Going AI-Native: How Law Firms Can Reshape the Delivery of Legal Services

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Hello, I'm Kaj Rozga and welcome to Version Up One Lawyer's Journey to Digitally Transform his legal practice.
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Scott, welcome to Version Up.
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Hey, thanks for having me.
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Appreciate it.
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Yeah, really happy to have you on and would love to kick it off by just hearing a little bit about your background and how you got into Legal Tech.
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Yeah.
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Yeah, it's kind of a, a very circuitous path, uh, to get here.
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I, I've been in tech for go way too long.
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20, 25 plus years.
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Cut my teeth at Amazon, turn of the century.
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Um, I have the dubious honor of being on their, um, Y 2K team, which is like a super awesome humble brag.
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Um, which was a giant nothing burger, of course.
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And, uh, but from there, you know, I got really active in open source.
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Hosted a bunch of, uh, pro built some projects myself and then hosted this thing called the Open source lab where we hosted like the Lennox Kernel Drupal, a whole bunch of different projects.
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Anyways.
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From there, sort of moved over to the business side of things.
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Went from doing the tech stuff to doing the business side and had been building, scaling and selling company for, for the rest of that time.
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Uh, did a company that, you know, did push notifications for the iPhone when that came out, when Steve Ballmer was calling it, cute and no one would do anything serious with it.
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Did a vacation rental platform that we launched in March of 2020.
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Not awesome.
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You, you win some, you lose some as as it were.
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And, uh, launched a site that where we built, uh, a full blown e-commerce engine and then we're selling bacon on the internet, like actual bacon cured pork.
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That was a long, long time ago.
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And, uh.
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Anyway, so long story short, I got, I got married 15, you know, plus years ago.
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Met my wife 15 plus years ago, and uh, uh, she's an attorney.
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She runs an insurance defense practice here in Oregon.
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She's got Oregon, Washington, Idaho 65 associates, paralegals and attorneys.
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Um, and so when I went to go start this, uh, case mark about.
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Two plus years ago she jokingly but not jokingly said to me why don't you build something that helps me for once? And so she's not only a phenomenal attorney, she's also a very I think like a lot of attorneys, a critic of software because software just doesn't do what she wants it to do.
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And so candidly, it was hard.
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To build solutions.
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And so that was sort of the impetus for this.
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And it's, it's been a kind of a crazy wild ride.
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And, and you know, we've been navigating the same challenges that I think a lot of people have around what does it mean to really embrace ai and are you really, really embracing it? Have you really leaned in, have you sort of red pilled as it were? And so that I think has been a biggest challenge for us.
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And then once you do kind of flip that bit the amount of.
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What you can build and how you can sort of leverage what's called compound engineering.
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In other words, you build a foundation that allows you to build more things on top of it that allow you to build more things gets really, really exciting.
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So, that's kind of the, the background in a nutshell, although it was kind of a large nutshell.
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Anyways, yeah.
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Amazing.
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I, I've got my deposition hat on now.
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So now I'm thinking, which of these leads do I wanna follow because bacon marriage, open source, um, I'm gonna spin the wheel and pick Y two KI have to ask you, were helping Amazon, uh, prepare their infrastructure for Y 2K? You Yeah, so I, I, at the time I was a junior, like, it'd be called a.
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DevOps engineer.
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I was a system administrator back then and I was on what's called this tiger team, and what we would do is I would go around to all the distribution centers in the us.
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At the time there were only five distribution centers, and the thinking at the time, which is completely pivoted, um, was that we'd have these massive centrally located based on distribution hubs.
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In other words, you know, close to Kentucky, Georgia, you know, places where like FedEx and UPS and things work.
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And so we built these huge, huge data centers.
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Well, the Y 2K stuff was like a massive concern.
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And that was part of what fueled the whole Y 2K and sort of.bomb.com
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bubble burst because everybody invested so much money up until Y 2K, and then when it hit, it was like, oh, it turns out it didn't really matter.
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And of course we were in, I was based in Seattle, right downtown Seattle.
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So we started seeing the Y 2K hit in Japan.
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We could see it going and we had infrastructure there, so we knew like nothing was gonna happen.
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And so by the time, two, three in the morning rolls around we're still had to stay there and make sure everything's still going and doing its thing.
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But it was a giant nothing burger.
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And we had literally everybody.
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And there was no party.
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There was no like, no, nobody was like, we were all like literally at our keyboards waiting for something to happen that never came.
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And so it was, you know, it is what it's.
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Giant nothing.
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Burger.
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Well, one, one reaction and one question reaction is every 10 years you should have like an alumni gathering.
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I would love to, to imagine where all those people went, you know, and to kind of relive that story.
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But the question is I'm just curious what happened to all that capacity? All these people who have been focusing on this issue one day, wake up, the next morning it's gone.
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What happens to those people? Did they transition into roles inside their existing or enterprises? Was there like some other issue that came up that had to be tackled because of the Y 2K infrastructure build out, or, because I imagine there's a lot of people then been like, ramped up to do something and then bam it's over.
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For sure.
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For sure.
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And and what we saw was in March of 2001, the bottom fell outta the market because.
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There was so much investment that had gone in and the investors were like, well, it's time to pay the piper.
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We need to see a return on this.
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If you can't it sort of kicks off a cycle of panic and all these things.
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And what's interesting is if you actually look, if you track the curve, this is really typical with pretty much every technological.
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Developments, uh, you can go back to the steam engine, the, telegraph, the telephone, the television, the radio, massive investment leads to over it leads to speculation.
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There's a bubble and then it crashes out.
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But then when you map from the creation of the technology to the time of full blown adoption, the curve goes like this.
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So there's this bubble, and ultimately the market is significantly bigger.
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So if you go back to.
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2000 when they had all the crazy Super Bowl commercials, pets.com,
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and all these web van, you know, grocery delivery to your house, that sounded like foreign to people.
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And today it's commonplace, right? And, and also if you think about the valuations for these companies back at the turn of the century compared to what we're seeing now.
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Even inflation adjusted.
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There's they're bons.
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Even the, the craziness we talked about in 2000 wasn't nearly as crazy as it really was.
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Now when I think when we're gonna look back.
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Let's say 30 years from now, I don't think we're gonna talk about the.com
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bubble, we're not gonna talk about the iPhone, we're not gonna talk about web two or any of that.
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I think what we're gonna talk about is ai.
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We're gonna go, oh, that's when AI hit that, that changed everything.
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Uh, and I, I don't think, you hear a lot of, of hyperbole on LinkedIn.
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People talking about how, oh my gosh, this is gonna disrupt so much.
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It actually is gonna disrupt a lot.
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My big concern is, is, what's next with every major technological disruption.
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Again, the telegraph, the, steam engine, the car, the, you know, tv, all this.
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They spawned a whole set of industries that supported that.
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So when the car came along, yes, the horse and buggy went out.
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However you created the windshield and the tire and the road industries, um, that came from that.
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So.
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I, in this case, it's just, we're just kind of displacing a whole bunch of white collar workers.
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Potentially.
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Now there will be secondary effects that do create larger markets that it has yet to be determined yet.
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So it is still crazy.
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And, and you know, for me it's, it's, I'm, I'm a fan of disruption.
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I'm also a fan of, of.
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I'm not a, a big fan and, you know, contrary or this is a opinion, but I'm not a big fan of, of legal in general.
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Just having to hear my wife when she walks in, you know, and still walk into a deposition and they'll be like, oh, good, the court reporter's here.
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She's like, well, actually no, I'm, I'm the attorney.
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And just the constant, berating and this whole idea that, well, I'm a partner now.
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I get to talk as much, you know, SHIT as I want to down at my.
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Associates.
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'cause that's what I, you know, it's, it's a hazing game and all these things.
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So to me it's, it's actually an industry that, that's kind of ripe for disruption.
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And, and so that actually, it creates a huge opportunity for people who don't want to have to make that seven year March partner.
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I share some of your sentiment in terms of the industry being ripe for disruption.
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And you've touched on some issues like change culture the business model itself, I.
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I, I hear you there.
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And that's sort of, yeah, one of the main things I want to explore on this podcast is yeah, trying to understand that impact.
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I'll agree.
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By the way, if I hear the pets.com
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story one more time, I'm gonna barf.
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So if we can stop doing the pets.com
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internet bubble story that I agree that we can let that one go.
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Yeah, totally.
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Um, but I think it's interesting to think about boom and bust and to think about the way you put it.
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It's almost like.
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Maybe the bubble bursting was a bit of like the noise, right? The signal was the longer trend.
