Podcast Ep #123: Legal Ops, Legal Tech, & Litigation: How One Mindset Can Improve All Three with Justin McCallon

John: There are some surprising similarities between the mindset it takes to lead a legal ops transformation for a major telecommunications company, the approach you need to launch a successful legal tech business, and the tools you can use to better manage a legal matter overall.
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My guest today, Justin McCallon, has done all three, and I think his experience holds lessons for legal professionals facing workflow challenges in all kinds of situations.

You're listening to The Agile Attorney Podcast, powered by GreenLine. I'm John Grant, and it is my mission to help legal professionals of all kinds build practices that are profitable, sustainable, and scalable for themselves and the communities they serve. Ready to become a more Agile Attorney? Let's go.

A quick note. The concepts from today's episode should be useful to you no matter what kind of practice you're part of or what tools you use. If you'd like, stay tuned at the very end where I will briefly talk about how my software tool GreenLine supports the principles and practices from today's show.

Hey, everyone. Welcome back. So this week, I'm sitting down with Justin McCallon, the CEO of a company called StrongSuit, which is an AI tool built specifically for litigators. And I want to be upfront about something right from the top. Last week in episode 122, I spent the entire episode laying out a framework for thinking critically about the ROI of artificial intelligence tools in legal practice.

And I argued that most lawyers aren't fully accounting for the investment side of the ledger when we bring new tools into our practices. And I've had some great feedback about it, so if you haven't listened to that one, you should go check it out.

But now, the very next week, I'm giving a platform to someone who is actively selling an AI product to lawyers. And I think that's me being the AI cautious pragmatist role that I coined for myself last week. But as you'll hear, Justin has some real credibility around legal process improvement in some pretty complex situations, both before and now during the LLM AI era. I think you're going to get a lot from our conversation.

But let me also be clear, I am not a StrongSuit user. I can't vouch for its effectiveness. I will leave it to you all to decide whether you think you'd get a good return on any investment you might make from it. And fair warning that this is also the second episode in the past few weeks where I get into some nerdy lingo with a guest. In this case, Justin talks about DMAIC, which is a Lean Six Sigma initialism that stands for Define, Measure, Analyze, Improve, Control. It's a useful tool set that is common in a lot of enterprise level process improvement efforts.

But the main thing I hope you'll get from this interview is Justin's fundamentally Agile approach to his work, whether it's team and process improvement or product development. I think there are great lessons for all of us in his journey, especially lawyers who might be exploring productizing your own services in some way. All right, here's my conversation with Justin.

All right, welcome back, everyone. I am excited this week to bring on Justin McCallon, who is the CEO of a legal technology company called StrongSuit, although he's got a background that gives some really interesting context to why he's doing what he's doing today. And I hope we'll get into some of that. Justin, thanks for coming on the show.

Justin: Yeah, thanks for having me.

John: So give me a little bit about that background.

Justin: Yeah, yeah, thanks. So I started StrongSuit in 2023, about three years ago now. And prior to that, I had a interesting journey where I did a mix of transformation mixed with law and mixed with analytics. And so, obviously we have a lot in common and a lot of common interests. But I had spent a lot of time AT&T and before that, McKinsey, the consulting company. I was very focused on, how can we take a big, hard, kind of broad topic and be more efficient in it?

And so that might have been looking at when we ran legal transformation, I co-led that where we looked and tried to understand, what's a good framework to apply to make legal more effective at AT&T while spending less money and doing its job? Later on, I launched the first GenAI products at DirecTV, our subsidiary, and that combination of AI, especially GenAI, plus legal work, made me think, okay, this is the time to go. Time to start my own company. And I've always been fairly entrepreneurial and excited about the prospect.

John: Love it. Okay. So it's a great background. But when you talk about making legal more effective at AT&T, unpack that a little bit for me. So what specifically were the business drivers? And I'll say, my assumption from my experience working with some bigger legal teams and also working as in-house counsel for a while is that there's this interesting dynamic where I think businesses tend to look at legal as a cost center, right? We're definitely not revenue generating, but it's also a necessary part of the revenue generation process. So there's always a little bit of a love hate going on.

