This week, we welcome back Tom Martin, CEO of LawDroid, to discuss his widely read “AI Law Professor” column for Thomson Reuters and his five-level roadmap for legal AI. Martin explains that the framework was inspired by a leaked OpenAI memo and aims to give legal professionals a clearer picture of AI’s trajectory. The five levels range from basic chatbots to fully AI-run organizations, with intermediate stages such as reasoners, agents, and innovators. According to Martin, while we are still in the early stages, the release of GPT-5 and its reasoning capabilities has accelerated progress toward higher levels, especially in the development of autonomous agents.

The conversation turns to the implications of GPT-5’s hybrid reasoning model, which combines inference with step-by-step reasoning to deliver more relevant answers. Martin sees this as a significant shift for the legal industry, moving beyond single-response chatbots toward sustained, goal-oriented AI. He predicts that while the technology for fully autonomous legal agents could be available within a year, widespread adoption in law firms and corporations will take closer to three years. However, with these advancements come ethical concerns. Martin outlines four principles for responsible AI agents: transparency, autonomy, reliability, and visibility, cautioning that AI’s knowledge is always bounded and potentially incomplete.

Reflecting on the legal industry’s pace of change since their last discussion, Martin notes that while some firms are sprinting to adopt AI, others may already be too late to catch up. He warns that professional services organizations must actively integrate AI to remain competitive. The discussion explores the potential for tech giants or AI companies to acquire major legal information providers, and Martin argues that the future lies in blending software, consulting, and education into a unified service model. This integrated approach, he believes, will be necessary for survival in a market where AI is capable of generating solutions without traditional software development cycles.

Beyond the legal tech roadmap, Martin shares insights from his teaching at Suffolk University Law School and his observations from producing the “Last Week in Legal AI” news series. He sees both opportunities and risks for the next generation of lawyers, particularly in acting as translators between AI systems and legal practice. The discussion touches on generational attitudes toward AI, with younger users showing both skepticism and heavy reliance on AI for personal and professional support. Martin also addresses societal concerns, from AI in mental health applications to job displacement, and stresses the importance of curating AI outputs with human judgment.

The episode wraps with Martin’s update on the American Legal Technology Awards, set for October 15 at Suffolk University Law School in Boston, which he describes as “the Oscars of legal tech.” When asked about the biggest challenge for the next few years, Martin points to the uncertainty of where professionals will fit in a rapidly shifting world. He envisions a possible new model that combines service, education, and software to deliver legal help at scale, but stresses that no one knows exactly how the future will unfold. His hope is that the AI-driven abundance ahead will be shared broadly, without excluding people from its benefits.

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[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
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Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Marlene Gebauer (00:00)
Hi, I’m Marlene Gabauer from The Geek in Review and I have Nikki Shaver here from Legal Technology Hub. Nikki, you have some really important news about an agent’s map, right?

Nikki Shaver (00:11)
That’s right. So some of you listening will be aware of our general market map for generative AI and legal tech. We actually just released our map of agentic AI products in legal. So anyone following along to your podcast, Marlene knows by now that agents have been a really hot topic in late 2024 into 25. And LTH has just had what we call our agents week, which just meant lots of different kinds of content dedicate

dedicated to this trend, including an excellent article by Stephanie Wilkins diving into the definition of agents, a timeline of major agentic announcements in legal tech, and our map, which shows already over 100 products in legal that now include some form of agentic AI. So it is a lot. I know it’s moved very quickly. Access it all on www.legaltechnologyhub.com.

Marlene Gebauer (01:02)
That’s a lot!

Nikki Shaver (01:11)
and look for it as well on LinkedIn. It’s an interesting one to be able to show, especially if you’re doing some strategic analysis of the market or want to show internally at your firm or legal department how things are changing and how quickly things are evolving in the market.

Marlene Gebauer (01:29)
Yeah, that’s going to be an incredibly useful tool for everybody. So thank you for that.

Nikki Shaver (01:34)
It’s a pleasure.

Marlene Gebauer (01:42)
Welcome to The Geek in Review, the podcast focused on innovative and creative ideas in the legal industry. I’m Marlene Gabauer.

Greg Lambert (01:50)
and I’m Greg Lambert.