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And so it does beg the question of, okay, right now we're in some sort of upward trajectory.
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At some point there'll probably be a dip.
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But let's think about what the signal is.
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What's the signal of the trend? And so if we get to get on that you mentioned your wife's what law firm, and I think that's actually a great entry point to a, a topic I wanted to explore with you, which is, when I think about ai, native law law firms, and then I think about the incumbent existing traditional law firms, ai, native law firms are sort of this idea of a hybrid model.
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It's a new entity that's formed from scratch, right? The incumbents have been along for a long time.
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To me, one of the questions is, which of the incumbents.
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Position to kind of convert into an eight i of native not model.
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And there's probably some sweet spot where you're not too small, not too big, where you're able to be nimble and maybe switch over from being sort of a traditional law firm to being something that is more built on top of like a tech stack.
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Just would love to hear your thoughts on that Because it's one thing to talk about startups, right? A lot more difficult to tackle the question of how does an existing traditional law firm switch from one to the other? Or transition.
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Yeah.
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Do you have any thoughts on that? I, I have a few on it and it's, um, it's interesting, you know, so my wife's in insurance defense, which, you know, arguably is, is not very sexy.
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Right.
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And it's interesting, even here in, in Oregon and Washington, there's been this, this giant transition for so many of these insurance defense firms, major senior partners going off and starting their own plaintiff's firms.
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And the reason they're doing that is the plaintiff judgments are just better.
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There's just, it's a more lucrative kind of deal.
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And with AI, it gets a lot easier to do that.
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In other words, I can feed in all this data and I can crank out a demand letter and fire it off.
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And not only that.
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I can fire off a demand letter that's tailored to the insurance company.
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In other words, we know this is a trip and fall for a major retailer, and it's Allstate's, the, the carrier.
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Ah, we know well if we keep it under this amount, Allstate will just write a check.
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And so, so that's, that's crazy.
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Now the flip side for my wife, of course, is.
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For the insurance defense firms that have stuck it out, they actually are realizing they can raise their rates now because the game is getting much harder.
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And, and more importantly on the plaintiff's side, because they can create so many demand letters, now they have to respond, right? So they have to leverage these tools to respond because they're not gonna add headcount.
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So I, I think that's a big one.
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And then when you think about these big incumbents, I think there's, I think there's a couple different things that are gonna happen.
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You know, you have firms like even up Finch is another really interesting one, a couple other, and what they're doing is they're building infrastructure for basically pre-litigation.
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So the idea is that you could engage this firm at a discount over your headcount to deliver, back office paralegal, you know, even some associate work.
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Then you do that at a discount for the firm.
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So the idea is these large firms are coming and hiring folks like Finch or even ups, armed to do these things.
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And they literally can calve off that spend, increase their margins.
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You know, maybe they lower their hourly rate a little bit just to sort of placate clients to say, Hey look, we're AI and we're doing these things.
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Then the really, really smart firms, I think, anyways, are taking that savings and plowing it back into sort of their marketing channel.
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That's the key, right? How do I continue to be the marquee firm for whatever this, this segment is and leverage these economies of scale from these infrastructure providers and these infrastructure providers are a mix of AI and legal teams.
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Doing these things again, starting sort of legal first.
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Those to me are, are really, really interesting.
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And it's actually, those are the type of firms that, that we're leaning into.
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Because, you know, for what we do at Case Mark around delivering essentially infrastructure for these folks, in other words.
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I don't wanna have to build, you know, my own, solutions for these things.
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I wanna be able to leverage some infrastructure that solves these problems, that has the security and privacy infrastructure in place that just lets me sort of click a button and have magic happen.
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And so, that to me is a, is a, obviously a huge opportunity for us, but.
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But ultimately, this is where I think this is playing out.
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I think there will be some big firms, especially, you know, not, not to get political or anything, but there's been a lot of large firms that have placated the existing administration.
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Um, and I think that's gonna have some changes when this all shakes out in, four, eight years, whatever.
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So I think, aI to me is, you know, look, we've, we've had technological disruptions in legal for years, right? So the, the facts, the email, like those sound silly, but they didn't actually change the business model of, uh, legal itself.
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That's true.
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It's still That's true.
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Billable hour and, and honestly, if you think about it, law firms and, and.
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Legal as a whole has really fought tooth and nail against technology.
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And to me, AI is a forcing function.
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Not only does it force law firms to think about technology as a whole, I think it's gonna force them to think about their business models.
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Now the flip side of that, what's very, very exciting, especially when it comes to ai, is.
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You know, attorney's work is episodic in the sense that, you know, rules change, regulations change.
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You might need some specific tool for just one case.
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Um, you couldn't do that in the traditional SaaS sales model because the sales cycles are long.
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You're locked into software.
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You get these sort of zombie pieces of software.
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But if I could just come up with an idea and have some software magically appear out of thin air, and that solves a problem for one case.
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Great.
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And then guess what? You can throw it away.
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It doesn't matter.
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You, there isn't some developer behind the scenes that's going, no, no, this is my life's work.
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You know, it's like, no, no, no.
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This is, this is literally a piece of infrastructure that we spun up and we spun down.
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And so thinking about that and the impact on what that means for legal, to me is really, really interesting.
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And I think you know, we, we see a lot of this.
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I I'm totally going off task now, but anyways, um, I wanna make sure we stay focused on the, the big law and what's, how are these folks gonna adopt these things? And it's going well.
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I I, do wanna get to case mark.
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I want to get to what you just talked about, which I think of as sort of almost like disposable solutions.
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But before we do that, you did an excellent way of sort of thinking about how a law firm's gonna approach it and how a, a legal tech vendor will then address that, if we could flip that role for a minute and think about that insurance company, the end client who actually has a legal question or a legal need, right? They're proceeding a million of these demand letters and they need to figure out how to respond to 'em.
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There's one of two ways they could do that, right? They can keep working with the law firm.
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And count on the law firm to just keep up.
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Right? And then the law firm has the pressure to, uh, use technology, for example to do that.
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The other option is the insurance company could, uh, come up with this or deploy or build a solution internally to tackle this in some way.
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Yeah.
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Do you think about how the person asking the legal question is thinking about that sort of decision? Or are you thinking more about, look there's gonna be a lot of work coming from the law firm, and so let's focus on what the law firm needs.
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I.
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It is.
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Yeah, I mean, uh, obviously I have uh, not only do I have, you know, my wife's take on what she's seeing, but I also have what I see in the industry and the insurance carriers, as you can imagine, are slow to move.
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They leverage their panels.
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In other words, they'll have in.
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Counsel, and if they can solve it quickly with in-house counsel or their, or their team, they will, otherwise they kick it to a panel firm, um, that is in the jurisdiction that matters.
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So, you know, my wife's on, I don't know, 10 or 12 different panels for all these different insurance carriers.
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And so they get tapped with their different pieces.
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Now what happens is they get a case file over and then they start running a, a, basically a bill against that, right? Well, guess what? They're just getting a bunch of raw data.
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It'd be far more interesting if the insurance company could take those demand letters plus any associated data and just do a quick AI pass on it, right? In other words, oh, there's a bunch of medical records in here.
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Let's analyze those.
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Let's put together a chronology.
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Why don't we put a case summary together too? You know, we could even shove this all.
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Let's get nerdy completely.
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Let's shove this all into a giant vector database and graph rag, and then send the link over to the law firm and let them start.
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Doing it from there.
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Now, the insurance company might have to pay a little bit more to do that initial analysis, but they'll save a fortune on what they send with the billables coming back.
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Yeah.
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Now, the challenge, of course, is the insurance companies are very risk averse.
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That's the business that they are in.
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So the adoption of AI for an insurance company is almost a non-starter right now because they're afraid of litigation.
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In other words, they are a great target to go after if somebody starts, you know, suing people for using AI for these things.
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And so the insurance companies that we've talked to, and we've talked to a bunch of these large insurance companies have just said, we're waiting until the end of 2026.
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To even think about this, um, which means, okay, great.
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Start a conversation.
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And even if I do, these things don't happen overnight.
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I have customers that I've talked with for 18 months that we finally closed.
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And it's, it's this, it's notc.
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I didn't sell 'em hard enough or, you know, it's just this sheer like organizational inertia you have to overcome.
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And so to me that that's.
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Part of this as well.
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And so the insurance companies are, are in an, in a, you know, a not a very envious position.
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Right.
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Uh, it's not ideal.