Justin: Yeah, and I think that the in-house attorneys tend to feel that and I think they want more and more to be seen less as a cost savor and more as driving meaningful value while reducing risk. And so for us, we always looked for, what are the kind of inputs and what are the outputs?

And the output is sort of the risk reduction, liability reduction, claims reduction, and just doing a good job of being a transactional leader to form ventures and deals in an effective way. And on the input side, they’re just thinking about, okay, what are all of the questions that go to legal? What are all the problems that go to legal and so forth? And then trying to think through, what's a good framework for the intermediate steps to understand, how can we be more effective?

We use one, I think you like where we're looking at people processes, technologies, trying to understand that with that framework, but then try to be very quantitative at each part of the analysis where we're trying to understand, okay, for people, how much are we spending inside counsel, outside counsel, what percent goes where, who handles what, breaking that down doing that double click on outside counsel. What are the biggest groups, why, and so forth.

And then trying to understand, okay, do we have the right efficiency set up, but also the right kind of internalization of the values to where a firm's disincentivized from billing us a ton and doing a mediocre job. How do we set up review systems? How do we set up some kind of gamification to where they're incentivized to be very effective counsel? There was a lot of that.

And then for the people side, what we really enjoyed the idea of, we would look and see, we have some very, very talented lawyers there with rich pedigrees and great backgrounds that were just very good. And when we talked with them, many of them were saying, hey, look, I don't really do as much practicing law as I used to. I become the person that project manages a second or third year at a big firm and we spend a ton of money on that lawyer.

And I've kind of lost the practice of law angle that I loved. And so what we wanted to see, are there ways and opportunities to be more effective to where we could bring some work in-house in a way that doesn't just drain the attorneys?

John: Yeah. So there's a lot to unpack in that. But part of it at its core, what I'm hearing is an ROI calculation in a way, right?

Justin: Absolutely. Yes.

John: It's basically saying, okay, we know that we have to invest, and whether you think of it as an investment or a cost center or whatever, you still want to get a return on that. And the sort of abstract nature of the return is what you said, in terms of risk reduction or certain amounts of opportunities that you can capitalize on that require use of the legal function.

If we were to get a little bit more granular though, because I think at least part of why I'm excited to have you on is you and I have used some frameworks and at risk of going alphabet soup, but my listeners are kind of used to it, right? You've worked within Lean and Lean Six Sigma and danced around Agile. So I'd love to hear you talk a little bit more, and you already talked about one of them, which is this idea of having inputs and outputs is something that I find a lot of lawyers don't think about as much. Right?

They recognize that it's happening once you point it out, but it's not necessarily obvious from the jump that's what they're doing. How did you approach that with legal teams and work with them in a way that helped them feel like you could operationalize a lot of the work without stifling those senior attorneys that have all this experience, are good at issue spotting, risk spotting, whatever, not feeling like you're putting too many constraints on them?

Justin: I felt like many attorneys I've met with are very academic and intelligent and kind of enjoy the idea of applying a framework that's well vetted. And so when you kind of explain the thought process behind it, explain the vision that you're going for, they usually really bought in and so and then they wanted to kind of push the frameworks more. So as an example, I was lucky. I worked for a leader that was very into DMAIC in Six Sigma. So defining the problem was that first step and trying to figure out, okay, why is it that we're spending so much for this result?

And then kind of unpacking that using analytics as part of the later steps to understand kind of the amount of lawyers maybe per case or per matter that we're looking at, trying to kind of dissect and understand the issues and then having a measurable way to solve the with a new structure generally worked really well and the attorneys were just very interested in saying, how can I contribute to this new vision for how law should be practiced? They found that a lot of fun.