Marlene Gebauer (01:53)
This week we’re joined by Tom Martin, CEO of LawDroid and Deep Legal. So Tom, thank you very much for joining us on the Geek in Review.

Tom Martin (02:01)
It’s my pleasure. Thank you, Marlene. Thanks, Greg, for having me on.

Greg Lambert (02:05)
Yeah, it’s good. ⁓ Yeah. So it’s nice when we have these meta shows of having somebody has their own YouTube channel and joins us. ⁓ So so Tom, the the last show that we had you on was was back last year in November. And I went back and looked at that. And, you know, we were deep into the process then of.

Marlene Gebauer (02:05)
our fellow podcaster.

Greg Lambert (02:30)
know, chat bots and talking about access to justice and workflow automation. But you wrote something recently in the Thomson Reuters ⁓ in their online ⁓ newsfeed about what you called the AI law professor ⁓ when chat bots become senior partners. And in this, you discuss this

five level roadmap for legal AI and it really, I thought it was really good. And so I reached out and said, please come on and talk about it. so what was it that compelled you to outline that type of five level classification system?

Tom Martin (03:16)
Well, yeah, ⁓ I’m really lucky I have that platform. I get to call myself the AI Law Professor and write ⁓ that column for Thompson Reuters. ⁓ What compelled me is that actually that came from a leaked memo that came out of OpenAI. They didn’t intend for people to see it, or maybe that was a marketing ploy. I don’t know. ⁓ But I wanted to give people a map because

The first column I wrote was kind of jumping into the weeds about a specific thing. And then I wanted to kind of pull back from that, ⁓ a move that I kind of learned from Richard Susskind because he likes to zoom in on an issue and then zoom back from the issue to give you that kind of perspective. So I thought by using that to give people a map of where we might be going with AI would be really helpful for them to see what might be coming down the road.

Marlene Gebauer (04:14)
And so while we’re decoding the future handbook, can you walk us through the levels? So where’s the tech today? ⁓ Where do you think it might land over the next few years?

Tom Martin (04:29)
Yeah, so it first starts with level one, which is chatbots. And so I was doing chatbots nine years ago. ⁓ That’s not anything spectacular or earth shattering.

Marlene Gebauer (04:38)
I have to say I’m a little depressed to hear that since everybody’s just talking about

Greg Lambert (04:41)
Hahaha

Marlene Gebauer (04:43)
chatbots now. That’s level one. We’re only at level one.

Greg Lambert (04:45)
I was, I was doing Yahoo chat, you know, at the turn of the century.

Tom Martin (04:49)
⁓

Yeah, the next level after chatbots is reasoners. So, you know, when you actually have ⁓ the ability for it to think through step by step and break down a problem. ⁓ And that has been only about a year of reasoners that we’ve had. And then after that, agents. And there’s different flavors of agents that we’re learning about now.

There’s workflow agents and then there’s actually like actually autonomous agents, which we really haven’t gotten to. There’s been some plays at that and I could talk more about that in depth, but I don’t think we’re really there yet. After that becomes innovators. Innovators is interesting because it’s kind of hard to wrap our heads around, but so what would make an innovative AI?

The example that I throw at people is imagine that you could take an AI and you could roll its knowledge back to the year 1900. And given everything that it knows at that time in 1900, would it be able to come up with, let’s say, the theory of special relativity on its own? If it could,

That’s what we mean by an innovative AI. It’s one that could actually like take that jump, those conceptual jumps of putting things together, connecting the dots and coming up with a new invention or idea. then lastly, sorry, number five is organizations. It’s where all of these things come together and you could actually run an entire organization with the benefit of AI ⁓ and everything it could do.

Greg Lambert (06:14)
⁓ Well, ⁓ good.

Marlene Gebauer (06:29)
anybody without oh boy

Tom Martin (06:32)
Potentially, yeah.

Greg Lambert (06:35)
Yeah.