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However, I think it's where you could, you could see a significant amount of savings, you know, candidly, you know, we've been talking with some about how we can literally just take that data, shove it into our solution and produce.
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Basically a set of PDFs that explain the case with hyperlinking and all that, so people don't have to like use our solution.
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The law firm can literally just shove a, or the insurance company can just shove a bunch of PDFs with links in it.
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Somebody could print that out and put it in a binder and take a highlighter to it.
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Great.
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You know, they don't have to learn how to prompt or use Claude or chat GPT or worry about, you know.
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Training and data leakage and all that kind of stuff.
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So there are ways to do this stuff.
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It's maybe not the sexiest way to do it because it'd be great for everybody to just kind of prompt against stuff for, you know, talking to a microphone and have magic come back at you.
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But the, this crawl, walk, run of a, a technology adoption is always, always the way.
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And I think people underestimate that.
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I think it's part of why we're in a bit of a bubble right now.
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Do I think that AI and legal and the technology solutions around this, you know, over the long haul, that sort of graph we talked about, it's gonna be massive.
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However, we're in a speculative bubble right now and it's gonna burst and then what's gonna happen is there's gonna be companies like ours who come into pick up the pieces and who can go the long.
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The, you know, the long view on this and, uh, build interesting, compelling businesses that I think are gonna do really, really well.
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Right now you're seeing the Alta Vista and Yahoos of legal AI tech being built.
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And I'll say it, it's Harvey, it's Logra, it's sio, it's all these guys.
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They're building tech, one big tool to sell long-term deals into big firms.
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That, that whole thing's going away.
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Well that's, I mean, lemme pick up on that thread 'cause that's a great analogy because.
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Yahoo, by the way, is still around, right? And so what that makes me think of is, you talked about crawl, walk, run, and I, that's a great way to describe the pace of what we're gonna experience.
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But in an anecdote with the insurance company, you also, I think, addressed this.
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Question of what's the end state look like? And it's not gonna be binary.
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It's not gonna be all one thing or another.
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Yeah.
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It's not gonna be all law firms, no tech, not all legal tech and no law firms.
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There's gonna be different solutions for different needs.
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There's gonna be situations when a company bought builds something internally when they buy it, there'll be situations where they still use external counsel.
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There's gonna be a lot of different stuff out there in the market.
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There's gonna be variety, and it's not gonna be a binary situation where a law firm goes extinct.
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Yeah, no, I, I completely agree.
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And, and I think, you know, it's, it's really easy to get caught up in all these, crazy, you know, catchy headlines about, oh, I'll, I'll like, what was it the.
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Some senior person over at Microsoft said in 18 months, all uh, attorneys will work, can be done by ai.
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Okay.
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No, first of all, no.
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Second of all, the adoption curve on these things takes forever.
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And then, you know, if you think about Microsoft, well then who's gonna, who's gonna buy all those office licenses? I mean, I know that, that, that's sort of a secondary effect that nobody really cares about.
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But uh, you know, I, I think it's, it's.
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It's wildly pragmatic, it's overly op, optimistic.
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I do think it's gonna be a significant disruptive force.
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But, but to your point exactly, it's not gonna be all one thing or another and we just don't know how these technologies will shape things.
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Um, yeah.
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You know, that, that when the iPhone came along, we all had mobile phones in our pockets already.
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And.
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It wasn't until I saw that first iPhone and I touched it and I used it and I realized, oh, this is what mobile is supposed to be.
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And that's, to me was like, that was the, that was the light bulb moment to me.
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And that's when I said, okay, well we're gonna build a company that helps people, like brands connect with consumers directly into their pocket.
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Now we did it through push notifications.
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They were novel and fun that everybody hates 'em now, and sorry.
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But it was a transformative technology and.
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You know, this idea that you're, you were, gate kept by the carrier and the handset manufacturer, 'cause they wanted to take their piece of the action and that didn't need to happen.
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The same thing is gonna happen here, I think with AI and legal.
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This, when you saw AI and you, yeah, there fits and starts, and I think a lot of attorneys maybe tried it 18 months ago or a year ago, and they're like, oh, I don't have to worry about this at all.
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The sheer pace of, of adoption and technology and the speed.
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If you're not keeping up with it, if you're not digging in and learning how you can take edge of these things.
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Now, I'm not saying, you know, rethink your entire business today.
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Stay up to date with the tools, leverage some things, crawl your way into your first tool.
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Then you can see what, you know, walk and run are gonna look like.
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And you can do that in some, in some pretty, um, inexpensive ways that don't completely disrupt your firm.
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And so that's how I, I sort of, uh, I talk to folks about, uh, how they should approach it.
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It's one of the reasons why we've leaned into this whole attorneys that are vibe, coding, mantra.
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Do I think every attorney's gonna build their own tools? No, absolutely not.
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But I do think that.
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It's a signal to the noise that's out there that, that what we've seen is now you have people who understand the problem, who can just build the product.
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Where before it was I have this problem and in between me as engineers and product people and CEOs and people who have, quarterly results they have to hit.
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And that just means the solution never gets to be what you be.
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Let me bring it.
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Back to the iPhone actually, because to me yes, picking up the iPhone was great.
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It was a great device, but to me the, another huge moment was the app store, right? Like the notion that people could create, yeah.
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A random person could create an app and 99% of it was garbage, but 1% of it was really cool and innovative and that bubbled up to the top That's kind of what you're describing with vibe coding and empowering the actual legal users to come up with their own solutions.
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Same idea, like to me, the real power comes from.
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Not having a few big companies decide what I need in terms of functionality and features.
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It comes from empowering other users to bring those features to me because those other users are gonna come up with really good ideas.
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It's almost like a democratizing kind of way of development.
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What was, what was really interesting about.
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The App store.
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So when the iPhone first came along, people immediately jail broke the iPhone so they could start putting their own apps on there.
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And in true Steve Jobs fashion, he was reluctant at first, but then he said, oh my God, we can take 30% of whatever they do.
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Right? And he is like, oh man, I get it.
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Right.
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And I'll never forget, like this was a transformative technology in.
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Just think about this.
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I, so one of our first customers that came to us, this is back when it was just fart apps and, you know, you know, cheesy games and stuff and like, and you know, I, I got laughed out of partner meetings, uh, partner meetings saying, how many, you know, how big can this market really be? How many fart apps are there? And I'm like I mean, there's a bigger thing here.
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And what I heard from my customers, Starbucks came to us and they said, look, we have a team of seven people at a time.
322
00:25:25,469.1502702 --> 00:25:26,99.1502702
That was bonos.
323
00:25:26,99.1502702 --> 00:25:29,669.1502702
You only have, you had one person who used to do your website who is now in charge of mobile.
324
00:25:30,329.1502702 --> 00:25:33,869.1502702
And, uh, what they, what? They were actually quite visionary about it.
325
00:25:33,869.1502702 --> 00:25:41,879.1502702
They said, we believe that these smartphones, especially the iPhone and, and you know, what would come next are going to transfer.
326
00:25:42,519.1502702 --> 00:25:45,519.1502702
Transform, fundamentally transform our business.
327
00:25:45,699.1502702 --> 00:25:50,769.1502702
And they leaned into it, not just like, oh, cool, we can put our menu on in, on the app.
328
00:25:51,189.1502702 --> 00:25:54,999.1502702
They said, wow, this is gonna completely change our retail experience.
329
00:25:55,299.1502702 --> 00:25:56,979.1502702
We want to do order ahead.
330
00:25:57,9.1502702 --> 00:25:58,779.1502702
We want to do stored value.
331
00:25:58,839.1502702 --> 00:26:01,89.1502702
We want to be able to do tipping of our baristas.
332
00:26:01,389.1502702 --> 00:26:02,774.1502702
We wanna leverage the fact that.
333
00:26:03,54.1502702 --> 00:26:12,824.1502702
You know, you used to be able to walk into a Starbucks and they had the pick of the week, which was this little card that you would get you, you take it with you and you could scan it and put it into iTunes and get a track.
334
00:26:13,424.1502702 --> 00:26:19,214.1502702
They saw like a, a, I don't know, it was something like a three to 6%, um, conversion rate on those.
335
00:26:19,544.1502702 --> 00:26:27,974.1502702
Well, when they put pick of the week, in other words, they turned it into a marketing channel onto this device when they put the pick of the week so that you could just be in the, in the Starbucks app.
336
00:26:28,184.1502702 --> 00:26:29,744.1502702
Um, 'cause you're in the store anyways.
337
00:26:29,744.1502702 --> 00:26:31,4.1502702
You click the thing and you download it.