John: Yeah. Well, it's interesting because I think for me at least, one of the challenges when you're introducing a framework like that is to say, hey, we're not necessarily saying you're doing it wrong. Here's this outcome that we're currently achieving and we're interested in it as a problem set to see if we can achieve it better, cheaper, faster, whatever.

But there can be an interesting inflection point and different lawyers, or I've run into it in different times where you do have to be a little bit careful to not have it come off as accusatory, to have it come off as opportunistic, not trying to shame anyone into thinking that their performance has been bad.

Justin: I definitely agree with that. And I mean, for me, what I noticed was, I mean, lawyers are very smart. They want to be empowered and they want to make an impact. And so framing it with that lens and truly trying to push that lens usually works very well. The more that you can empower your team while still giving them the tools to succeed, I think they really like that and they're going to gravitate toward frameworks that support that. And I think that can that can work just very well and it did for us.

John: So before we pivot, like, tell me a little bit about the outcome of that work. So like, what were you able to accomplish at AT&T and DirecTV using those approaches?

Justin: Yeah, we were very proud of this. I think the whole organization contributed a lot, and it was definitely a team effort. But at AT&T, this was a little after the Time Warner acquisition that we did. And we were able to save over 100 million dollars year over year while still empowering the lawyers, having no change in outcomes that we could tell that were negative.

A lot of the lawyers felt like they were getting better outcomes based on surveys. A very meaningful impact to our bottom line there and not just the cost savings, but also just the way that we manage cases, the way that we felt more integrated with the cases, the speed of which we were returning to the business an answer that was useful. Those sorts of things all mattered.

John: Yeah. Well, good. You just answered the next question I was going to ask is like the hard dollars aside, which is, of course, in a big company like that, that is always going to be a major consideration. But what are the other things you measured? And you just said one of them, which is the speed at which you were able to turn around answers or deliver value back to your internal clients.

Justin: Yeah, and we tried to look at payouts from like a liability perspective, the amount of like lawsuits that we were receiving from customers in different kinds of ways. Those sorts of analytics too were important. And we didn't see any kind of negative trend on any of those in the following years.

John: Well, so tell me then about your pivot into your current role in the software world. So, obviously, StrongSuit is big on AI. What is the problem set that StrongSuit is solving out in the world?

Justin: We're trying to help litigators go from end to end, solving, basically anything that you're going to face as a litigator more effectively and efficiently. But the very first problem that we solved was something that I faced as an attorney. So I was practicing in commercial bankruptcy. I was mostly transactional going through school, and then was thrown into this role that was basically half litigation.

And when I was doing that, nonstop, I would be researching just for days the right answers to this like outline we would build, and then inevitably, there would be a few areas where the partner would look at my work and say, okay, you obviously missed the key case here. Now I think you're a doofus or whatever. And then now, go find that, type of thing. And no associate wants to go through that.

And that was the first problem we aimed to solve where we try to very much go through and give you the confidence that if you're using our system, we're really going out, finding the best cases and giving you a case that's truly on point for every point that you're trying to make.

John: Got it. So it's a little bit of the you don't know what you don't know problem when you're diving into a new topic, a new issue, whatever. How does it work? Tell me about what specifically does it do to help people and where does it sort of plug into the litigator's workflow?

Justin: We're focused heavily on great legal research and drafting, but we do take you from the early stages of your case where you might be doing some kind of doc review or evidence gathering, putting together a timeline or a statement of facts and then using that to build great legal research and drafting where you're building that strong legal research outline that's detailed enough that has pin sites, all that kind of stuff, and then using that as the basis to build a great case.

And so a key pillar for us is that we believe law is highly connected, which I think is an easy statement to make. But your evidence gathering is very, very integrated with your research. And so you need a tool that's able to do both in an effective way and do well in both steps.

John: Yeah. Well, so it ties back to one of the sort of core tenets of Agile methodologies that I really like, which is to not look at your workflow so much as work, but see it as a series of knowledge improvement steps. And you really are trying to sort of take it from a, okay, I don't know what I don't know in the early going of a new matter and how do I intentionally and within a defined process improve what I know, improve my information, obviously to give me leverage so that I can win if that's the situation, but also being open to the idea that, hey, this thing is not going to go my way and figure out where your off ramp is if that's the right way to go too.