Well, I was, I was going to jump to level three in my notes, but, ⁓ open AI today just rolled out the GPT five, ⁓ and essentially set the default to the reasoning models now. ⁓ and that’s, so from what I’m, from what I’m gathering, it’s like most of the previous models are going to be sunset and

the default is going to be these reasoning models. And so I know I think you had a little chance to play with the API a little bit, but ⁓ what do you think that changes for the legal industry that the AI now isn’t just the chat bot kind of one shot things, but rather now.

every time that you’re going to deal with it, you’re dealing with this reasoning model. Do you think that’s going we’re going to need to adjust to that?

Tom Martin (07:41)
Well, there’s definitely an adjustment period for all of this. ⁓ It’s a crazy amount of change in a small amount of time, but there’s two things that stand out to me. One is that ⁓ this model is best described as a hybrid model. So before we had something that was straight ⁓ inference where it just like gave you an answer. Then we had the reasoners, which would think things through and kind of plan things out and then give us a response. What this thing does is it

it kind of thinks about which is the best approach and then provides us with just what we need. So it’s kind of like putting together both of those approaches and that way it just provides us the best answer that we would likely need.

So it saves a lot of time and it puts everything together. The second thing I would mention is that in terms of not only law firms, but anyone else using or benefiting from this model, like what can it provide us that’s different? Because I could tell you that as these models get better, it’s kind of harder and harder to tell how they’re different because they’re getting so good. But one thing that I think kind of clarifies this, I played around with operator.

the first, you know, attempted agency that they used back when it first came out. Operator, I would give it a task to look something up and it would like open up multiple tabs and just kind of send itself in circles because it opened way too many tabs on the browser it was using. Right? It would just kind of get lost in the assignment. And then Agent came out just recently and I tried using Agent and

I assigned it a task of researching something, giving me a report. Okay. Because part of it is deep research. It did that really well. But then the next part of it where I said, Hey, can you make a Google doc out of that? And then email it to me, email it back to me. It got stuck on that part of it for 26 minutes and was just going around in circles. So what this new model can do is it can actually keep that attention on the tasks that it’s given.

and know the assignment and carry it forward for a longer period of time with more attention.

Marlene Gebauer (10:02)
So, ⁓ Tom, you and your level, I want to go back to the level three. So you’re talking about that, know, AI would do, you know, proactive monitoring, filings, you know, interacting with systems. And you’re saying less than three years, right, to get there? Yeah.

Tom Martin (10:20)
to fully autonomous?

Well, ⁓ I think that was my estimate, is that we would probably be there with people using it, know, adoption. I think in terms of it actually being there, GPT-5 is actually taking us much closer.

Marlene Gebauer (10:31)
Mm-hmm.

Tom Martin (10:39)
that ability to have like a sustained effort where it actually can work towards accomplishing that goal is going to definitely get as far as an operator and chat GPT’s agent. I think what their plan was is that they launched chat GPT agent with the best model they had at the time with the intention of bringing five in to make it even more effective. So I think in terms of autonomous agents that actually work,

probably in the next couple of years, we’ll have something that works really well. ⁓ As far as adoption, do think it would, you know, like within a year we’ll have the technology that’s working. ⁓ Within about three years, we’ll actually have adoption ⁓ of people across, you know, business and corporations and law firms.

Marlene Gebauer (11:27)
So, okay, so then my next question is like what about the ethical concerns?

Tom Martin (11:33)
Yeah, there’s definitely ethical concerns and actually my next column for Thomson Reuters is talking exactly about the principles that we should employ when using agents. And there’s four of them and all of them go towards ethics. You know, one is transparency.

with whatever agent we use, we need to have transparency. We need to know what it’s doing and why it’s doing it. So it actually reports back to us and gives us explanations of what it’s doing. It has to be autonomous or otherwise it’s not an agent, but we really shouldn’t mistake autonomy for reliability just because it might be a ⁓

you know, a good model, a smart model doesn’t mean it’s entirely reliable. And so that’s the third principle is that we have to ensure reliability. And lastly, visibility. And I think this one is actually overlooked by a lot of people. Visibility has to do with the body of information and knowledge that’s made available to the agent, because there’s always some limit.

on how much knowledge we have available to us. And we can only make decisions based upon what we know, right? Not what we don’t know, obviously. But what we don’t know might be important, but we just don’t know it. And so likewise, an agent is going to have some kind of limitation on what it knows. And so it could make a mistake potentially by only relying on what it knows. And there could be something that’s left out. So we need to be cognizant of that.

know, agents are not seers, they’re not magical. They only know what they know, and so we need to be cautious about relying on them and keeping in mind that they only have a certain limited amount of information available to them.

