 00:15:56,413 --> 00:15:59,945 You might double down on that when you do finally meet with them, right? 239 00:15:59,945 --> 00:16:07,319 And the net effect of that is when they do meet client for the first time, they're not start, it's not a cold start with like, what's your name? 240 00:16:07,319 --> 00:16:07,620 Right? 241 00:16:07,620 --> 00:16:10,071 No, they're hitting the starting line at a hundred miles an hour. 242 00:16:10,071 --> 00:16:10,691 Right. 243 00:16:10,691 --> 00:16:20,957 The, and, in our experience, the feedback that we've gotten is the fidelity of the initial conversation is just so much richer than, than otherwise than it otherwise would have been 244 00:16:20,957 --> 00:16:22,914 that, that they're achieving just like 245 00:16:22,914 --> 00:16:29,537 velocity and cruise and like cruising speed way earlier in the engagement with this client. 246 00:16:29,537 --> 00:16:38,961 And so, you know, the system doesn't, systems don't exist to measure that kind of like thing yet, but we can, it's, tangible. 247 00:16:38,961 --> 00:16:49,216 And if we could measure it in, in vibes and feedback and enthusiasm, like that we've received back for that kind of thing. 248 00:16:49,358 --> 00:16:53,855 uh It's blowing, you know, it's blowing away expectations exceeding exceedingly. 249 00:16:53,855 --> 00:16:57,010 So yeah, so so yeah, that's that's the upside 250 00:16:57,010 --> 00:16:58,174 Vibe intake. 251 00:16:58,174 --> 00:17:00,005 That's, that's what you're doing is right. 252 00:17:00,005 --> 00:17:00,135 it. 253 00:17:00,135 --> 00:17:00,446 Yeah. 254 00:17:00,446 --> 00:17:01,476 Yeah. 255 00:17:03,126 --> 00:17:03,857 hilarious. 256 00:17:03,857 --> 00:17:06,622 um I've seen like vibe lawyering. 257 00:17:06,622 --> 00:17:07,844 um 258 00:17:09,516 --> 00:17:11,196 You know, obviously vibe coding. 259 00:17:11,196 --> 00:17:15,956 That's, that's the new, um, that's the new hot word is, is vibe. 260 00:17:15,956 --> 00:17:29,276 What, what about, so this, this required R and D and you know, that's one of the, I've really been beating this drum with legal clients is to think about, you know, R and D is a 261 00:17:29,276 --> 00:17:31,116 foreign concept of law firms. 262 00:17:31,176 --> 00:17:36,616 Um, on average, they spend 1 % of operating costs on R and D. 263 00:17:36,616 --> 00:17:39,402 The average, the average company. 264 00:17:39,402 --> 00:17:39,622 Right. 265 00:17:39,622 --> 00:17:43,943 This includes, you know, across the across the industries is 4%. 266 00:17:43,943 --> 00:17:46,766 So they spend one for, and that's due to a number of different things. 267 00:17:46,766 --> 00:17:55,781 I think one of the big drivers is the fact that law firms use cash basis accounting, which is actually a small business accounting approach. 268 00:17:55,801 --> 00:18:04,506 IRS has rules where if you're over more than, if you're more than 25 million in revenue, you have to use accrual based accounting and then R and D makes sense. 269 00:18:04,506 --> 00:18:04,816 Right. 270 00:18:04,816 --> 00:18:07,948 You have a mechanism to amortize expense over 271 00:18:08,062 --> 00:18:13,717 over multiple years, but it's completely foreign to law firms and they're going to have to shift that. 272 00:18:13,717 --> 00:18:23,225 I'm not saying they're going to have to, you know, switch to accrual accounting, but they're going to have to shift their mindset to a place where instead of thinking about 273 00:18:23,225 --> 00:18:24,976 ROI, I need ROI. 274 00:18:24,976 --> 00:18:36,936 You know, I hear that from a lot of law firm leaders when they talk about AI investment and it's like, you know, your return on investment, your return sometimes is learning. 275 00:18:37,040 --> 00:18:44,064 or it's the accumulation of intellectual property that allows you to enable capabilities like the ones you guys built. 276 00:18:44,064 --> 00:18:57,431 How did your firm wrap their head around conceptualizing R and D and ultimately getting partners, some of which are, you know, two years from retirement and they're not going to 277 00:18:57,431 --> 00:19:01,633 see the break even on this until maybe further down the road. 278 00:19:01,633 --> 00:19:05,935 How did, how did you build support and change the mindset around that? 279 00:19:06,023 --> 00:19:09,045 Well, it starts with the right leadership. 280 00:19:09,045 --> 00:19:15,051 Our C-suite is pretty forward thinking and I'd say tech interested, if not enthusiastic. 281 00:19:15,051 --> 00:19:17,773 Also, that is a trust exercise as well. 282 00:19:17,773 --> 00:19:25,899 We had to start small and generate small wins such that the firm had the confidence that like dollars they invested into our program were well spent. 283 00:19:26,701 --> 00:19:29,262 And so that's where it started. 284 00:19:29,503 --> 00:19:31,555 But I take your point. 285 00:19:31,555 --> 00:19:33,058 I like what you're saying about like, 286 00:19:33,058 --> 00:19:37,110 This actually R &D is sort of antithetical to the existing model, right? 287 00:19:37,110 --> 00:19:43,106 Like it doesn't really, doesn't really make sense to try to disrupt something that's going so well. 288 00:19:43,286 --> 00:19:55,176 you know, this last generation of technology has really introduced, in my opinion, some existential, you know, threats, if not important conversations that need to be had about 289 00:19:55,176 --> 00:19:55,996 this. 290 00:19:56,738 --> 00:20:01,701 And I think it's because like historically, if you look at like the arc of technology innovation, 291 00:20:02,808 --> 00:20:06,561 The innovations and the disruption rarely come from within any company. 292 00:20:06,561 --> 00:20:19,392 It's more so that the incumbents, the uh existing big players, usually they don't enjoy it so much as they get T-boned by at the intersection of innovation, technology, and market 293 00:20:19,392 --> 00:20:20,432 forces. 294 00:20:21,193 --> 00:20:27,488 So if we take streaming, for example, like... 295 00:20:28,258 --> 00:20:32,959 You know, Blockbuster was never going to invest in a Netflix disruptor, right? 296 00:20:32,959 --> 00:20:36,820 Because their, their existing business was doing just fine, right? 297 00:20:36,820 --> 00:20:40,021 They weren't nobody, there was no interest in like messing with a great thing. 298 00:20:40,021 --> 00:20:47,013 ah CNN was never going to invent YouTube any more than cable was going to invent like streaming, right? 