Justin: Absolutely. I think that's well said. And when we build, we're thinking with that kind of kind of multi-step workflow in mind and I think it's great for attorneys also to think of their practice that way. You're just going to be able to run a more effective practice and find out areas for improvement.

John: Yeah. Well, and again, I'm going to call out because I'm noticing some landmarks already along the way or some milestones in the process. And one of them is that you said is a solid research memo with pin sites. And that's an output, right? It's a deliverable. It's an interstitial deliverable. It doesn't necessarily have value in and of itself in the case, but it's a good landmark on the route to something that is going to build you value.

And I also think it's something that not all firms necessarily do in a consistent or even a routinized way. We know that we need to do research. We don't always think of that research as having a clear output. And so walk me through a little bit of your thinking.

And number one, tell me if I'm right or not, but if I am, walk me through your thinking in terms of, how are you helping litigators work through that milestoning process and making sure that they've got these sort of clear checkpoints where they can take a step back and assess and say, great, I can now call this phase complete based on what I've learned from this phase, I'm ready to embark on the journey for the next part of this thing.

Justin: I think that you're right. For us, let's say you've done the evidence gathering and you're ready to do research, we have an agentic system that has matter memory. And so you're starting to see some of this pop up, but anything that you're putting into your doc review or your timeline creation, we now can pull from that as we do research. And so if you have a contract that's being disputed, we might be able to pull in, okay, the waiver clause is very relevant to the litigation at hand now. That'll be that early stage part of it.

But now let's let's move to the research stage and talk about what we do. So we try to think through, what is a typical kind of flow for how information works in a firm when they're doing their research? And we try to build a corpus of knowledge and then use that to build a great outline, and then let you use that combination to build any kind of draft document that you would need.

And so if you think through it, you might pull in some follow-up questions where you have some general background, but you might want to pull in some more information that might be something you can find in the case to be more relevant. Then we try to find what are the causes of action that are relevant in your case, and then what statutes or other legal authorities might those align to.

And then we can start thinking through, okay, we want to frame the brief, memo, demand letter, whatever, with a good outline and good structure. And so we start trying to build out that structure for how we kind of see the case. And then we use all of that to say, okay, now we know kind of the arguments we want to make. We know the general direction we want to go. Let's kind of iteratively build a case outline where we have cases on point for each of the different parts of the outline.

So it might be a fair use case and then you have four subcomponents and we find cases on point for each of the subcomponents and maybe some tertiary issues below that. And then because we have all of that, it becomes much easier for us to build then a full draft of a brief or a memo or a complaint or whatever the case is.

John: Okay. And so then the other hallmark of Agile practice is that it is iterative in nature, right? And sometimes, you're going to maybe have to do, you're going to have a few facts and you're going to need to do a little bit of research. But then the outcome of that research is, hey, here's what you should build as a discovery plan, for example. And basically getting the new facts that either confirm or unconfirm the path that you think you're on in terms of achieving resolution in the case. How does StrongSuit approach that part of the process?

Justin: Great point. a couple of different ways. One is that we have the AI and the human iterate heavily. So we try to move away from just a pure pure based chatbot and move more toward an interactive platform that's more visual. And so we try to kind of take the workflow that you're building and have a step for each piece and have the AI synthesize a lot of under, the kind of background data and then have the lawyer then decide, okay, let me go this direction. Let me go that direction based on what they're seeing.

We'll usually surface some ideas, but then let the lawyer stay in the driver's seat. But then often you'll see too, when you build a cause of action and then look at the authorities, you might want to go back and say, okay, this authority doesn't really support that cause of action in my state specifically. Let me go back. And so we make it really easy to do that iterative approach.
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John: What are users saying about you?