Marlene Gebauer (13:26)
I mean, sounds like there’s still the data problem that firms have. Having good data to give to your system. So you’re still going to have the same sort of problems if you have bad data or not enough data, I guess, to use these tools. ⁓

Tom Martin (13:53)
Absolutely, absolutely. ⁓ And there has to be a way of viewing what those limitations are, you know, knowing what the scope of knowledge is, and, and then taking active steps to supervise it and add more if necessary.

Marlene Gebauer (14:13)
I’m going to sort of switch a little bit, talking about the levels and sort of move into ⁓ sort of how things are since our last conversation. ⁓ I’m pulling out a quote, firms that resist may find themselves bypassed by history.

in your articles. now that we’re about eight months past our last conversation, what signs are you seeing that signal who’s sprinting and who’s strolling?

Tom Martin (14:47)
Well, you can see that a lot of firms are trying to join the sprint. ⁓ And I think, you know, some of the…

Marlene Gebauer (14:52)
and really trying

to sprint, not just the hype, right?

Tom Martin (14:58)
Well, there are firms that sign on just for marketing purposes where they could reflect that, show that to their clients. ⁓ I’ve actually been speaking with innovation officers within firms that are actually making a change.

And that’s actually something I’m doing right now towards a book that I’m writing about this type of ⁓ experience and innovation that’s happening within firms because I want to hear it from the boots on the ground, the people that are actually doing it in a real way, not just press releases ⁓ and what they might have in common. But ⁓ certainly there’s a lot of talk about innovation. ⁓ But I think that in some ways,

not to sound controversial, but in some ways I think…

Marlene Gebauer (15:48)
Go ahead, sound controversial.

We like that.

Tom Martin (15:51)
I

think in some ways it may already be too late. It might already be too late because the level of sophistication and capability that we’re seeing even before today’s release of GPT-5 has been exceptional and GPT-5 brings a lot of these disparate things together in one model with a high proficiency of expertise right out of the box.

This is without any fine tuning or additional training. ⁓

And so if you’re a professional services company or a professional

You have to be working ⁓ with this technology to amplify what you do. And there’s always that concern kind of far off in the back of our heads, which is, is it possible at some point for that organization that I talked about at level five to actually be undertaking this work and delivering work product at scale? Yes.

Yes, it is. you know, some companies that are participating in legal tech right now, ⁓ you know, some of them, are they participating with lawyers for the purpose of helping lawyers or learning their tactics and work product and using it to their advantage? Like, there’s a question about that. So it’s a difficult time because every model

Marlene Gebauer (17:20)
you

Tom Martin (17:31)
⁓ essentially is a C change and we just need to find our way to navigate through it.

Marlene Gebauer (17:37)
I’m curious, mean, with this new release, I mean, how, because I know that they did mention that it’s, they’re sort of looking at at Chat GPT for legal, like how is that going to impact some of the existing, you know, LLM tools that firms are using now?

Tom Martin (18:02)
Yeah, I mean, it was mentioned explicitly more than once. ⁓ Sam Altman hinted at it. ⁓ Mark, who followed him, ⁓ also mentioned and legal, you know, like this is a this is an expert in your pocket. ⁓ Greg also, when he was talking, was saying that it’s essentially an expert in many things, including legal. ⁓ So this is definitely something that

You know, people are already using it. They’re already getting legal ⁓ guidance from chat GPT. And now with the benefit of GPT-5, they’re going to get better, you know, better information and guidance and yes, advice. ⁓ And so then, you know, the real question isn’t whether or not lawyers want that to happen or if they’re going to allow it to happen, it’s already happening. And so we just need to find a way of

living in a world where we’re still relevant and we can contribute to, you know, helping people in a real way that makes a difference in their lives.

Marlene Gebauer (19:14)
I was going to pose ⁓ another question because ⁓ Greg asked our guest last week in Crutchfield this question I thought was really interesting that and sort of given what you’re saying about ⁓ you know chat GPT you know could they buy kind of one of our large legal information you know information or you know corporations I mean is that feasible?