338
00:26:31,364.1502702 --> 00:26:37,394.1502702
That turned into a massive revenue generator for them because they were a channel for driving, you know, content.
339
00:26:37,394.1502702 --> 00:26:39,434.1502702
And people were willing to pay to get those eyeballs on there.
340
00:26:39,914.1502702 --> 00:26:54,794.1502702
And then you think about what Starbucks, they had to, they basically changed their stores around the iPhone, right? So to me that's a fundamental transformation that, you know, looking back 10, 15 years ago, you're like, well, that this is obvious.
341
00:26:54,794.1502702 --> 00:26:56,654.1502702
And it's like, well, not 15 years ago it wasn't.
342
00:26:57,164.1502702 --> 00:26:59,954.1502702
And so these are the kinds of things that I think are about to happen with legal.
343
00:26:59,954.1502702 --> 00:27:05,134.1502702
I'm not, I can't do the whole crystal ball thing and tell you what's gonna happen in legal, but, but those kinds of stories will be.
344
00:27:05,714.1502702 --> 00:27:07,574.1502702
Like all over the industry.
345
00:27:08,64.1502702 --> 00:27:15,604.1502702
And, and to me, these vi coders, these people who are like hacking on things right now, that's a signal, that's an indicator of what's to come to me.
346
00:27:16,504.1502702 --> 00:27:19,129.1502702
Well, it took about a half hour, but you know.
347
00:27:19,614.1502702 --> 00:27:22,764.1502702
We have someone on from Pacific Northwest, you know, we had to work Starbucks in.
348
00:27:22,764.1502702 --> 00:27:22,974.1502702
Right.
349
00:27:22,974.1502702 --> 00:27:25,284.1502702
I feel like that we did care.
350
00:27:25,284.1502702 --> 00:27:26,154.1502702
We made it half an hour.
351
00:27:26,154.1502702 --> 00:27:26,214.1502702
Yeah.
352
00:27:26,664.1502702 --> 00:27:28,914.1502702
But that was such a great, that was a great example.
353
00:27:28,964.1502702 --> 00:27:33,284.1502702
And changing the store around the iPhone makes me think of changing law firms around ai.
354
00:27:33,674.1502702 --> 00:27:40,4.1502702
And help me understand, you said Case Mark helps build the infrastructure for law firms to do that.
355
00:27:40,34.1502702 --> 00:27:48,299.1502702
How does it do that? What does it offer? Yeah, so it's, when we started our, our goal really was again, this whole crawl, walk, run.
356
00:27:48,299.1502702 --> 00:27:51,149.1502702
It's, it's basically part of our company culture.
357
00:27:51,489.1502702 --> 00:27:57,399.1502702
And we started thinking about how can we deliver work product that attorneys understand with the click of a button.
358
00:27:57,399.1502702 --> 00:28:01,69.1502702
In other words I, maybe, I don't want to deal with the learning prompting or.
359
00:28:01,679.1502702 --> 00:28:08,999.1502702
The things, I just wanna upload a de transcript and get a summary back right in A PDF that's clickable that I could print out, put it in a binder and take a highlight or two.
360
00:28:09,479.1502702 --> 00:28:12,89.1502702
That's a great way to sort of crawl your way into this space.
361
00:28:12,629.1502702 --> 00:28:26,9.1502702
And what we realized as we went through this is that most of the companies that we see in this space are really just features of what should be sort of a, a transformational shift in how we think about technology as it relates to law.
362
00:28:26,189.1502702 --> 00:28:28,169.1502702
Technology is gonna be disposable.
363
00:28:28,634.1502702 --> 00:28:29,924.1502702
But it's gonna be critical.
364
00:28:30,214.1502702 --> 00:28:36,244.1502702
And so if you can't answer the all the questions that you need to for a law firm you have to find a way to do it.
365
00:28:36,644.1502702 --> 00:28:48,154.1502702
Because these law firms don't wanna stitch together 10, 15, 20 different solutions to make it work, because they have to then go through 10 or 15 different security and privacy, you know, considerations and all these pieces.
366
00:28:48,154.1502702 --> 00:28:48,394.1502702
And so.
367
00:28:49,179.1502702 --> 00:28:52,809.1502702
Fundamentally, about six months ago, we realized, oh, we have to red pill this.
368
00:28:52,809.1502702 --> 00:28:55,489.1502702
We have to go all chips in on what it means to build ai.
369
00:28:55,489.1502702 --> 00:29:08,929.1502702
And so we'd solve some hard problems around OCRing old records and doing data storage and doing transcription analysis and summarization and translation, and just all these different pieces.
370
00:29:10,84.1502702 --> 00:29:18,504.1502702
We stitched all those together into something called case Dev, which is basically an infrastructure layer that allows companies to build solutions on top of it.
371
00:29:18,504.1502702 --> 00:29:19,434.1502702
One API key.
372
00:29:19,764.1502702 --> 00:29:24,244.1502702
We have relationships with all those folks such that we can, you know, do sensitive data.
373
00:29:24,819.1502702 --> 00:29:27,39.1502702
We have our HIPAA and our SOC two certifications.
374
00:29:27,39.1502702 --> 00:29:28,299.1502702
We have a whole variety of different things.
375
00:29:28,299.1502702 --> 00:29:33,639.1502702
We have people, basically third parties monitoring us continuously to make sure that we're doing what we say we're doing.
376
00:29:34,9.1502702 --> 00:29:40,329.1502702
And then most recently we launched something called Thurgood, which is basically a vibe coding front end to the case, do debt.
377
00:29:40,329.1502702 --> 00:29:44,799.1502702
So the idea is an attorney, Hey, I might be able to get to a 0.1,
378
00:29:45,369.1502702 --> 00:29:47,409.1502702
uh, implementation of something, but.
379
00:29:48,39.1502702 --> 00:29:49,929.1502702
Thurgood allows you to do is get to the 1.0,
380
00:29:49,929.1502702 --> 00:29:56,469.1502702
the fully baked, completely secure in a, in a, an environment that's safe, that's backed up, that's all those kinds of things.
381
00:29:56,749.1502702 --> 00:29:59,779.1502702
Continuously monitored, all, all those kinds of things.
382
00:30:00,374.1502702 --> 00:30:12,4.1502702
More than anything are people coming to us to, to vibe code solutions know what they're doing Is they're coming to us to help them do institute institutional or organizational transformation.
383
00:30:12,4.1502702 --> 00:30:19,264.1502702
In other words, how do we take these processes and use them internally so that we can start building tools, help us do that.
384
00:30:19,264.1502702 --> 00:30:25,204.1502702
And so our model is not just, Hey, here's a, here's a development solution, here's a platform, it's we're gonna land a human.
385
00:30:26,274.1502702 --> 00:30:35,394.1502702
In your firm, we're gonna bolt them on the side of your innovation team, and we're gonna help you adopt this concept of basically vibe coating and how we do this.
386
00:30:35,394.1502702 --> 00:30:48,199.1502702
Now, vibe coating, sounds like you're shooting from the hip and all this stuff, but really we have a whole bunch of sophisticated systems behind the scenes that are continuously monitoring every single line of code, every single decision that happens.
387
00:30:48,384.1502702 --> 00:30:51,204.1502702
And literally next week we're launching, um.
388
00:30:52,414.1502702 --> 00:31:07,744.1502702
It's called our agent, CLI, and it, and it's, it's very nerdy to talk about, but basically what it's gonna allow you to do is as an attorney, you're gonna be able to describe a natural language, what you want to have happen, and this is gonna go off and build it and deploy it in our infrastructure and be production ready.
389
00:31:07,744.1502702 --> 00:31:16,654.1502702
We can even land it inside of somebody's security perimeter because again, the software is disposable, but this expertise on how to maintain it and navigate the next.
390
00:31:16,924.1502702 --> 00:31:19,234.1502702
Decade of disruption is not.
391
00:31:19,294.1502702 --> 00:31:21,604.1502702
And I think that's what folks are coming to us for.
392
00:31:21,964.1502702 --> 00:31:23,764.1502702
And so that's what gets me really excited.
393
00:31:23,764.1502702 --> 00:31:32,229.1502702
It's, it's really astounding to watch some big firms, you know, I mean, we had somebody come to us, it's an am law 100 firm, and, and they just said, Hey, I.
394
00:31:33,69.1502702 --> 00:31:38,169.1502702
What, what would it take for us to partner with, um, taking this office action, this patent office action.