Justin: We've been very happy with our customers. I would say in 2024, it was, this is a cool idea, but it's not there yet. In 2025, it was, okay, I see why this is useful. I get value. Now, I think we're seeing, okay, this is going to, this is already pretty revolutionary, and I can see the trajectory. And this is going to just change the way that we practice. And we'll have some major releases at the end of this month, the month of May, and I think throughout the year, you're going to see just an avalanche of change with these tools becoming increasingly more useful.

What tends to happen is you have moments where you add value to the point that it becomes actually useful, and then it becomes very useful because the AI can do a lot more than it could before and it replaces a lot of work. What I don't think is going to happen is the lawyers are going away anytime remotely soon. I think that they're going to just be empowered to do a lot more work per lawyer and your output's going to be very high if you learn to use these tools. And I do think also your own experience and kind of depth in your practice area really does become a multiplier if you can use the tools well.

John: Yeah. I love that. And part of it too is and I've been talking about this with a lot of people, that it's important and interesting that these technology tools, including AI-driven tools, can kind of be that force multiplier, right? That allows you to handle a higher volume. But it's also important that sustainability remain a part of it, right? Because with the wrong tools or even the right tools wrongly used, it's really easy to work yourself, you know, the AI brain fry has been a thing lately out in the media.

And I think it's very real that there are people that are using AI to actually generate even more work for themselves because they're not quite sure where they are. They don't have a right understanding of how to plug it into an existing workflow. They're kind of just throwing spaghetti at the wall. And then they find out they've got a lot of mess to clean up.

Justin: Definitely the case. And one thing that we've seen is that the lawyers that onboard with us, which we always very much want our customers to onboard. We very much encourage them to. They will often tell us, before I had done this, I was getting value, but there were some limitations. Now I see how it actually works together. And this makes a big difference. You really need to learn how to use the tools that you're using well and get some practice and get some feedback on it from the people that can help. I think that goes a long way.

John: Yeah. As someone that is also now starting a software company and we've been onboarding our own, you know, first early set of clients or customers, I should say, right? Changing my own mindset there. The onboarding process is really a key part of it. And as much as it is learning how to use the tool, a big part of it is having a different mental model for how the work can be done.

And just learning how to use the tool doesn't necessarily get you all the way in that mental model shift. But once you have that mental model shift, it really can open your eyes to a lot of different ways of working.

Justin: I think that's very insightful and very accurate. Something that we've tried to do earlier on was we would notice that people had a, or lawyers had a very specific way they wanted to use the platform and they just try to kind of ram that approach in, and then that was it. Then they'd forget about it and not use us for a while.

And so we've tried very hard to say, here's some other steps you can take in your case to be useful and ways that we can help. And once they start seeing that and building that kind of repetition, they start understanding, oh, and like that light bulb moment goes off and it's a lot more impactful what they can do.

John: Yeah. Well, and to tie it back to Lean and Agile and Six Sigma and DMAIC and all these functionalities, a lot of it is kind of rethinking the value stream map. It's like, okay, what is the end product you're trying to achieve and let's work backwards from there. And, oh, this thing that you've always done it this way, have you thought about or what would need to happen if or, you know, what could you accomplish if it worked this other way? And that's where the light bulbs start to come on, I think, at least in my experience.

Justin: I agree. I agree. I think that makes sense.

John: Well, so I feel like I would be, you know, we're still in this era of AI adoption where I can't have an AI executive without saying, okay, what about safety, security, hallucinations? I don't want to go down the whole laundry list, but obviously, there is the laundry list of objections that people have to using AI in their legal workflows. If you can give me just a couple of minutes on StrongSuit's answers to those objections, I think it's still helpful that, for everyone to sort of think through it because they are valid. They just need to be accounted for.

Justin: Exactly. As long as you're cognizant that hallucinations could be an issue and you're thinking about how to approach them, I think you're in good shape. Same thing with security, trust, all that. So going through a couple of the key ones, hallucinations were one that we were very passionate about early on. As far as I know, we had the very first anti-hallucination approach for legal research. And so what we were able to do even in 2023 was say, we've built our own case database. We had all the cases in the Bluebook citations.