299 00:20:47,013 --> 00:20:58,264 Like, ah and so, uh so to do our leaders think that will be the case for this new and burgeoning technology, law firms are not inherently gauged. 300 00:20:58,264 --> 00:20:59,465 for this kind of activity. 301 00:20:59,465 --> 00:21:02,846 You have to make a conscious effort and really push on it. 302 00:21:02,846 --> 00:21:04,757 And it's not a mayfly project either. 303 00:21:04,757 --> 00:21:11,120 Like this is an initiative and if anything, a huge culture shift has to take place here. 304 00:21:11,120 --> 00:21:20,874 Now to answer your question about how we do that, the answer is uh by starting small and with the leadership in the firm and showing them like, this is what we're doing, this is 305 00:21:20,874 --> 00:21:22,104 how it's useful. 306 00:21:22,104 --> 00:21:26,356 We're not gonna push this into your practice group without your say so like. 307 00:21:26,442 --> 00:21:27,372 All of that stuff, right? 308 00:21:27,372 --> 00:21:36,688 We need everybody to go in eyes wide open about, you know, um the upside to this, but also like the risks that you adopt inherently when you bring something like this into your 309 00:21:36,688 --> 00:21:37,288 practice, right? 310 00:21:37,288 --> 00:21:41,701 And so that's how, that was how GWT was able to make it happen. 311 00:21:41,701 --> 00:21:45,913 And to date, over 50 % of the firm uses the app every day now. 312 00:21:45,913 --> 00:21:48,264 um And that's a lot of people, right? 313 00:21:48,264 --> 00:21:51,606 But that didn't happen overnight, to your point, right? 314 00:21:51,606 --> 00:21:53,037 That was a slow burn. 315 00:21:53,037 --> 00:21:55,078 But yeah, so that's how we did it. 316 00:21:55,134 --> 00:21:55,634 Interesting. 317 00:21:55,634 --> 00:21:55,874 Yeah. 318 00:21:55,874 --> 00:22:00,526 I had a LinkedIn post recently where I mapped out. 319 00:22:00,526 --> 00:22:14,300 you know, my, my position is that AI, it is an extinction level event for the traditional law firm model and product market fit for the traditional model is crumbling beneath our 320 00:22:14,300 --> 00:22:15,130 feet. 321 00:22:15,310 --> 00:22:22,392 And we've got headwinds in the legal industry that are holding us back from 322 00:22:23,350 --> 00:22:35,923 being the Netflix of the world and you know, the, the, the reasons, the, sources of those headwinds I mapped out consensus driven, driven decision-making slows rates of change, 323 00:22:35,923 --> 00:22:37,084 lateral mobility. 324 00:22:37,084 --> 00:22:44,816 So the fact that law firm part, even partners can take their book of business and move down the street also creates challenges. 325 00:22:44,816 --> 00:22:51,408 Why am going to write checks and invest in a, in a capital project when I might be down the street in three years? 326 00:22:51,408 --> 00:22:52,672 Um, 327 00:22:52,672 --> 00:22:56,154 Healthy profit margins make the status quo sticky. 328 00:22:56,154 --> 00:22:59,365 Cash basis accounting and retirement horizons, which we talked about. 329 00:22:59,365 --> 00:23:01,876 Law schools aren't keeping pace. 330 00:23:01,876 --> 00:23:04,577 Only around half even offer AI courses. 331 00:23:04,577 --> 00:23:06,938 Half, which blows my mind. 332 00:23:07,218 --> 00:23:08,999 That number should be in the 90s. 333 00:23:08,999 --> 00:23:16,783 um Empowering non-lawyer managers, the business professionals, that's a tough sell. 334 00:23:16,783 --> 00:23:18,844 um It doesn't always happen. 335 00:23:18,844 --> 00:23:20,224 Risk aversion. 336 00:23:20,460 --> 00:23:26,040 Lawyers are naturally risk avoidant and R &D requires risk. 337 00:23:26,040 --> 00:23:30,980 And then finally, and I think this is a big one, it's lack of diversity within law firm leadership. 338 00:23:30,980 --> 00:23:36,100 If you look at law firm leadership, it's a bunch of old white dudes primarily, right? 339 00:23:36,100 --> 00:23:50,480 I looked at something like 50 % of, I found this stat somewhere on the internet, 50 % of executive committee membership is male, 55 and older. 340 00:23:50,666 --> 00:23:51,016 Right. 341 00:23:51,016 --> 00:23:59,853 The people who really understand this technology best, and this is, there's data on this from McKinsey, it's millennials, right? 342 00:23:59,853 --> 00:24:07,049 They need to have a seat at the leadership table, not just your director of innovation, who's four levels down from the XCOM. 343 00:24:07,049 --> 00:24:16,336 They need to have a seat at the table where conversations are had about capital deployment and it's not happening for the most part today. 344 00:24:16,336 --> 00:24:17,176 So. 345 00:24:17,302 --> 00:24:17,914 I don't know, man. 346 00:24:17,914 --> 00:24:23,531 I feels like the firms that manage these headwinds most effectively are going to be the long, longterm winners. 347 00:24:23,531 --> 00:24:24,521 You agree? 348 00:24:25,544 --> 00:24:27,055 yeah, it's coming. 349 00:24:27,055 --> 00:24:36,259 problem, part of the problem Ted is that, you know, for all of the progress that's been made, this tech has only really been mainstream for the last two years. 350 00:24:36,259 --> 00:24:40,500 Before that, you didn't want to be the guy in the room who's like, no, believe me, computers will talk to you one day. 351 00:24:40,500 --> 00:24:42,621 You know, like it was, it was still a weird thing, right? 352 00:24:42,621 --> 00:24:44,902 um But, but you're right. 353 00:24:44,902 --> 00:24:53,226 Those of us that are in it can, can see clearly what, what is happening, especially given the history of technology and the way it disrupts industries. 354 00:24:53,226 --> 00:24:54,336 It, it, takes. 355 00:24:54,336 --> 00:25:00,529 It gives, but it takes, I love the points in your blog post, by the way. 356 00:25:00,529 --> 00:25:02,809 I want to back up to like models changing. 357 00:25:02,930 --> 00:25:11,813 Part of the problem with like us saying that models change or like business models need to change is the data doesn't support it yet, but we can clearly see it right. 358 00:25:11,813 --> 00:25:13,384 Because the industry is growing. 359 00:25:13,384 --> 00:25:21,437 So legal service spend is, is, is growing as, uh, as our clients are, as they start to adopt this new technology. 360 00:25:21,437 --> 00:25:24,358 You know, that said, there's, um 361 00:25:24,524 --> 00:25:28,016 Something is happening with the tech that I think is going to catch everybody by surprise. 