395
00:31:38,469.1502702 --> 00:31:50,849.1502702
And we want, we want to tear this file apart, find all the prior art that they mentioned, and then put together a packet that, that basically downloads all that prior art and all the different, you know, trademarks and then highlights the different sections and does it all.
396
00:31:51,419.1502702 --> 00:31:55,169.1502702
And they're like, what would it take for us to partner? And I literally had a response.
397
00:31:55,199.1502702 --> 00:31:57,299.1502702
Now I didn't have an email to him.
398
00:31:57,899.1502702 --> 00:32:01,49.1502702
I had an endpoint that he could click through that.
399
00:32:01,549.1502702 --> 00:32:04,309.1502702
He could upload an office action and it would solve the problem for him.
400
00:32:04,339.1502702 --> 00:32:08,689.1502702
And he's like, whoa, how, what? What? He's like, okay, well it doesn't do exactly what I want.
401
00:32:08,689.1502702 --> 00:32:09,529.1502702
I want this, and this.
402
00:32:09,709.1502702 --> 00:32:10,339.1502702
I was like, great.
403
00:32:10,459.1502702 --> 00:32:13,39.1502702
I'll tell the agent and like, we'll be off and running.
404
00:32:13,594.1502702 --> 00:32:18,24.1502702
It's the fact that you can do that in 20 minutes that is, is actually pretty hard.
405
00:32:18,24.1502702 --> 00:32:23,394.1502702
Now, the magic there, of course, is we've spent the last six months and we have a team of people who really understand this ai.
406
00:32:23,694.1502702 --> 00:32:28,44.1502702
So there's more than just, oh, okay, we, you know, this, everything takes 20 minutes.
407
00:32:28,74.1502702 --> 00:32:31,614.1502702
There is some hard stuff in here, obviously, but that to me is what's pretty exciting here.
408
00:32:31,614.1502702 --> 00:32:34,251.7474076
Anyways, you, you can tell I'm, I'm pretty fired up about this.
409
00:32:41,632.157437 --> 00:32:44,807.157437
Let me try to read it back in my kind of layman's terms and tell me if I'm getting it.
410
00:32:44,807.157437 --> 00:32:44,867.157437
Yeah.
411
00:32:45,527.157437 --> 00:32:48,827.157437
So let's say I'm a partner at a law firm.
412
00:32:49,467.157437 --> 00:32:52,917.157437
Case Mark is helping create sort of a secure.
413
00:32:53,562.157437 --> 00:33:02,132.157437
Operating system for me to develop applications, et cetera, internally, and really helping empower my organization to problem solve using these solutions myself.
414
00:33:02,132.157437 --> 00:33:04,232.157437
Is that the gist of it? That's right.
415
00:33:04,232.157437 --> 00:33:05,252.157437
That's absolutely right.
416
00:33:05,252.157437 --> 00:33:15,712.157437
And I think the, we obviously talk in acronyms and technological terms and everything, but at the end of the day, it's allowing law firms to, to basically control their own destiny when it comes to technology.
417
00:33:16,52.157437 --> 00:33:26,402.157437
For the last, however many, 30 plus years the law firms have just sort of said, well, who's the vendors that are gonna show up to solve us, solve these problems? And of course, the vendors come with problems.
418
00:33:26,667.157437 --> 00:33:30,747.157437
Or solutions that they probably don't have or completely don't have and they overpay for.
419
00:33:31,107.157437 --> 00:33:35,757.157437
And, you know, show me an attorney who's paying a, a bill for a piece of software that they didn't use that month.
420
00:33:35,757.157437 --> 00:33:38,67.157437
And I'll show you an attorney who's about to be one of our customers.
421
00:33:38,437.157437 --> 00:33:47,377.157437
This idea of, of being able to pay per use or pay per, you know, action, uh, or pay per outcome, that is actually really, really interesting.
422
00:33:47,627.157437 --> 00:33:54,617.157437
And the technology and the solutions are getting such that we can actually do that at scale, um, and do it, you know, with a pretty small team.
423
00:33:54,927.157437 --> 00:34:01,812.157437
You know, there's only 10 of us on this team right now and, and, um, I don't know how much bigger I need to get if I'm totally honest.
424
00:34:02,212.157437 --> 00:34:07,812.157437
I mean, obviously we're gonna need team, you know, folks to support, you know, all of our different, customers and things like that and over time.
425
00:34:07,812.157437 --> 00:34:17,822.157437
But you can do this in an AI native fashion in such a way that you can kind of 10 x folks which is, you know, again, part of our core mantra of what we do, uh, you know, here at Case Mark for sure.
426
00:34:18,842.157437 --> 00:34:20,912.157437
So let's stare.
427
00:34:21,692.157437 --> 00:34:26,492.157437
The beast right in the face, which is confidentiality, right? Security, privacy, yeah.
428
00:34:27,362.157437 --> 00:34:37,702.157437
Every law firm lawyers, the first thing they're gonna ask about, think about when it comes to allowing individuals in their organization to problem solve in this way, to develop their own tools.
429
00:34:38,422.157437 --> 00:35:04,372.157437
Can you help me understand? Where are we in the current state of art in guaranteeing that kind of secure, safe sandbox to build in versus the things that we're still looking to come down the pipeline, technologically speaking, to get us to the point where you should not think of this any different than you creating a word file on your work laptop using, enterprise 365 in terms of safety, security, all that.
430
00:35:05,137.157437 --> 00:35:12,67.157437
Yeah, so the problems around privacy and security are solved.
431
00:35:12,397.157437 --> 00:35:15,787.157437
In other words, you can solve those problems.
432
00:35:15,887.157437 --> 00:35:28,977.157437
The challenge is, and mark my words, the next 18 to 24 months one of the big players, it'll either be Google, uh, Microsoft, OpenAI, anthropic, you name it, probably all of them to some degree.
433
00:35:29,297.157437 --> 00:35:30,622.157437
We'll train with your legal data.
434
00:35:31,277.157437 --> 00:35:34,997.157437
If you upload it into chat, GPT, if you upload it into cloud, they will train with that data.
435
00:35:34,997.157437 --> 00:35:36,47.157437
I guarantee it.
436
00:35:36,467.157437 --> 00:35:39,377.157437
Mark my words and what's gonna happen.
437
00:35:39,377.157437 --> 00:35:42,377.157437
It's a $10 trillion opportunity that they're staring at.
438
00:35:42,407.157437 --> 00:35:43,547.157437
The math is simple.
439
00:35:43,817.157437 --> 00:35:51,477.157437
Okay, I can pay a 200, 500 million, 2 billion, $10 billion, fine.
440
00:35:51,957.157437 --> 00:35:52,377.157437
Great.
441
00:35:52,947.157437 --> 00:35:54,777.157437
This is a $10 trillion opportunity.
442
00:35:54,777.157437 --> 00:35:55,857.157437
We'll do that all day long.
443
00:35:56,187.157437 --> 00:35:59,157.157437
Now what happens is, is if they do train with that data.
444
00:36:00,237.157437 --> 00:36:03,377.157437
And I log into the next version of Claude, 17.5
445
00:36:03,377.157437 --> 00:36:10,607.157437
or whatever, and I say, oh, tell me the details of so-and-so's, uh, medical malpractice case and tell me about their deposition.
446
00:36:10,997.157437 --> 00:36:17,147.157437
It's gonna be able to recall parts of that in there, which means you had data leakage, which is just a massive, massive no-no.
447
00:36:17,387.157437 --> 00:36:19,397.157437
And guess who gets left holding the bag.
448
00:36:20,27.157437 --> 00:36:27,127.157437
It's the firm that used Claude or OpenAI or chat GT or whatever it is that uploaded that data that's gonna be left holding the bag here.
449
00:36:27,157.157437 --> 00:36:30,187.157437
I guarantee this is gonna happen and it's gonna happen at scale.
450
00:36:30,557.157437 --> 00:36:39,797.157437
And so, you know, and I, I say that a little bit to, to make sure that people, to get this into people's head, you can't trust these big companies that are, are funded like this.
451
00:36:39,797.157437 --> 00:36:42,947.157437
It just, the math, the equation for them is simple.
452
00:36:42,952.157437 --> 00:36:43,32.157437
It's.
453
00:36:43,312.157437 --> 00:36:45,712.157437
It's, you know, you're on the losing end of that equation.
454
00:36:46,82.157437 --> 00:36:57,362.157437
Now there are companies like ours and a whole host of these other sort of legal first AI companies that are taking security and privacy and, and those considerations first and foremost.