Tom Martin (19:45)
100%. Actually, when I was teaching my class at Suffolk, ⁓ towards the end of it, because this was ⁓ last spring semester, ⁓ I was talking to my students at the end that what I see as the way forward for business generally, know, software businesses, like the legal tech companies, there’s, I don’t see a future in that, you know, software.

Marlene Gebauer (19:45)
Does it make sense? ⁓

Mm-hmm.

Tom Martin (20:11)
⁓ As

we saw demonstrated with GPT-5, you could just basically ask for what you want and it creates it. That was possible even before GPT-5 with Replet. There were various solutions that were working really well, some of which I use myself. And so software on its own, dead end. Consulting on its own, dead end. Professional ⁓ education just solely on its own.

to me as a way of reaching out and marketing to people. And that on its own, think is a dead end. The only way forward I see is actually like a ⁓ congruence of bringing together of those three things, which before this time has been seen as too much. Like, well, I’m just doing software, you know, like if I spread myself too thin, I’m going to do software and education and, you know, services, right?

That’s been the mentality, the classical tradition, traditional mentality is that that’s spreading yourself too thin. The way that I think of it, that’s the only way forward. And I think evidence of that being true, which I’ve seen happen since the end of last semester, OpenAI, for example, has really been taking on consulting. And this approach where you combine all of those things together,

which by the way consulting and services becomes much more scalable with AI so you’re not spreading yourself that thin to accomplish it. You could really provide real value for people by combining those three things. that’s what I think the answer is. ⁓ I hope I didn’t spread myself too thin with that answer.

Marlene Gebauer (21:55)
That is a fascinating answer and we’re going to have

to think about that one for a while.

Greg Lambert (22:01)
Yeah, well, and I had asked

if specifically if someone like Microsoft can come should come in and buy them, which I think may may actually make more sense than an open AI doing it because Microsoft’s already embedded into the law firms. so and yeah, so it was something I hadn’t even thought of before.

Marlene Gebauer (22:08)
Okay, well.

But if chat

GPT puts out something legal and pushes the other ones out, maybe getting that data would be useful. I don’t know.

Greg Lambert (22:35)
Yeah, that’s true.

gonna be interesting.

Tom Martin (22:39)
And

well, I realized I didn’t directly answer the question about opening eye buying. I do see that in the cards. You know, they’ve been in an extremely aggressive. They’ve been an extremely aggressive company in terms of taking up market share and this push into consulting. And I see it probably being part of their their prospectus and playbook to do that.

Marlene Gebauer (22:48)
Ha, Greg, he sees it in the cards,

Greg Lambert (22:50)
Ha

Marlene Gebauer (23:09)
I’m going to switch things up a little bit, so I wanna focus on LawDroid, Tom. ⁓

and you’ve been running weekly news and analysis and YouTube interviews. Super great stuff, super informational, really helpful. And this is under the Lodgerite Manifesto as the last week in Legal AI series. ⁓ So what are you seeing lately that, you know, from your work there that excites or alarms you? Maybe alarms you.

Tom Martin (23:28)
Thank you.

Well, there’s been, you know, like on my daily news that I put out, there’s a lot that is alarming me and I write about it, my takeaways on it. ⁓ It actually, I’m going to write an article that’s going to come out probably in a week or so that I’m calling a, know, ⁓ a Gen X tech progresses apology. ⁓ And the reason why I feel kind of compelled to write it is that I think, you know, being a Gen Xer growing up,

at that moment in time. Tech and you know, our 2D2 and like the future and everything was just so exciting and compelling and ⁓ a vision that you know, I’ve always hoped would come to reality. ⁓ But I think that’s been blinding to a certain extent because you know, I talked to my daughters who are 18 and 23.

Marlene Gebauer (24:30)
you

Tom Martin (24:43)
they’re much more skeptical about this stuff and worried not only about their job prospects, but about all of the information about themselves, personal information that could be made available to technology. And I think people, some people in my generation have been far too forgiving and open. And ⁓ I think there is a lot to be worried about. You look at, know, CEOs talking about, you know, AI first job. ⁓

policies, you know, if you can’t find an AI to do it, then maybe a human being. ⁓ People turning to AI for therapy and then, you know, being given shoddy advice from ⁓ AI and there’s just, there’s hundreds of examples of how it negatively impacts us that there’s a lot to be concerned about.