362 00:25:28,016 --> 00:25:35,630 Where it is most suited today is with like large high volume matters that are pretty consistent in the way these things are handled. 363 00:25:35,630 --> 00:25:36,440 Right. 364 00:25:36,440 --> 00:25:41,963 Now the technology is doing great to improve the quality and streamline those services. 365 00:25:41,963 --> 00:25:53,059 It's increasing in efficacy, but ah the barriers to entry and adoption are also decreasing such that you don't actually need an expert lawyer to string together some of these 366 00:25:53,059 --> 00:25:54,698 systems and 367 00:25:54,698 --> 00:26:02,521 And all you really need is a really motivated like BA, business analyst, with some guidance from a supercharged paralegal or an associate partner. 368 00:26:02,521 --> 00:26:05,963 And they can get really effective with this stuff really fast. 369 00:26:05,963 --> 00:26:13,586 And whether that happens at a law firm or in-house, you know, there's no, there's no like moat saying like that knowledge has to be locked up anywhere. 370 00:26:13,586 --> 00:26:15,006 So that's going to be a thing. 371 00:26:15,006 --> 00:26:16,077 Make of that what you will. 372 00:26:16,077 --> 00:26:24,242 But like that is going to be a thing all law firms will have to navigate is the increasing efficacy and power of the technology. 373 00:26:24,242 --> 00:26:25,933 as it operates in-house, right? 374 00:26:25,933 --> 00:26:31,988 That's gonna be a I also love what you said about uh lateral movement. 375 00:26:31,988 --> 00:26:41,576 um Who would have thought 10 years ago that one of the first questions any lateral asks when they're hiring a new firm is like, well, what's your technology stack like, right? 376 00:26:41,576 --> 00:26:42,577 Like that's a new thing. 377 00:26:42,577 --> 00:26:43,697 Who's your CIO? 378 00:26:43,697 --> 00:26:48,301 know, like that's a, does your firm managing partner stand on like technology adoption, right? 379 00:26:48,301 --> 00:26:49,710 And it doesn't stop there. 380 00:26:49,710 --> 00:26:55,010 you can see a future in which like M &A, these are tough questions that are getting asked upfront, right? 381 00:26:55,250 --> 00:27:05,730 Like when you are looking to bring in 80 attorneys and their tech stack and stuff, so the question will ask, like, do you guys have any, or they will ask the question, where are 382 00:27:05,730 --> 00:27:06,310 you with AI? 383 00:27:06,310 --> 00:27:07,650 Do you have AI systems? 384 00:27:07,650 --> 00:27:08,770 Who are your AI vendors? 385 00:27:08,770 --> 00:27:09,170 Right? 386 00:27:09,170 --> 00:27:16,630 Like it bears mentioning that that will be a first-class citizen concern in all M &A and not just for law firms, but all industries going forward. 387 00:27:16,630 --> 00:27:17,070 Right. 388 00:27:17,070 --> 00:27:18,990 But I think the thing that you said, 389 00:27:19,554 --> 00:27:27,749 you know, about the incoming generation is, it's pointed and it, it, and it is front and center for me lately. 390 00:27:27,749 --> 00:27:35,444 It's on my mind because I had the good fortune of going to a Stanford CodeX hackathon uh a few weeks ago. 391 00:27:35,544 --> 00:27:44,972 CodeX is a, is a program at Stanford University that strategy that it sits between the computer science program and the uh law in the law school, right? 392 00:27:44,972 --> 00:27:50,605 And it's sort of right now it's, acting as a conduit between the two to introduce both to each other with AI. 393 00:27:50,686 --> 00:27:51,947 And it's exceptional. 394 00:27:51,947 --> 00:27:56,370 If you, if you get a chance, your listeners might be interested in learning more about it. 395 00:27:56,370 --> 00:27:58,001 Look at Megan Ma at Stanford. 396 00:27:58,001 --> 00:27:59,662 She's, she's spectacular leader. 397 00:27:59,662 --> 00:28:05,475 She's built this program up to be so good, but we got to go down to their hackathon. 398 00:28:05,496 --> 00:28:08,358 Um, and Ted, I'm getting goosebumps as I even think about it. 399 00:28:08,358 --> 00:28:15,072 You would not believe the things that I saw in the, in the 12 hour hackathon, as we got to mentor and coach these, these kids. 400 00:28:15,124 --> 00:28:23,738 I'm going to give you, if it's okay, I'd love to give you just two examples of the apps that I saw built, but the big thing is about the way these kids did it, which I think is 401 00:28:23,738 --> 00:28:26,198 going to be most interesting to law firms. 402 00:28:26,779 --> 00:28:36,113 In 12 hours with the power of AI, random teams that were assigned, kids that had never met before, sometimes they had a coder, sometimes they didn't, churned out, they had 12 hours 403 00:28:36,113 --> 00:28:37,623 to churn out an AI powered app. 404 00:28:37,623 --> 00:28:38,924 And some of these things were amazing. 405 00:28:38,924 --> 00:28:42,145 The first one was called Claim Hero. 406 00:28:42,145 --> 00:28:43,726 What Claim Hero does is, 407 00:28:44,416 --> 00:28:49,087 It uses AI to help regular people like you and me appeal denied medical claims. 408 00:28:49,127 --> 00:28:49,848 Like it's amazing. 409 00:28:49,848 --> 00:28:50,838 And it was really good. 410 00:28:50,838 --> 00:28:52,658 Like it wasn't like, this is a prototype. 411 00:28:52,658 --> 00:28:53,268 We call it together. 412 00:28:53,268 --> 00:28:53,789 Here's mockups. 413 00:28:53,789 --> 00:28:56,109 No, like it was a full blown prototype. 414 00:28:56,109 --> 00:29:00,040 um These kids were using AI assisted development tools. 415 00:29:00,040 --> 00:29:05,582 were practically talking to a computer and it was building the app that they, that they were inspired to build. 416 00:29:05,582 --> 00:29:06,372 Right. 417 00:29:06,492 --> 00:29:08,053 Excuse me. 418 00:29:08,053 --> 00:29:12,034 The next one, the one that won was called GovMatch. 419 00:29:12,034 --> 00:29:13,294 And what this app does, 420 00:29:13,294 --> 00:29:15,694 This is a team of MBAs and an engineer. 421 00:29:15,694 --> 00:29:25,574 They realize that when you're a small business and you're working on gigs like government contracts or whatever, it's really hard to service a contract and find the new one at the 422 00:29:25,574 --> 00:29:26,074 same time. 423 00:29:26,074 --> 00:29:31,534 What you end up with is like this lurching business model where you're working a gig and you finish it now you've got to find the next gig. 424 00:29:31,534 --> 00:29:32,494 You're not making money. 