455
00:36:57,362.157437 --> 00:36:59,492.157437
In other words, we don't train with anyone's data.
456
00:36:59,492.157437 --> 00:37:05,882.157437
We will not, we have like serious teeth in our contracts and our agreements that say, you know, you can't do that.
457
00:37:06,132.157437 --> 00:37:17,112.157437
We also leverage the models in such a way that we basically take our customer data, drop it into a bucket with that model, we do the operations on it, and then we tear that whole thing down and it goes away.
458
00:37:17,512.157437 --> 00:37:20,902.157437
And so there's definitely, like I said, the problems are solved.
459
00:37:20,902.157437 --> 00:37:25,582.157437
It's the commercial side and the market opportunity that makes this fuzzy.
460
00:37:25,632.157437 --> 00:37:31,872.157437
Because any of these big players could solve this problem, you know, tomorrow, they just want, because the opportunity is too big.
461
00:37:33,7.157437 --> 00:37:35,407.157437
You know, we, we take it really, really seriously.
462
00:37:35,737.157437 --> 00:37:46,747.157437
We work with a whole host of different providers to deliver those models and this whole thing, you know, these models are continuously shaking up and changing and all these things, and so that's, that's another consideration for folks to think about.
463
00:37:47,77.157437 --> 00:37:51,727.157437
You're not choosing a vendor who has the right solution today for you.
464
00:37:52,27.157437 --> 00:37:54,697.157437
You're choosing a partner in this decade of disruption.
465
00:37:54,697.157437 --> 00:37:57,127.157437
Who's gonna help you navigate that? Starbucks came to us.
466
00:37:57,497.157437 --> 00:38:06,17.157437
Because they believe that we not only understood what was happening with the iPhone, but what was gonna be coming with the next and the next and the next, and the next version of the iPhone.
467
00:38:06,557.157437 --> 00:38:09,107.157437
And to me that's what you wanna find in a partner.
468
00:38:09,107.157437 --> 00:38:13,817.157437
And you know that they've crossed their T's and dotted their i's with respect to the security and privacy pieces.
469
00:38:14,207.157437 --> 00:38:25,277.157437
While those, three letter, uh, certifications, sound, uh, warm and fuzzy, you have to make sure that they actually do have a third party auditor that is continuously monitoring their infrastructure.
470
00:38:25,557.157437 --> 00:38:26,907.157437
We have over 200 controls.
471
00:38:26,907.157437 --> 00:38:28,797.157437
I have to background check every employee.
472
00:38:28,797.157437 --> 00:38:30,957.157437
I have to make sure we're doing password rotations.
473
00:38:31,287.157437 --> 00:38:34,17.157437
I have to make sure we do annual training on hipaa and.
474
00:38:34,387.157437 --> 00:38:37,327.157437
Social, uh, social engineering for the company.
475
00:38:37,327.157437 --> 00:38:43,867.157437
Like, there's just a gazillion different things we have to do to make sure that we deliver on our promise to, to our customers.
476
00:38:44,257.157437 --> 00:38:52,407.157437
And there are a host of, of other companies like ours that are doing those kinds of things that are working in partnership with the AI firms, but the smart ones.
477
00:38:52,407.157437 --> 00:38:56,792.157437
And I think that the ones that are gonna succeed are gonna, are gonna keep those providers at arms length.
478
00:38:57,352.157437 --> 00:39:07,332.157437
And make sure that they're looking to their customers to deliver solutions and, you know, making sure they answer that security and privacy question with an emphatic, we've got this solved period.
479
00:39:14,173.8550076 --> 00:39:17,803.8550076
To put you back in sort of the third party vendor perspective.
480
00:39:18,763.8550076 --> 00:39:28,33.8550076
If you are starting a legal tech company today, Scott, from scratch, what are you looking for as sort of the white space to focus on? Because.
481
00:39:29,233.8550076 --> 00:39:38,533.8550076
Clearly, there're gonna be a lot of solutions that are developed through vibe coding that will be just too small of a scale to be worth anyone's time who isn't working in some niche area.
482
00:39:39,283.8550076 --> 00:40:03,483.8550076
But there always will be things that get productized, things that are solutions that cut across enough practice groups, enough law firms, enough areas of the law that it makes sense to productize What does that decision look like for a vendor who's thinking about what problems to tackle or what opportunities to go after? Yeah, I mean, I, I think most of the legal tech like startups right now I think are thinking honestly too small.
483
00:40:03,693.8550076 --> 00:40:09,273.8550076
They're thinking, oh, I'm gonna solve this one small niche problem and then I'm gonna build a business from that.
484
00:40:09,643.8550076 --> 00:40:18,913.8550076
You know, and this may sound horrible, but unless you have a plan towards world domination, um, you're just gonna get squeezed and you're probably gonna get squeezed a lot faster because of how fast the AI is going.
485
00:40:19,463.8550076 --> 00:40:22,583.8550076
And you know, that doesn't mean there aren't opportunities.
486
00:40:22,583.8550076 --> 00:40:29,783.8550076
There are all kinds of opportunities here, but again, it to me is, is this sort of, it's not delivering software to firms, it's.
487
00:40:30,8.8550076 --> 00:40:35,228.8550076
Delivering either expertise or understanding on how they can navigate this transition.
488
00:40:35,618.8550076 --> 00:40:42,218.8550076
Um, again, that's, you know, landing for deployed engineers inside that firm and helping them, you know, use these tools so they can build their own things.
489
00:40:42,558.8550076 --> 00:40:47,468.8550076
You know, really getting that sort of mantra, through to them that this stuff is disposable and that's okay.
490
00:40:47,768.8550076 --> 00:40:50,738.8550076
You know, it's interesting too because, you know, we've had.
491
00:40:51,563.8550076 --> 00:40:56,93.8550076
I've had some folks on my team that ended up moving on that just they couldn't flip the bit.
492
00:40:56,663.8550076 --> 00:41:05,563.8550076
And that bit is how do I use AI in such a way that, that it's always continuously making me better and making the company better with what we're doing.
493
00:41:05,563.8550076 --> 00:41:11,683.8550076
And when you see somebody flip that bit, uh, it it's like transformational not only for them, but for the company.
494
00:41:11,683.8550076 --> 00:41:12,58.8550076
And so.
495
00:41:12,913.8550076 --> 00:41:21,463.8550076
And what I'm finding is it's the younger engineers, it's especially engineers who maybe have a little bit of experience, but not too much candidly the, the like.
496
00:41:21,613.8550076 --> 00:41:22,333.8550076
Perfect.
497
00:41:22,433.8550076 --> 00:41:30,803.8550076
You know, one of our strongest engineers is a philosophy major who used to be an SDR at Databricks for God's sakes.
498
00:41:30,893.8550076 --> 00:41:31,343.8550076
Um.
499
00:41:32,228.8550076 --> 00:41:38,48.8550076
He's unbelievable because he has no, no, like affinity or, or like attachment to his code.
500
00:41:38,388.8550076 --> 00:41:41,898.8550076
He doesn't really even care what language it's in as long as it solves the problem.
501
00:41:41,898.8550076 --> 00:41:44,988.8550076
And we can build tools that will continuously maintain this stuff.
502
00:41:45,258.8550076 --> 00:41:46,358.8550076
We don't care what language it's in.
503
00:41:47,23.8550076 --> 00:41:50,893.8550076
And is it maintainable by humans? No, it's not.
504
00:41:50,893.8550076 --> 00:41:52,783.8550076
But guess what? That's the direction that we're going.
505
00:41:53,143.8550076 --> 00:41:57,703.8550076
Can you build a system that's maintainable, period? That's the question.
506
00:41:57,703.8550076 --> 00:42:07,903.8550076
And so to me that's kind of, anyways, I'm, I'm kind of off task again because I, you know, I get going down a path here, but, um, no, I mean, to me, like the, one of the big takeaway themes here is.
507
00:42:08,623.8550076 --> 00:42:30,668.8550076
If case Mark and other technology companies, collectively crack the code on creating secure environments for internal build of effective solutions, it's going to truly unlock the potential for law firms to fully leverage to capabilities that these AI uh, technologies can offer in a way that maybe.
508
00:42:31,673.8550076 --> 00:42:39,353.8550076
Decouples them from a dependency on 15, 20, 25 vendors offering niche products, which overwhelms legal departments.
509
00:42:39,383.8550076 --> 00:42:41,363.8550076
It is not practical as a long-term solution.
510
00:42:41,423.8550076 --> 00:42:48,143.8550076
And also, by the way, heads off the other version of this, which is people just looking to one consolidated.