Marlene Gebauer (25:22)
you

Greg Lambert (25:37)
Yeah, and that was one of the things that let me focus in on the using AI as basically a therapist. mean, Sam Altman brought on specifically that issue and talked about it. And that seems to be something that they’re 100 % going in on that it’s not just therapy, but rather it’s also mental health issues, relationships.

you know, that this could be your new friend. And, you know, when we got Gen Zs now that, ⁓ yeah, I mean, that’s nothing new. But, you know, you’ve got a younger generation that is, when they do use it, they’re using it almost as this, like their own personal social.

Marlene Gebauer (26:14)
your new AI friend.

Tom Martin (26:16)
Yeah

Greg Lambert (26:32)
gathering or social interaction. And so I think it’s interesting to see the millennials and Gen Xers having this concept of, yeah, that’s pretty cool. And then looking at the younger generation, ⁓ and I’m a little scared at how they’re using it, but also the skepticism that… ⁓

Marlene Gebauer (26:58)
you

Greg Lambert (26:59)
that they’re having because this is going to directly affect them. it’s a weird dichotomy of how the younger generation and even the older generation are looking at these AI tools. ⁓

Tom Martin (27:16)
And I don’t mean to say that it’s all generational. mean, it all depends on like, you know, maybe your mental generation, ⁓ yeah, I but I agree with you. I mean, the younger generation is going to have to live with this. And I kind of feel, ⁓ you know, concerned about what we’re going to leave them.

Greg Lambert (27:26)
Yeah, because I still act like a teenager.

Yeah. So speaking of the younger generation, let’s look at your teaching responsibilities at Sulfic at the law school there. ⁓ You’ve been an adjunct professor there. So what questions are students bringing in now? ⁓

as they see these advancements in AI, is there anything that you didn’t expect?

Tom Martin (28:18)
Not really that I didn’t expect. I think they had a lot of great ⁓ questions about the limitations of the different models that they were using and found they found great ways of using it to their advantage. I think, you know, they all voiced a concern, you know, about job prospects post graduation. ⁓ I think, though, the timing for them for the class that I had this

last spring and that I’ll likely have, well I’m teaching again this coming spring. I think the timing for them is actually good because it’s this middle ground. We haven’t fully transitioned to this new way and certainly many different law firms are at various different levels of sophistication when it comes to AI. That kind of ⁓ arbitrage between different levels of AI ⁓

comfort gives them an opportunity because if they do have a background and understanding how it works and you know, I gave them essentially like a, an AI implementation plan that they could take to a law firm they go to work for. It gives them real value, you know, cause they could be that translator between worlds that a lot of employers are looking for right now. So they, you know, it actually is a big ⁓ plus I think for them to have that expertise.

Greg Lambert (29:48)
One of the things that, and I heard ⁓ right before the GPT-5 ⁓ show came out, ⁓ because it was this understanding that these reasoning models were going to now be the default, ⁓ but ⁓ I heard ⁓ someone that isn’t a lawyer ⁓ talk about ⁓ one of the great skill sets that users of this system ⁓ can have is a

Marlene Gebauer (30:01)
you

Greg Lambert (30:18)
understanding of the Socratic method. Because with these tools, ⁓ it’s not just a, let me put in a prompt and get the answer and then we’re done. That the same techniques that go into a Socratic method actually improve the output that the AI tools can do so that you ask it follow-up questions. How did you come to that ⁓ reasoning? What led you to…

choose this over this. ⁓ And I think that it’s one of those things where, I used to tease that, you know, if you thought the Socratic method in law school was finally going to go away, sorry, it’s probably going to stay here, you know, at least for the foreseeable future. ⁓ you see that as kind of the techniques that you use for learning?

Marlene Gebauer (31:06)
All of us inner grown. ⁓

Tom Martin (31:08)
No.

Greg Lambert (31:15)
in law school are actually going to be beneficial in this new era of AI.