425 00:29:32,494 --> 00:29:38,194 Then you find it and you start making money again and then you finish that gig and you stop making money while you find the next one. 426 00:29:38,194 --> 00:29:42,342 Well, what they did was they built an agent that 427 00:29:42,390 --> 00:29:51,316 It's just always looking for the next gig and pitching you and filling out the RFPs and submitting your thing and then plugging it in to where it made sense on your calendar. 428 00:29:51,317 --> 00:29:52,468 Ted, and was really good. 429 00:29:52,468 --> 00:29:55,100 Like this wasn't like jakey stuff that kids were putting together. 430 00:29:55,100 --> 00:30:02,465 Like, and so my takeaway there is great software is table stakes now with AI, with AI enabled development teams. 431 00:30:02,465 --> 00:30:06,148 Anybody can build anything and, in record time. 432 00:30:06,148 --> 00:30:07,429 Now, was it production ready? 433 00:30:07,429 --> 00:30:08,490 Of course not. 434 00:30:08,490 --> 00:30:09,206 It was. 435 00:30:09,206 --> 00:30:11,107 It was a product, but it wasn't a company yet. 436 00:30:11,107 --> 00:30:12,968 There's a lot more that goes into it. 437 00:30:13,009 --> 00:30:19,153 but my, My point is like, this tech is enabling people to create as quickly as they can think. 438 00:30:19,153 --> 00:30:19,874 And that's amazing. 439 00:30:19,874 --> 00:30:27,139 But, but how does this relate to law firms in the in coming generation of people to have, we're not ready for it. 440 00:30:27,139 --> 00:30:30,701 No one, no one in our generation is when I, when I was watching. 441 00:30:30,701 --> 00:30:35,744 there was an auditorium and a lot of tables with like engineering teams and kids sitting around doing their thing. 442 00:30:35,885 --> 00:30:38,086 But what I saw is 443 00:30:38,356 --> 00:30:40,628 A, these kids are amazing collaborators. 444 00:30:40,628 --> 00:30:43,450 They grew up in an era of co-authoring. 445 00:30:43,450 --> 00:30:46,872 None of them have used word solo mode like us. 446 00:30:46,872 --> 00:30:52,396 Their entire being has just been co-authoring everything, right? 447 00:30:52,396 --> 00:30:56,638 They've a totally connected world, multiplayer only, right? 448 00:30:56,638 --> 00:31:07,186 That's just, they just collaborate so well with groups of strangers coming together and just being able to mix and match ideas and thoughts and put pen to paper or fingers to 449 00:31:07,186 --> 00:31:07,906 keys or... 450 00:31:07,906 --> 00:31:11,677 voice to AI or whatever the mechanism is, they can do it well at scale. 451 00:31:11,677 --> 00:31:17,349 But the other thing that was interesting is I would watch a team release a really cool feature, right? 452 00:31:17,349 --> 00:31:21,290 And they'd post it to Insta or whatever the social media platform of choices. 453 00:31:21,290 --> 00:31:25,731 And I would watch all the phones light up across the auditorium. 454 00:31:25,731 --> 00:31:28,592 And it was like a beehive kicking into gear. 455 00:31:28,592 --> 00:31:29,532 did you see what they've got? 456 00:31:29,532 --> 00:31:30,732 We've got to add that to ourself. 457 00:31:30,732 --> 00:31:34,463 And table by table, as the idea spread, the whole thing came alive. 458 00:31:34,463 --> 00:31:38,154 And so the rate of information distribution 459 00:31:38,228 --> 00:31:47,905 and assimilation is so much faster than a corporate memo to us would ever matriculate across like a large population of people. 460 00:31:47,905 --> 00:31:53,729 It was a hive mind like operating at a higher level than like we've ever experienced. 461 00:31:53,729 --> 00:32:02,635 And I don't know what that means, but I sense that's profound and that's gonna mean some different things for the industry as these creative like minds come into play. 462 00:32:02,635 --> 00:32:03,256 right? 463 00:32:03,256 --> 00:32:06,870 There's no way, there's no way any hiring recruiter 464 00:32:06,870 --> 00:32:13,456 is gonna make any sense at all to these kids in an interview when they start asking questions about like, what is team collaboration like? 465 00:32:13,456 --> 00:32:15,338 And we're like, well, we schedule meetings. 466 00:32:15,338 --> 00:32:16,338 You know what I mean? 467 00:32:16,338 --> 00:32:19,521 And we circulate a link to a document, right? 468 00:32:19,521 --> 00:32:22,784 And that is gonna look just slow. 469 00:32:22,784 --> 00:32:23,885 That's just gonna look slow to them. 470 00:32:23,885 --> 00:32:27,548 Yeah, so who knows what that means, but it means something. 471 00:32:27,548 --> 00:32:29,830 And we're gonna be here to see it firsthand. 472 00:32:29,830 --> 00:32:32,723 Yeah, that was a soapbox, but you get what I mean, right? 473 00:32:32,723 --> 00:32:33,204 Like. 474 00:32:33,204 --> 00:32:34,134 good stuff, man. 475 00:32:34,134 --> 00:32:35,915 And that's a really good point. 476 00:32:35,915 --> 00:32:37,016 I had another post. 477 00:32:37,016 --> 00:32:43,080 I'm plugging my LinkedIn post here, but I think it's super relevant to what you just talked about. 478 00:32:43,080 --> 00:32:43,720 So Dr. 479 00:32:43,720 --> 00:32:49,754 Larry Richard uh wrote a book called Lawyer Brain and he has conducted like 35 years of research. 480 00:32:49,754 --> 00:32:57,068 He surveyed over 30,000 attorneys and he has a list of traits in which 481 00:32:57,068 --> 00:33:01,788 attorneys score either much higher or much lower than the general population. 482 00:33:02,208 --> 00:33:07,788 So high in skepticism, high in autonomy, high in urgency, high in abstract reasoning. 483 00:33:07,788 --> 00:33:18,168 Few of these are assets to innovation, urgency, abstract reasoning, low sociability, low resilience, low empathy. 484 00:33:18,168 --> 00:33:22,588 Those are inhibitors to innovation. 485 00:33:23,048 --> 00:33:27,168 I heard a podcast with 486 00:33:27,424 --> 00:33:34,606 Um, Andrew Huberman and Mark Andreessen and Mark Andreessen mapped out the five traits of an innovator. 487 00:33:34,606 --> 00:33:37,087 And who knows more about innovation than Mark Andreessen. 488 00:33:37,087 --> 00:33:46,149 mean, that dude invented the web browser literally, and then has spent the last 30 plus years as a VC in Silicon Valley. 489 00:33:46,149 --> 00:33:54,212 He knows he writes checks based on his assessment of a founder's ability to exhibit these traits. 490 00:33:54,212 --> 00:33:56,214 Those traits are open to many new. 491 00:33:56,214 --> 00:34:00,517 kinds of ideas, not lawyers, um, high level of conscientiousness. 