And so if the AI model was going to surface a case that didn't exist based on our model, which we kind of used traditional programming to check with, we were able to say, don't show that case to the user. And we would have this intermediate step between what you feel like is ChatGPT and your output.

And so we would block anything that would hallucinate that way. We've become much more sophisticated in that where we're actually looking at the holdings of the case, ensuring that they're aligned to your case, having other agents review kind of the way that we're showing things. But having that series of steps helps a purpose-built tool be more effective than one of these tools like ChatGPT where, especially if you're misusing it, you do run the risk of being fined or otherwise.

On the trust side, there's a few different angles, but one of the great ways you can ensure that you're working with a good company is, are they SOC 2 Type 2 compliant and do they agree that none of your data is being used to train a model? And so I would always look for that in the companies that you work with. If you have that, the security and confidentiality perspective, I think you're doing your job.

John: Great. So it sounds like with your hallucination checking and all the rest, you're helping solve for one of the things that I've been on this riff around lately that part of why we're seeing all of these sanctions around hallucinations for lawyers is that lawyers are a little bit behind other parts of the business world in terms of the maturity of their quality assurance function.

And I don't mean that to sound like, oh, lawyers are doing QA wrong, but we haven't necessarily had to have a very sort of mature or programized quality assurance function because of the structure of firms and the multiple layers of review and things like that where I sometimes joke that the lawyer's version of quality assurance is, well, let me read it through a fifth time and make sure I didn't miss anything. But part of what I'm hearing is you've actually come up with some objective standards that you're doing quality assurance against before you're even showing information to the user.

Justin: That's right. And I would go on what you said there to say, I think it's helpful to really understand the basics of any tool that you're using, how it works, because then you'll be able to structure a tailored approach to how do you quality assure with that tool? You'll understand where will it not make a mistake or where will it make a mistake? You'd be wasting your time to check that all of our cases are real that we show you.

They will always be real and exist. But you might still want to read certain pieces of the case to ensure, okay, they said this was the holding, let me just make sure that this applies well to my case. And so what we try to do more and more of that every few months and try to make the process better and we can get more sophisticated over time. But it still is helpful to understand where the pitfalls could come in and what kinds of things you might want to do to assess the tool's failures.

John: Well, and just, I think, from the standpoint of good lawyering, right? When you cite cases in your legal documents, you're vouching for those cases, and you could be asked to vouch in person at any given moment, right? By the court or the judge. And it sure would be a tough situation to be having to prepare for a hearing or trial or whatever else and finally read through the cases and go, oh, shoot, that's not what I thought, right? So when I talk about workflow as a series of knowledge discovery steps, I mean that personally as well, right? You do need to be getting smarter. You do need to be doing the reading.

And I think what I'm hearing is you're not advocating offloading the actual thinking and analysis to your tool, right? The thinking and analysis still has to happen. And I think that's where a lot of lawyers have gotten into trouble. When they go and they get caught with these fake citations and the judge asks them to stand up and defend it, and they go, uh, it was, you know, that paralegal's fault or that co-counsel's fault or that other thing, because they just don't have another good answer for it. And the reality is they didn't read the case and they couldn't have, especially if it didn't exist.

Justin: Yeah, you should still read your cases. I do think it helps you prepare in a variety of ways. I think that's certainly right. As you're going through and using the tools also, I mean we really believe in you collaborating with the tool that you're using and not just the tool that you're using building everything for you and just kind of turning it in. I think you need to build in a collaborative way so that you'll learn, you'll find new ideas. You'll keep yourself sharp and be better for the next case. That needs to be part of the process.

John: And so I think maybe part of what I'm hearing is that your tool is a good way for lawyers to sort of improve their signal to noise ratio when they're building up their cases, right? So if you're having to approach research as a blank slate problem, then you're going to have to wade through a lot of cases that don't apply before you start zeroing in. And what I think I'm hearing Spellbook does is it does some of that early filtering for you. So by the time you do have to apply your finite time and attention, you're actually applying it on stuff that is likely to be useful as opposed to unlikely to be useful.