511
00:42:48,638.8550076 --> 00:42:57,398.8550076
Mega incumbent provider, right? We could probably name four, five companies that would fit that mold, which has its own downsides and risks.
512
00:42:57,398.8550076 --> 00:43:14,178.8550076
So this is an opportunity, it sounds like, to really position our legal industry, to take advantage of what this technology has to offer without falling into some of these, um, dependencies and traps that frankly we've seen sector after sector after sector fall into over the last 15, 20 years.
513
00:43:14,598.8550076 --> 00:43:14,838.8550076
Yeah.
514
00:43:15,723.8550076 --> 00:43:16,323.8550076
Without a doubt.
515
00:43:16,323.8550076 --> 00:43:17,553.8550076
I mean, I, I think that's dead on.
516
00:43:17,553.8550076 --> 00:43:24,223.8550076
And I think you know, I, I, I may talk, you know, some, some trash about, you know, the big providers and some of these things.
517
00:43:24,583.8550076 --> 00:43:37,953.8550076
Ultimately, I think it's, this is gonna be, there's a huge opportunity here, and I think if you're, if you're, earlier in your career, even if you're like, you know, halfway through your career, whatever that even means today, I think leaning into AI now is absolutely critical.
518
00:43:37,953.8550076 --> 00:43:40,953.8550076
Just learning it, knowing these tools, I think you'll find that it's.
519
00:43:41,673.8550076 --> 00:43:41,853.8550076
It.
520
00:43:41,853.8550076 --> 00:43:47,673.8550076
Once again, you flip that bit in your mind and you realize, oh, this, this is actually, um, really powerful for me.
521
00:43:48,3.8550076 --> 00:43:54,913.8550076
I mean, if an attorney could like actually solve the problems they want with the software that they actually wanna solve, that to me is really interesting.
522
00:43:54,913.8550076 --> 00:44:07,273.8550076
And, and when we look at these vibe coding solutions, one of the things we, we do is, you know, obviously we work closely with the vibe coating community and we're hosting a vibe coating event at Legal Week in a couple weeks, we're doing one in London, like it's it.
523
00:44:07,503.8550076 --> 00:44:09,213.8550076
Actually really kind of neat.
524
00:44:09,423.8550076 --> 00:44:26,13.8550076
What we do is we look at those different projects and we ask ourselves, is there something that's a fundamental primitive inside of that project that we should bubble up into Case mark? In other words, wow, that's a tool or that's a component that every attorney's gonna need or some significant segment.
525
00:44:26,13.8550076 --> 00:44:32,343.8550076
Can we take that idea and sort of build a, some solution around that? So that's how we kind of lean into it.
526
00:44:32,403.8550076 --> 00:44:35,13.8550076
And then we also have, you know, folks who are coming to us who just say.
527
00:44:35,538.8550076 --> 00:44:36,138.8550076
Hey, I can't.
528
00:44:36,138.8550076 --> 00:44:37,728.8550076
I can't ever, I can't get this finished.
529
00:44:37,728.8550076 --> 00:44:40,703.8550076
I can't get this over the finish line to make it, you know, useful in production.
530
00:44:41,688.8550076 --> 00:44:44,418.8550076
We can now take a vibe coded 0.1
531
00:44:44,418.8550076 --> 00:44:49,998.8550076
that you have, and literally our agents, you know, our AI agents behind the scenes can take it to that 1.0.
532
00:44:49,998.8550076 --> 00:44:52,608.8550076
In other words, it'll do the security and privacy audits.
533
00:44:52,608.8550076 --> 00:45:00,378.8550076
It'll make sure that it's wrapped with authentication, that the database is secure, that you're not, you know, leaking any data to the, to the LLMs, all those kinds of things.
534
00:45:00,703.8550076 --> 00:45:02,413.8550076
And then that's exciting for these folks.
535
00:45:02,413.8550076 --> 00:45:10,153.8550076
That actually is potentially a new opportunity for these vibe coding attorneys to build solutions or, join companies that are building solutions.
536
00:45:10,153.8550076 --> 00:45:17,908.8550076
And that's, I think, I think that's a tricky beast that a lot of these attorneys, because the reality is the vi, the really killer vibe coding attorneys could have been.
537
00:45:18,448.8550076 --> 00:45:22,98.8550076
Attorneys, they could have been technical, like, product managers.
538
00:45:22,98.8550076 --> 00:45:24,288.8550076
They could have been, really strong engineers.
539
00:45:24,288.8550076 --> 00:45:26,508.8550076
They just chose legal as their path.
540
00:45:26,538.8550076 --> 00:45:33,168.8550076
Um, they're smart people, so it's natural that they could learn vibe coding once the technology got to a place where it is today.
541
00:45:33,568.8550076 --> 00:45:33,988.8550076
Um.
542
00:45:34,583.8550076 --> 00:45:37,973.8550076
So, so it's, to me, this is a, a ridiculously exciting time.
543
00:45:38,373.8550076 --> 00:45:40,683.8550076
I will say it's also an exhausting time.
544
00:45:40,713.8550076 --> 00:45:44,403.8550076
I've never worked so goddamn hard and I have AI helping me.
545
00:45:44,763.8550076 --> 00:45:58,863.8550076
But it's also, it's also, you know, very rewarding and very exciting, um, when you see these, these aha moments or you're on a call with a, with a customer, and especially the video calls and you actually see their jaw drop and they're like, what? I can do that now.
546
00:45:58,863.8550076 --> 00:46:02,193.8550076
And you're like, yeah, that's, and this is just the tip of the iceberg, you know? Yeah.
547
00:46:02,453.8550076 --> 00:46:07,373.8550076
I hope that everyone's taking a little bit of time to professionally develop themselves in this area.
548
00:46:07,943.8550076 --> 00:46:09,293.8550076
I know a lot of people are really busy.
549
00:46:09,293.8550076 --> 00:46:13,823.8550076
It can be hard and so hopefully their organizations or employers or giving them that space.
550
00:46:14,63.8550076 --> 00:46:15,383.8550076
'cause it helps the companies too.
551
00:46:15,413.8550076 --> 00:46:18,83.8550076
So I completely agree and.
552
00:46:18,638.8550076 --> 00:46:25,798.8550076
I'm curious, the legal week event the hackathon, can you tell us about the hackathon? What's the plan with that? Yeah.
553
00:46:25,798.8550076 --> 00:46:30,718.8550076
The idea is that we'll have, you know, we'll have a couple folks there from from case mark.
554
00:46:30,778.8550076 --> 00:46:34,828.8550076
Uh, we actually have a, a, one of our Ford deployed engineers lives in Queens.
555
00:46:34,928.8550076 --> 00:46:36,368.8550076
And so we'll have a couple of us there.
556
00:46:36,668.8550076 --> 00:46:40,718.8550076
We're hosting a, a venue, it's, it's not about coming in and using case mark.
557
00:46:40,748.8550076 --> 00:46:43,838.8550076
Um, it's specifically actually under the auspices of the A four L.
558
00:46:44,168.8550076 --> 00:46:46,628.8550076
The A four L is the Association for AI and Legal.
559
00:46:46,628.8550076 --> 00:46:48,398.8550076
This is a a 5 0 1 C six.
560
00:46:48,398.8550076 --> 00:46:51,198.8550076
It's basically a vendor, uh, sponsored organization that helps.
561
00:46:52,23.8550076 --> 00:46:55,83.8550076
Our members who are, law firms, attorneys, those kinds of things.
562
00:46:55,333.8550076 --> 00:46:56,563.8550076
They join for free.
563
00:46:56,563.8550076 --> 00:47:01,993.8550076
It's the members pay to basically build these programs that help people adopt this technology.
564
00:47:02,303.8550076 --> 00:47:06,653.8550076
And better and pretty much just understand it because the, the thinking with the A four L is.
565
00:47:06,703.8550076 --> 00:47:08,53.8550076
The rising tide lifts all boats.
566
00:47:08,53.8550076 --> 00:47:13,873.8550076
If we can help people adopt this technology faster and more confidently, that's just gonna help all the vendors involved.
567
00:47:13,873.8550076 --> 00:47:22,783.8550076
And so, um, I've done this previously with open source stuff and other sort of vendor based you know, not-for-profit kind of things, uh, previously, and they've been really, really successful.
568
00:47:23,53.8550076 --> 00:47:25,423.8550076
So we basically said, let's host an event.
569
00:47:25,753.8550076 --> 00:47:28,408.8550076
There's gonna be a whole bunch of attorneys in New York for Legal Week anyways.