492 00:34:00,517 --> 00:34:03,389 That's lawyers, high and disagreeableness. 493 00:34:03,389 --> 00:34:06,111 That's definitely lawyers, high IQ. 494 00:34:06,111 --> 00:34:07,632 They're definitely smart people. 495 00:34:07,632 --> 00:34:09,553 Um, high in resilience. 496 00:34:09,553 --> 00:34:10,994 That's not lawyers. 497 00:34:11,034 --> 00:34:21,401 So we've got a gap and it's, it's not, I'm not saying like lawyers can't be innovative, but if you look at the bell curve, the ones that are tend to be outliers, they're, they're 498 00:34:21,401 --> 00:34:23,413 really past focus. 499 00:34:23,413 --> 00:34:25,804 Like practicing the law requires 500 00:34:25,898 --> 00:34:28,509 the concept of precedent, right? 501 00:34:28,509 --> 00:34:33,730 And it's a backward looking uh practice or discipline. 502 00:34:33,730 --> 00:34:36,731 Risk orientation, lawyers are risk averse. 503 00:34:36,731 --> 00:34:43,053 uh Outlook, innovators are very optimistic, lawyers are uh skeptic. 504 00:34:43,053 --> 00:34:49,214 uh Comfort with ambiguity, innovators extremely high, lawyers low. 505 00:34:50,075 --> 00:34:53,645 Resilience to setbacks, relationship to status quo. 506 00:34:53,645 --> 00:34:55,990 There's all these different markers 507 00:34:55,990 --> 00:35:00,522 So it's not that, hey, blow up your innovation committee and put a bunch of millennials on there. 508 00:35:00,522 --> 00:35:01,745 I'm not saying that at all. 509 00:35:01,745 --> 00:35:09,191 But what I'm saying is the lawyer perspective is necessary, but not sufficient um for innovation in law firms. 510 00:35:09,191 --> 00:35:10,572 And they need to augment. 511 00:35:10,572 --> 00:35:20,230 They need to bring in business professionals, younger ones who really grasp this technology, those digital natives that have that beehive mindset and bring a different 512 00:35:20,230 --> 00:35:22,582 dimension to the conversation. 513 00:35:22,582 --> 00:35:24,984 Because if we just have innovation, 514 00:35:25,216 --> 00:35:31,741 council or committee of only lawyers, it's not, it's probably we're missing opportunities. 515 00:35:31,741 --> 00:35:36,765 So I think there's real lessons to be learned in what you experienced. 516 00:35:36,765 --> 00:35:45,362 And I don't know how we communicate that like without seeing it firsthand like you did, but it's those, there are lessons there. 517 00:35:46,006 --> 00:35:46,956 Yeah, I agree. 518 00:35:46,956 --> 00:35:59,443 think, I think, um, gosh, I just, get so excited to think about it because if, if channeled correctly, um, it could be a superpower for any firm that has to evolve their, 519 00:35:59,443 --> 00:36:02,915 their platform and their offering faster and faster. 520 00:36:02,915 --> 00:36:11,400 Um, what you can't do, um, is assemble a board of people that sit around just thinking big thoughts and then like inventing things and then go into market and hoping there's a 521 00:36:11,400 --> 00:36:12,290 problem that it solves. 522 00:36:12,290 --> 00:36:12,921 Right. 523 00:36:12,921 --> 00:36:15,724 I think that, I think that the, um, 524 00:36:15,724 --> 00:36:24,948 The problems will be appearing so quickly that you're going to need, you're going to need a culture that can evolve and adapt on the fly and generate new product offerings and new 525 00:36:24,948 --> 00:36:35,742 ways of thinking about services faster and faster because the needs of our clients will be evolving in step with how quickly their core technology offerings are as well. 526 00:36:36,022 --> 00:36:44,962 You can imagine, you know, any large technology company, how different their needs are today than they were a year ago because they can move faster and, um, 527 00:36:44,962 --> 00:36:49,523 get into new territory and new lines of business faster than ever before, right? 528 00:36:49,523 --> 00:36:57,525 And so it might be that your law firm just doesn't have services available for like the new ground that they're covering, right? 529 00:36:57,525 --> 00:37:07,608 But it could, if you have a team of people that can assemble these things and think differently about the offerings or even the new business models that they grew up with. 530 00:37:07,608 --> 00:37:14,156 Like for example, kids today, even saying kids today, I realized like, 531 00:37:14,156 --> 00:37:18,800 where I'm at in my career is, well, I remember being that kid with crazy ideas and no one would listen to it, right? 532 00:37:18,800 --> 00:37:20,351 It's like, no, you don't understand. 533 00:37:20,351 --> 00:37:21,292 I see it every day. 534 00:37:21,292 --> 00:37:26,837 You guys have been locked up in this big building, like heads down doing great work, but things are changing out there and it's coming, right? 535 00:37:26,837 --> 00:37:33,242 um They've grown up in a world with completely different billing models where everything is just a monthly service charge, right? 536 00:37:33,242 --> 00:37:35,464 For all you can eat or at some kind of thing, right? 537 00:37:35,464 --> 00:37:42,956 And so, so maybe like they bring in the ability to see ways of bundling legal services where 538 00:37:42,956 --> 00:37:52,573 Maybe the AFAs are commoditized and done cheaply, but at a higher rate for litigation services and mixing and matching these things to best meet the situation that clients are 539 00:37:52,573 --> 00:37:54,654 now uh navigating, right? 540 00:37:54,654 --> 00:37:58,457 Like, uh I think we're going to need that kind of thing. 541 00:37:58,457 --> 00:38:00,558 And it's not going to happen by default. 542 00:38:00,558 --> 00:38:11,425 I do think this is going to be a conscious decision that leaders make to create environments where that kind of culture can thrive and good ideas can come out of. 543 00:38:11,425 --> 00:38:12,398 uh 544 00:38:12,398 --> 00:38:15,938 Because if you don't, it's someone else will. 545 00:38:15,938 --> 00:38:22,238 Maybe it won't be a law firm, but it will happen to the incumbents one way or another. 546 00:38:22,378 --> 00:38:32,078 I just want to point out, we've had the last, well, for the last 30 years, like it's been the same 30 tech companies that sort of ruled the roost, right? 547 00:38:32,078 --> 00:38:35,578 But they were not the big tech companies 30 years ago. 548 00:38:35,578 --> 00:38:39,734 There was a time when today's companies were small startups. 