Justin: That's right. Yeah, yeah. And I mean, if you were using StrongSuit versus the older traditional form of case search, it is night and day the speed that will help you build the outline, but we'll help you structure your thoughts along the way. And having that structured approach, I think will prepare you well for trial or whatever step you're moving on to.

John: Love it. Well, so my other question just kind of hanging out there, who do you consider your competition to be?

Justin: I think it's getting interesting right now. Certainly the groups that are the horizontal players like Harvey and Legora are competitors. Other groups that do pure play legal research, it's somewhat of a, they could be competitors like your Westlaw or Lexis. We do try to make it to where you don't need to use those tools anymore.

We have a full case database, all 11 million US cases that are presidential are in there, and we have just a new way of operating that is much more AI forward than what the traditional players can offer. And so we do consider those legitimate competitors, but we also there are sometimes that we will integrate with them in some different ways too.

John: Well, so let me ask you a wrap up question, which is for litigators who are looking for a tool, are looking to start, you know, maybe have played with AI a little bit already. Maybe are using one of your competitor system, how would you encourage them to think about the evaluation process for figuring out what is the right tool for them and their practice?

Justin: What I would recommend is taking some time and putting together a fake or a sanitized case. So gather some fake files. You can use ChatGPT or whatever you like there to build a fake case, and then run it through the tools. Run it through to build a timeline or to spot issues or to ask legal questions that you think are interesting or and difficult and see which one comes up with the best research and the best case structure and then the best drafts.

I think that's a very a very easy way to have a very thorough test. When we demo and when anyone demos, it's always impressive. You should use the tools though and see, are they actually delivering the results that you expect?
J
ohn: Yeah. I was gonna say, it's what one of my biggest beefs is that I've seen some really amazing AI tool demos by people who are power users or who know exactly what the capabilities of the tool are and can make sure that they keep it inside the guardrails. And so, yeah, I totally agree. Kicking the tires on your own, taking it for a test drive is definitely an essential step before committing. Great. Well, Justin, thanks so much for coming on the show. It's been fascinating. I look forward to watching your tool and your team as you navigate this brave new world.

Justin: Thanks a lot for the time. I appreciate it.

John: Now that I've got my own legal tech startup in GreenLine, I really appreciate what Justin said about StrongSuit's evolution and improvement from user feedback. One of the most fun and satisfying things about GreenLine right now is how responsive we get to be to requests from our users. And while I think our tool is great today, I can also see how much better it is getting already. It's one of the advantages of being an early adopter. You don't just get the product, you help shape it.

And GreenLine is also a great way to help you make your AI ROI determination. The visual layout of your work means your bottlenecks kind of just jump off the screen, and our flow metrics help you understand the effect of your improvement efforts, with or without AI tools, on the time it takes your team to deliver quality work and create an outstanding client experience. I'd love to show you what we've got, so you can reach out to me at greenline.legal and hit that book a demo button, or just email me at john.grant@greenline.legal.

All right. That is it for this week. Thank you so much to Justin McCallon for joining me. If you'd like to learn more about StrongSuit or connect with Justin directly, I will put contact information and a link to the StrongSuit website in the show notes.

And if you haven't caught episode 122 yet, it's my first deep dive into what will be an occasional series around AI ROI for legal teams. Definitely go back and give it a listen. I think these two episodes work really well together.

As always, if you found today's episode useful or interesting, please share it with a colleague or friend who you think would benefit from a more Agile approach to their law practice. And if you have any questions or topics you would like to hear me discuss on the show, please shoot me an email at john.grant@greenline.legal.

As always, this podcast gets production support from the fantastic team at Digital Freedom Productions, and our theme music is “Hello” by Lunareh. Thanks for listening, and I will catch you again next week.