570
00:47:28,458.8550076 --> 00:47:33,433.8550076
We're doing it at this coworking facility that's close to, um, uh, the Javits Center.
571
00:47:34,213.8550076 --> 00:47:40,843.8550076
And you can just come in, we'll, we'll tell us your idea that you wanna build, we'll help you get tooled up on it and you can start playing with it.
572
00:47:41,183.8550076 --> 00:47:43,463.8550076
We're not gonna just say, oh, you have to come use the case Mark stuff.
573
00:47:43,523.8550076 --> 00:47:45,893.8550076
We'll, it's gonna be anything anybody wants to play with.
574
00:47:45,893.8550076 --> 00:47:50,933.8550076
And they wanna do, you can do notebook LM on Google, or, you know, play with.
575
00:47:51,83.8550076 --> 00:47:53,393.8550076
Claude Cowork or whatever it is, doesn't matter.
576
00:47:53,393.8550076 --> 00:47:56,553.8550076
Come in, you know, you'll, you'll get to um, build something.
577
00:47:56,553.8550076 --> 00:48:01,203.8550076
Ideally, what'll happen in the couple hours that you're there is you'll actually build a product that you can go, cool.
578
00:48:01,203.8550076 --> 00:48:03,273.8550076
Wow, I, I made something from scratch.
579
00:48:03,643.8550076 --> 00:48:10,158.8550076
And I think the other piece is getting connected to other like-minded people who are doing these things into your industry.
580
00:48:10,178.8550076 --> 00:48:13,393.8550076
That's another piece of what we've been trying to do with the A four L is.
581
00:48:13,663.8550076 --> 00:48:28,513.8550076
Build this connective tissue that spans, beyond just legal to this sort of, oh, I'm, I'm interested in this tech, because those connections are what lead to the next thing that maybe you're gonna do professionally or, or, you know, you find a project you didn't even know about.
582
00:48:28,963.8550076 --> 00:48:30,313.8550076
To me, that's, that's the thing.
583
00:48:30,313.8550076 --> 00:48:32,323.8550076
I mean, that's something AI's never gonna solve for.
584
00:48:32,323.8550076 --> 00:48:36,583.8550076
And so, um, we, we always wanna lean into those things that actually involve humanity.
585
00:48:36,583.8550076 --> 00:48:37,873.8550076
So, uh, yeah.
586
00:48:38,713.8550076 --> 00:48:39,343.8550076
Very cool.
587
00:48:39,613.8550076 --> 00:48:39,633.8550076
I great.
588
00:48:39,633.8550076 --> 00:48:39,818.8550076
I love it.
589
00:48:40,658.8550076 --> 00:48:44,93.8550076
I actually, I have my sister send me an old laptop that she's dusting off.
590
00:48:44,93.8550076 --> 00:48:47,663.8550076
I'm, I'm gonna scrape it and I need like a burner laptop or something.
591
00:48:47,663.8550076 --> 00:48:52,43.8550076
'cause Yeah, I hear, um, it's actually not a bad idea.
592
00:48:52,43.8550076 --> 00:48:54,863.8550076
We, we might actually bring a couple, something that we could do for folks.
593
00:48:54,893.8550076 --> 00:48:56,713.8550076
'cause you can't obviously install any of this stuff on your.
594
00:48:57,518.8550076 --> 00:48:58,538.8550076
Um, on your machine.
595
00:48:58,538.8550076 --> 00:49:02,48.8550076
Most machines, even even my wife's machine she can't install anything on.
596
00:49:02,288.8550076 --> 00:49:02,558.8550076
Yeah.
597
00:49:02,558.8550076 --> 00:49:04,568.8550076
So I'm, I'm tooling, I'm, I'm tooling up.
598
00:49:04,568.8550076 --> 00:49:07,358.8550076
I can't wait to see kind of how case Mark fits into the whole picture.
599
00:49:07,758.8550076 --> 00:49:13,318.8550076
Also find very kind of encouraging, inspiring the ways that you're refocusing your business.
600
00:49:13,428.8550076 --> 00:49:19,858.8550076
Azure brings you closer to the sort of some of the consulting work, the four deployment of people really sort of shows how.
601
00:49:20,233.8550076 --> 00:49:29,483.8550076
We all should be thinking about the roles that we're gonna play in this kind of new economy, right? Where we really need to think hard about what is the sort of value add our human brains can offer.
602
00:49:29,483.8550076 --> 00:49:32,753.8550076
And, and it's really interesting to hear your journey with, with case Mark.
603
00:49:33,83.8550076 --> 00:49:41,903.8550076
It seems to very much align with, um, with what would you probably would give as general advice to people for how to, how to shape their careers around this new world that we're entering.
604
00:49:43,28.8550076 --> 00:49:43,538.8550076
Yeah.
605
00:49:43,538.8550076 --> 00:49:43,928.8550076
Yeah.
606
00:49:43,928.8550076 --> 00:49:50,778.8550076
I, I think, I think that is the, I mean, as a serial entrepreneur, I'm very used to you know, ready, fire, aim.
607
00:49:51,48.8550076 --> 00:49:53,868.8550076
Um, well, let's just, let's go and we'll figure it out as we go.
608
00:49:53,873.8550076 --> 00:50:05,878.8550076
And, and, you know, for better or for worse and I think it's, it's really interesting to see, you know, attorneys struggle with the, oh my gosh, this is potentially gonna have an impact on my indu, on my industry and on my, my, my role.
609
00:50:05,878.8550076 --> 00:50:14,963.8550076
What do I do? Normally not, I shouldn't say normally, I don't wanna put everybody in a bucket, but this idea that, oh, I'm, I'm on a partnership track and that's gonna take me seven years and I know what I need to do to do that.
610
00:50:15,303.8550076 --> 00:50:19,983.8550076
Crank my billable hours, make sure I hit 18, 1900, 2100 hours, whatever the math is.
611
00:50:20,413.8550076 --> 00:50:22,663.8550076
And then, you know, once I do that, then I'm gonna be fine.
612
00:50:22,663.8550076 --> 00:50:25,453.8550076
But now this adds sort of a curve ball in there.
613
00:50:25,513.8550076 --> 00:50:26,953.8550076
So tooling up is gonna help you.
614
00:50:26,953.8550076 --> 00:50:29,263.8550076
One, that's actually gonna help you on the, if you wanna stick.
615
00:50:29,318.8550076 --> 00:50:30,428.8550076
Through that partner track.
616
00:50:30,758.8550076 --> 00:50:35,108.8550076
'cause guess what? You're gonna be able to do more or advise the firm successfully on what you should do.
617
00:50:35,508.8550076 --> 00:50:41,838.8550076
And you know, two is maybe you'll get the bug, maybe you'll get the entrepreneurial spirit and want to go spin up something yourself.
618
00:50:42,178.8550076 --> 00:50:49,258.8550076
To me, I would love to see just a whole bevy of, of, you know, attorney led legal tech startups that are building interesting solutions.
619
00:50:49,563.8550076 --> 00:50:58,923.8550076
Four attorneys, I think they'd be far more successful than, you know, a bunch of these like, Y Combinator, 20 something punks saying, we're gonna disrupt everything.
620
00:50:59,313.8550076 --> 00:51:00,813.8550076
I'm gonna go meet with an attorney now.
621
00:51:00,873.8550076 --> 00:51:01,923.8550076
You know, like, oh, wait a minute.
622
00:51:01,983.8550076 --> 00:51:04,173.8550076
You know, like that to me is, is crazy.
623
00:51:04,173.8550076 --> 00:51:04,323.8550076
But yeah.
624
00:51:04,323.8550076 --> 00:51:04,503.8550076
Anyways.
625
00:51:05,513.8550076 --> 00:51:13,403.8550076
Lots of opportunity, ums opportunity, lots of room for inspiration and, um, and, and fortunately people building the infrastructure for us to do that.
626
00:51:13,403.8550076 --> 00:51:15,533.8550076
Most importantly, I think that's, that's the critical piece here.
627
00:51:15,533.8550076 --> 00:51:21,173.8550076
So Scott, thank you so much for your time and for coming on a version up to tell us all about, uh, case Mark and, and what you've been doing.
628
00:51:22,103.8550076 --> 00:51:22,403.8550076
Awesome.
629
00:51:22,403.8550076 --> 00:51:23,63.8550076
Thanks for having me.
630
00:51:23,63.8550076 --> 00:51:23,698.8550076
I really appreciate it.