549 00:38:39,734 --> 00:38:42,535 looking out a way to disrupt existing industries. 550 00:38:42,535 --> 00:38:51,339 Ted, 30 years ago, who were the incumbents, the gigantic companies that nobody thought could ever tumble, right? 551 00:38:51,339 --> 00:38:54,511 The major phone companies, big networking companies, right? 552 00:38:54,511 --> 00:38:58,542 Big faceless, the IBMs, everything, right? 553 00:38:58,542 --> 00:39:02,604 And who would have thought that they could ever be disrupted? 554 00:39:02,604 --> 00:39:03,515 And they didn't. 555 00:39:03,515 --> 00:39:07,146 The internet came along and they didn't disrupt themselves, right? 556 00:39:07,148 --> 00:39:17,661 They used it as a tool to enhance their service offerings, but it wasn't until this generation of natives that the certain like the Googles, the Yahu's that those early 557 00:39:17,661 --> 00:39:23,423 adopters, like the Amazons got out there to Facebook's and MySpaces use this technology. 558 00:39:23,963 --> 00:39:26,684 And they realized like those incumbents were not the ceiling, right? 559 00:39:26,684 --> 00:39:29,925 That was actually the floor that they could build all these new cool services on. 560 00:39:29,925 --> 00:39:32,918 And wouldn't you know it disrupt them at the same time, right? 561 00:39:32,918 --> 00:39:45,067 missed opportunities left and right as this new technology and these new types of companies and ideas started to form that could solve problems for clients that the big 562 00:39:45,067 --> 00:39:50,711 guys were just too big to be nimble enough to maneuver around in ad service offerings for, right? 563 00:39:50,711 --> 00:39:54,863 That is the period that we are approaching with this new technology. 564 00:39:54,863 --> 00:40:01,698 Like the incumbents are the ceiling, but that's not where this technology is just going to smash right through it and you're going to see. 565 00:40:01,716 --> 00:40:03,988 new types of like things being built. 566 00:40:03,988 --> 00:40:14,825 If I had to guess, if I had to forecast like what happens over the next period of time, like with this tech, I legitimately believe the top 10 firms of the 2030s are being 567 00:40:14,825 --> 00:40:19,819 determined right now because these things are happening at hackathons and in garages. 568 00:40:19,819 --> 00:40:23,601 ALSP's are popping up that are AI first, right? 569 00:40:23,601 --> 00:40:29,005 And maybe it's not as good as like a large law firm, but their technology is good enough and it's way cheaper. 570 00:40:29,005 --> 00:40:30,996 So like maybe that's enough to get by. 571 00:40:31,178 --> 00:40:45,110 And so, um you know, if you play, if you just sort of look a little bit into the future, you can see where, um you know, people do some really interesting stuff and invent new 572 00:40:45,110 --> 00:40:46,231 markets with it, right? 573 00:40:46,231 --> 00:40:48,653 Or new ways to interact with customers. 574 00:40:48,653 --> 00:40:50,934 Like it's all within reach now. 575 00:40:51,115 --> 00:40:56,419 And the crazy thing is just like in the 90s, look at what they did with super slow internet. 576 00:40:56,419 --> 00:40:57,340 You know what I mean? 577 00:40:57,340 --> 00:40:59,301 Two kilobits per second? 578 00:40:59,402 --> 00:41:00,332 I mean, 579 00:41:00,438 --> 00:41:08,899 And that's where we are with this tech, like our language models in 10 years that we have today are going to look downright primitive because this technology is only getting 580 00:41:08,899 --> 00:41:09,201 faster. 581 00:41:09,201 --> 00:41:13,362 There's nothing to indicate it's going to slow down in efficacy or ability. 582 00:41:13,362 --> 00:41:14,082 Right. 583 00:41:14,082 --> 00:41:21,634 And so ah I think the real question is who's, who's nimble enough, which of the three firms will you be in the future? 584 00:41:21,634 --> 00:41:24,105 Will you be, will you be a new one? 585 00:41:24,125 --> 00:41:27,316 Will you be one that's merging with a new one? 586 00:41:27,534 --> 00:41:35,634 Or will you be a boutique or purpose-built technology firm that offers some kind of digital service, right? 587 00:41:35,634 --> 00:41:39,954 Because it's going to be the floor is raising for what will be acceptable. 588 00:41:39,954 --> 00:41:43,593 And I think that's what we're looking at over the next 10, 15 years. 589 00:41:43,593 --> 00:41:46,342 The next chapter of law looks just like that. 590 00:41:47,018 --> 00:42:04,197 Yeah, and if you are in that &A scenario where you're merging and you're not the technical leader, you're not adept, your multiple on your business is going to be miserable, right? 591 00:42:04,197 --> 00:42:09,860 You're going to be getting sold at a fire sale price because really, what do you have? 592 00:42:09,860 --> 00:42:11,160 You have people. 593 00:42:11,280 --> 00:42:15,082 And um it's not that people are going away. 594 00:42:15,082 --> 00:42:16,908 I actually, you know, there's a lot of 595 00:42:16,908 --> 00:42:20,568 Chicken Little out there in the marketplace like, the sky's falling. 596 00:42:20,568 --> 00:42:21,768 I don't think that at all. 597 00:42:21,768 --> 00:42:23,608 I think the sky's falling. 598 00:42:23,868 --> 00:42:28,288 If you don't take action, I think there are opportunities. 599 00:42:28,288 --> 00:42:31,928 There's going to be a reshuffling of the deck in the AMLAW. 600 00:42:31,928 --> 00:42:35,088 And I've used this comparison many times. 601 00:42:35,088 --> 00:42:42,508 If you look at the big four, which they're also a partnership model and they have their own issues, but the combined revenue of the big four is 220 billion. 602 00:42:42,508 --> 00:42:47,074 The combined revenue of the AMLAW 100 is like 140 billion. 603 00:42:47,074 --> 00:42:47,205 Mm. 604 00:42:47,205 --> 00:42:47,904 Mm-hmm. 605 00:42:47,904 --> 00:42:57,387 It's extremely fragmented and there's going to be consolidation as we move into this tech enabled legal services era. 606 00:42:57,407 --> 00:42:57,737 Right. 607 00:42:57,737 --> 00:43:01,428 Because it's not, it's no longer bespoke law. 608 00:43:01,428 --> 00:43:08,069 Legal work is, is moving from, you know, bespoke nature to the assembly line. 609 00:43:08,070 --> 00:43:10,110 And there's still going to be bespoke work. 610 00:43:10,110 --> 00:43:17,164 There there's always going to be, there are special unique needs associated, but man, there is a lot, um, that 611 00:43:17,164 --> 00:43:20,744 can absolutely make its way to the production line. 612 00:43:20,744 --> 00:43:32,664 And if you're just a production line worker, if you're a craftsman, what sort of value are you going to bring to the firm that's acquiring you that has this tech-enabled legal 613 00:43:32,664 --> 00:43:34,104 machine that they invested in? 614 00:43:34,104 --> 00:43:36,196 Probably not a lot of value there. 