Tom Martin (31:21)
So besides asking the right questions, I think it’s going to be a question of talent, really, and the ability to curate the information. Because only if you have a background in the domain of expertise will you know what questions to ask, will you know what makes sense to choose.

and to curate and choose the right things so that it’s valuable for other people. And I think that AI right now, it doesn’t have that talent for curation. ⁓ We ultimately can still bring that to the table.

Greg Lambert (31:59)
Well, can’t let you go before we talk about, you know, I think you’re, well, it’s third on our list, but it may be your number one passion is the work that you’re doing with the American Legal Technology Awards, and that’s coming up ⁓ in October there in Boston at Suffolk. ⁓ So tell us a little bit more and how that’s going.

Tom Martin (32:25)
Yeah, so it’s really exciting. mean, right now we’ve gotten just about 200 nominations submitted for the awards in 10 different categories. I know that ⁓ Cat Moon and Patrick Pallas, my partners in putting on the show, are excited to review everything and see…

all the nominations that have been put in. We have close to 30 judges that are so awesome, ⁓ world-class judges that are volunteering their time to judge these different nominees.

You know, October 15th at Suffolk University Law School in Boston, it’s going to be an amazing time. So if anybody’s going to be at the Clio cloud conference, please come to our awards gala. It is the, you know, it is law prom. It is the Oscars of legal tech as, as we like to call it. So, ⁓ know, please come on down.

Greg Lambert (33:21)
Do you have seat fillers so as people go to the bathroom, you have someone fill their seats?

Tom Martin (33:29)
and by the way, should mention it. AmericanLegalTechnology.com. If you could please go there, AmericanLegalTechnology.com. Check it out. We still have early bird tickets.

Marlene Gebauer (33:40)
Great. So Tom, we’re at the crystal ball question, and I know you’re familiar with this. So what do you see as the biggest change or challenge that the legal industry will be facing? We always say the next one to three years, I feel we should change this up to the next six months maybe. I’ll let you decide on the timeline.

This is really, really great or really worrisome that he’s thinking of so many things.

Greg Lambert (34:10)
It’s just smooth sailing. Yeah,

nothing could wrong.

Tom Martin (34:14)
One

So that’s a pretty tall order. I know that just figuring out where we fit in in this changed world, because it is changing daily. ⁓ And it feels like it is a sea change each time where like the underlying assumptions, the ground that we’re standing on changes underneath us. And we have to rethink ⁓ where North is every time. ⁓

And I think that, you know, where it’s leading is towards a completely new model of helping people. You know, it’s a new service model. It’s a new, is it a service education plus software model? As I, as I theorized earlier that that’s the way forward. ⁓ I don’t know. I don’t know for sure. Nobody knows. You know, we’re all grasping at straws here and whether or not we’re going to still be in the mix.

and what our economy is going to look like and do we have to like engage in a new political science, a new political philosophy to make this make sense for everyone and include everyone in hopefully the abundance that we’re going to create for ourselves and not exclude people from it. That’s my hope for the future.

Marlene Gebauer (35:39)
That is a great answer. And Tom Martin, thank you so, much for taking the time with us here on the Geek in Review.

Greg Lambert (35:41)
Yeah.

Tom Martin (35:49)
Thank you both for having me on. It’s always a pleasure to talk with you too.

Marlene Gebauer (35:54)
And of course, thanks to all of you, our listeners, for taking the time to listen to the Geek in Review podcast. If you enjoy the show, share it with a colleague. We’d love to hear from you, so reach out to us on LinkedIn or Blue Sky. ⁓

Greg Lambert (36:07)
And Tom,

for the listeners who want to learn more about what you’re doing with LawDroid and all the other adventures that you’re on, what’s the best place for them to go?

Tom Martin (36:19)
Thank you for that, Greg. The best place to follow me would be to go to LawDroidManifesto.com, LawDroidManifesto.com and you can sign up for my newsletter. It’s free. I’d love to have you.

Marlene Gebauer (36:34)
And as always, the music you hear is from Jerry David DeCicca Thank you, Jerry.

Greg Lambert (36:38)
Thanks, Jerry. ⁓ Thank you both.

Marlene Gebauer (36:41)
Yeah. Bye bye.

Tom Martin (36:42)
Thanks.