615 00:43:37,270 --> 00:43:40,632 Yeah, I think, man, I'm on board. 616 00:43:40,632 --> 00:43:41,983 think it hollows out the middle. 617 00:43:41,983 --> 00:43:43,434 Like technology has a habit. 618 00:43:43,434 --> 00:43:47,097 Like when it explodes into an industry, it has a habit of like bifurcating industries. 619 00:43:47,097 --> 00:43:50,939 And what you end up with is a couple winners at the very top. 620 00:43:50,939 --> 00:43:54,742 And then everybody else just fighting for like boutique status just to get noticed, right? 621 00:43:54,742 --> 00:43:56,763 What is your thing that makes you different? 622 00:43:56,923 --> 00:44:05,689 I mean, if we look at, look at the internet today, I mean, Netflix is streaming, Facebook is social, LinkedIn is professional. 623 00:44:05,689 --> 00:44:07,054 ah 624 00:44:07,054 --> 00:44:08,574 Amazon is shopping, right? 625 00:44:08,574 --> 00:44:11,094 There are like 20 websites, tops that actually matter. 626 00:44:11,094 --> 00:44:11,654 You know what I mean? 627 00:44:11,654 --> 00:44:14,814 In terms of like the economy and scale and things like that. 628 00:44:14,814 --> 00:44:20,614 And so if we, you know, if we, if we play that out, like in the industry, you're right. 629 00:44:20,614 --> 00:44:24,534 The real question is like, how do you, how do you get big and achieve scale? 630 00:44:24,554 --> 00:44:26,694 Like how can you leverage a first movers advantage? 631 00:44:26,694 --> 00:44:28,494 Cause that's what they all have in common. 632 00:44:28,494 --> 00:44:35,314 The big ones that, that we have today, those top 30 firms that we, we talked about earlier, they got in there fast. 633 00:44:35,314 --> 00:44:35,798 They, 634 00:44:35,798 --> 00:44:37,209 It wasn't enough to just be first. 635 00:44:37,209 --> 00:44:38,229 That's like the saving grace. 636 00:44:38,229 --> 00:44:39,720 Like you can be first and still get it wrong. 637 00:44:39,720 --> 00:44:41,960 There are a lot of first mice out there, right? 638 00:44:42,561 --> 00:44:44,822 My space is a great example, right? 639 00:44:45,162 --> 00:44:54,045 But whoever shows up in that early pack, maybe second, can demonstrate good enough uh efficiency with the technology, right? 640 00:44:54,426 --> 00:44:57,607 Build a dedicated workforce that understands their customers. 641 00:44:57,607 --> 00:45:04,620 But third, create that moat that sort of, that helps you achieve scale that's almost impossible to penetrate. 642 00:45:04,620 --> 00:45:15,836 Facebook's like button, Amazon's affiliate program, um There are these things that incumbents can do to sort of solidify like the next quarter century of like business for 643 00:45:15,836 --> 00:45:16,296 themselves. 644 00:45:16,296 --> 00:45:25,421 And in my opinion, I think the situation will be the same for any industry that the technology sort of crashes through the wall into. 645 00:45:26,342 --> 00:45:33,736 So that's, you know, I think, but to that point, to your point earlier about R &D and like how does this all tie together. 646 00:45:34,200 --> 00:45:38,093 Well, you don't want to be as a law firm as a forced buyer of technology. 647 00:45:38,093 --> 00:45:41,755 What you don't want to do is wake up and realize the market has caught up to you and it's time to change. 648 00:45:41,755 --> 00:45:45,438 Blockbuster realized that all too late, right? 649 00:45:45,438 --> 00:45:52,823 What you can't start doing, this is a tough sell in any partnership, is at the same time the revenues are going down because you're being chipped away, someone's going to show up 650 00:45:52,823 --> 00:45:58,066 and say, we should invest in R &D at the same time and start eating away at the bottom line from another angle. 651 00:45:58,146 --> 00:46:00,938 That's a bad situation. 652 00:46:00,938 --> 00:46:04,320 That looks more like desperation than innovation. 653 00:46:04,550 --> 00:46:08,512 And so you've got to hedge your bets and you've got to be ready for it. 654 00:46:08,512 --> 00:46:17,856 If not actively doing it, then planning for like, what is the maneuver that your firm um will pull off to stay at the cutting edge and ahead of the pack, right? 655 00:46:17,856 --> 00:46:20,977 um So yeah, yeah. 656 00:46:21,097 --> 00:46:22,104 What do you think? 657 00:46:22,104 --> 00:46:25,246 and we see, I already see early signs. 658 00:46:25,246 --> 00:46:26,766 It is very early. 659 00:46:26,766 --> 00:46:36,850 it's by no way can you pick out winners and losers here, but you're starting to see some early indicators. 660 00:46:36,850 --> 00:46:44,494 um Firms who I talked to a good friend of mine who's a director at innovation about a 400 attorney law firm. 661 00:46:44,494 --> 00:46:48,555 And I asked her what the strategy is with AI. 662 00:46:48,595 --> 00:46:50,156 And she said, well, we're piloting 663 00:46:50,156 --> 00:46:52,018 20 co-pilot licenses. 664 00:46:52,018 --> 00:46:53,759 And I was like, what else? 665 00:46:53,759 --> 00:46:56,301 We'll call her Sarah for this. 666 00:46:56,301 --> 00:46:57,622 What else are you doing, Sarah? 667 00:46:57,622 --> 00:47:04,356 Well, it's a conservative board and they really want to focus on ROI. 668 00:47:04,488 --> 00:47:09,932 And I'm looking at that picture and then I'm looking at what you guys are doing, what Cleary is doing. 669 00:47:09,932 --> 00:47:15,237 There's early signs with like, you look at Cooley and the team that they're assembling at Cooley. 670 00:47:15,237 --> 00:47:18,407 um I'm seeing, again, these are early signs. 671 00:47:18,407 --> 00:47:19,614 It doesn't mean that 672 00:47:19,614 --> 00:47:29,269 everybody who is making these early moves is going to be the ultimate winners, but you're already starting to see this parting of the seas. 673 00:47:29,670 --> 00:47:42,056 man, unless there's some pretty um dramatic course correction, you know, once, once momentum is heads you in a direction, it's really hard, just like you said, to pivot 674 00:47:42,056 --> 00:47:48,800 because again, while times are good, you need to be investing while you have, you know, the 675 00:47:48,800 --> 00:47:59,570 the margin to do it because once things start heading south, it's, you know, the scarcity kicks in and then it's a, it's a race to the exits. 676 00:47:59,570 --> 00:48:04,114 So, um, it's been really cool to see what, you guys are doing there. 677 00:48:04,114 --> 00:48:10,180 I've actually known your firm for a long time, a lot and Penn who she was probably there before. 678 00:48:10,180 --> 00:48:11,240 you know her? 679 00:48:11,374 --> 00:48:13,734 Yeah, I caught the tail end of her stay at DWT. 680 00:48:13,734 --> 00:48:14,574 She was wonderful. 681 00:48:14,574 --> 00:48:16,114 Yeah, yeah, I loved long. 682 00:48:16,274 --> 00:48:16,663 Yeah. 683 00:48:16,663 --> 00:48:27,331 I met her 10 years ago at a lean Six Sigma black belt conference, uh, not black belt, but it was a, it was a Six Sigma event in legal that arc put on. 684 00:48:27,412 --> 00:48:29,894 Um, so yeah, like that was another early sign. 685 00:48:29,894 --> 00:48:35,838 Like honestly, based on the fact of their presence at that event, I would have said, you know what? 686 00:48:35,838 --> 00:48:42,538 These guys are thinking ahead because there's not a lot of, I'm a lean Six Sigma black belt and I, 687 00:48:42,538 --> 00:48:46,173 I pay attention when I see firms adopting methodologies like that. 688 00:48:46,173 --> 00:48:47,264 You don't see it a lot. 689 00:48:47,264 --> 00:48:49,437 It does exist, but it's pretty rare. 690 00:48:49,437 --> 00:48:51,559 Again, outliers, long tail. 691 00:48:51,559 --> 00:48:54,513 um So it's cool to see what you guys are doing. 692 00:48:54,513 --> 00:48:58,598 I know we're running out of time here, but um man, this has been a fun conversation. 693 00:48:58,990 --> 00:49:00,172 Yeah, thanks for having me, Ted. 694 00:49:00,172 --> 00:49:01,374 I really appreciate it. 695 00:49:01,374 --> 00:49:09,168 And I think the work you're doing in the community to, you know, elevate the consciousness, you know, about all of the stuff and where it's all headed. 696 00:49:09,168 --> 00:49:10,630 So yeah, thanks for having me. 697 00:49:10,686 --> 00:49:11,296 Absolutely. 698 00:49:11,296 --> 00:49:15,389 Well, you know, our livelihood is tied exclusively to law firms. 699 00:49:15,389 --> 00:49:18,941 Like we have a hundred percent law firm clients. 700 00:49:18,941 --> 00:49:23,753 like, really want a lot of people, I've gotten feedback before like, man, you're really negative on the industry. 701 00:49:23,753 --> 00:49:24,934 Like, no, I'm not negative at all. 702 00:49:24,934 --> 00:49:26,065 I love this industry. 703 00:49:26,065 --> 00:49:28,026 I've been here almost 20 years. 704 00:49:28,026 --> 00:49:28,926 I love it. 705 00:49:28,926 --> 00:49:30,167 I want to stay in it. 706 00:49:30,167 --> 00:49:34,609 I just, I'm trying to raise the flat, the red flag, like guys, we got to start thinking differently. 707 00:49:34,609 --> 00:49:39,812 So it's good to see, uh, it's good to see firms like DWT. 708 00:49:40,278 --> 00:49:41,760 do it and then get recognized. 709 00:49:41,760 --> 00:49:44,241 So congratulations on the award. 710 00:49:44,241 --> 00:49:45,103 That's a big one, man. 711 00:49:45,103 --> 00:49:51,259 We've had two clients win that award for intranets that we've built for them and we had a front row seat to the process. 712 00:49:51,259 --> 00:49:52,711 It is highly competitive. 713 00:49:52,711 --> 00:49:56,284 So kudos for winning that recognition. 714 00:49:56,600 --> 00:49:57,140 Well, thanks. 715 00:49:57,140 --> 00:49:57,461 Yeah. 716 00:49:57,461 --> 00:50:07,848 And I, I, I appreciate it, but like I tell everybody, I'm just a paint job on, on, on a team that for a team that's doing great work, the engine that, drives this innovation, our 717 00:50:07,848 --> 00:50:10,800 leaders are our engineers, our attorneys. 718 00:50:10,800 --> 00:50:21,937 Um, one thing, if I could, uh, since we're talking about DWT, one of the cool things about the crescendo engine is that, um, it wasn't built in a bubble for the first time in DWT 719 00:50:21,937 --> 00:50:24,649 history, maybe the legal industry, this internal innovation. 720 00:50:24,649 --> 00:50:26,434 Um, they, 721 00:50:26,434 --> 00:50:29,915 They put this up for the entire firm to test before we went live with it. 722 00:50:29,915 --> 00:50:43,279 had over 75 attorneys, councils, paralegals, professional staff show up and commit hours to testing this thing because it had, it's a zero fault, zero tolerance like environment. 723 00:50:43,279 --> 00:50:47,700 Like we can't even risk a single mistake, the system making a single mistake. 724 00:50:47,760 --> 00:50:55,382 And so the firm got behind this, not to put too fine a point on it, but that's a demonstration of culture I have never seen anywhere. 725 00:50:55,382 --> 00:50:55,682 Right? 726 00:50:55,682 --> 00:50:58,326 Like a commitment to innovation and excellence. 727 00:50:58,326 --> 00:51:07,037 And so to that, know, I much gratitude to the firm to make sure that this thing was as bulletproof as possible before we put it into production. 728 00:51:07,037 --> 00:51:14,062 And so just one of the reasons I love working here, because like I said, the leadership is, a huge part of making all of this happen. 729 00:51:14,062 --> 00:51:14,784 Yep. 730 00:51:14,784 --> 00:51:21,767 I think it was Jack Welsh that used to talk to former CEO of GE's talk about the tone at the top, right? 731 00:51:21,767 --> 00:51:24,158 The tone at the top dictates the culture, man. 732 00:51:24,158 --> 00:51:27,129 You got to have that leadership buy-in. 733 00:51:27,809 --> 00:51:37,848 and, another, uh, metaphor is, you know, culture eats strategy for breakfast, right? 734 00:51:37,848 --> 00:51:41,615 It doesn't matter how good your strategy is, if your culture doesn't support it. 735 00:51:41,615 --> 00:51:44,626 So it's good to hear that you guys are doing it right. 736 00:51:44,854 --> 00:51:45,505 Well, cool, man. 737 00:51:45,505 --> 00:51:46,908 It was great talking to you. 738 00:51:46,908 --> 00:51:48,590 Good conversation as always. 739 00:51:48,590 --> 00:51:55,110 um Look forward to seeing you at a conference and finding other ways to collaborate to get the word out. 740 00:51:55,374 --> 00:51:56,094 Yeah, me too. 741 00:51:56,094 --> 00:51:56,698 Thanks a Ted. 742 00:51:56,698 --> 00:51:57,300 Thanks for having me. 743 00:51:57,300 --> 00:51:59,406 Good to see you. 744 00:51:59,406 --> 00:52:00,108 Bye. -->