The Man Who Helped Make eDiscovery Make Sense ft. George Socha

Welcome to between the Briefs, a podcast by Steno. We're here to bring you practical tips, expert insights and real conversations about the pre trial process, court reporting and the legal technology shaping the future of litigation. I'm your host, Adrian SEO. And I'm your host, Joe Stephens. Whether you're an attorney, paralegal, or just curious about how technology is changing the legal industry, we've got something for you. Each episode will break down complex topics, share behind the scenes intel and talk to the people leading innovation in and out of the courtroom. So grab a coffee and let's get into what's happening between the briefs. Welcome to between the Briefs, your go to podcast for legal innovation. I'm Joe Stevens. And I'm Adrian Seha. Today we're joined by someone who has helped shape the very foundation of modern discovery and information governance, George Scioscha. George is senior Vice President of brand awareness at Reveal, co founder of the electronic discovery reference model, and one of the most recognized thought leaders in the global ediscovery space. Over the course of his career, George has advised corporations, law firms and governments on everything from information governance to cross border discovery, testified as an expert Witness more than 20 times, and spoken at over 200 engagements worldwide on the future of legal technology. George, welcome to the show. How are you doing today? I'm doing okay. I think you got slightly outdated information. I've lost track of the number of times I've testified. I think the conferences, webinars and the like have topped a thousand by now. But that's okay. That's incredible. That truly is incredible. Why don't you sort of give our audience, catch our audience up to speed on just a little bit about your story. How did you get to the spot that you're in and yeah, enlighten us that way so I'll see how short I can make it while still being somewhat comprehensive. But it all started in January of 1972 when I took my first computer programming course. My last computer programming course was January of 1973. I was in high school in those days and then I spent the rest of my high school time, way too much of it, writing useless programs on our computer. Got to college, had nothing to do with computers, got a broad liberal arts undergraduate education, which I would strongly recommend to everybody. Went off to become a Peace Corps volunteer in West Africa. Came back and saw that while I was gone, the world had changed and this thing called the IBM PC showed up, taught myself how to use that, wrote an inventory control system for my father's microscope repair Business and then headed off to law school where no one was using computers at the time because I'd been a Peace Corps volunteer and wanted to get my hands on active stuff as quickly as I could. Starting in my second year, I was involved in the Legal Aid Clinic. I was at Cornell, which has and has long had a strong tie with IBM. IBM donated a half dozen computers to the law school. The then dean said, we're never going to have use of a computer in a classroom now. He went on to co found the Legal Information Institute, or lii, which is a phenomenal resource out there. Clearly came to a different view of it later on. But he handed them over to the head of the Legal Aid clinic who handed them to me because he knew that I had a computer. I had bought a Macintosh the first week you could buy one before I started law school. And with those computers and then a half dozen more that IBM added to the list, I built a matter management system for the Legal Aid Clinic. That was before you could network PCs together, so all the data had to be moved from one PC to another with floppy disks. Got done with law school. Showed up at a law firm in Minnesota. They handed me a Dictaphone, a stack of yellow pads and number two pencils with the law firm's name on the pencils and said, see how technologically advanced we are. I thought, okay, what have I done? Tried my best to follow their approach. After a very short period of time, gave up. Brought my Mac into the office and started, I thought, becoming much more efficient using that. I had a steady stream of senior associates and junior partners come into my office, close the door, either remain standing or sit down and all deliver essentially the same message. Lose the computer. Real attorneys do not type. No one will ever take you seriously if you have a computer on your desk. The obvious I did not lose the computer. I never did become a partner at that firm. But I ended up in charge of all of information technology, all of library services, oversaw all of paralegal program as well, and built out first the litigation support and then the ediscovery capabilities there. That firm collapsed. 30 of us left to start a new law firm and I did a rinse and repeat with a new firm. Except BY Then, in 1996, every single attorney and paralegal in the firm had a laptop. Our first day we were working, we had no desks, but we had email addresses, a website, functioning computer system. Putting our laptops on cardboard boxes, we got motion papers out the door. Day one ediscovery through all of that was becoming bigger and bigger. And finally, after 16 years of trying to fit into the world of practicing lawyers, I reconciled myself to the reality that I really didn't belong there so much as somewhere else. So I fired myself as a partner at that firm and went on to create a one person eDiscovery consulting practice. First project I got was one to help size the Ediscovery market, figure out who the leading providers and a few other things along those lines. I needed some help to do that turned to someone I had worked with previously, Tom Geldman, who had been the IT director at I forget whether it was the largest or the second largest law firm in Minnesota, Dorsey and Whitney, and was by that point an independent consultant himself, brought him in to help me. We ended up publishing reports for I think six years or nine years, I forget. But fairly soon in the process I turned to Tom and said, I got another crazy idea for you, which is I think it would make sense to put together a project to try to deal with the number one issue we hear as we conduct this survey. And the issue was basically no one could agree on what eDiscovery was or what you should do about it. The people who collected data said that was the one true ediscovery. The people who provided the software folks used to review it said the provision of the Software was the one true eDiscovery. The people who provided the reviewers said that task was the one true eDiscovery. They could not all be right. So in 2005, in the spring of 2005, we pulled together, I think about 35 people and had a two day meeting in St. Paul to kick off that process. They were all volunteers. They nonetheless worked feverishly and on January 1st of 2006 we released both the EDRM framework and diagram as well as I Forget maybe about 5, 6, 800 pages of supporting materials. It was the right thing at the right place and the right time to address a need that others hadn't adequately addressed. I'd like to say we were brilliant, but I think timing and luck just as important. It looks like a workflow because it was based on. It's from a slide I prepared that started out as a simple PowerPoint as I tried years before to document what I did for eDiscovery. And it had exploded to something like, I don't know, 60 or 80 or whatever slides. And then I said this is ridiculous. And I cut it back and back and back for no particular purpose until I had it down to one slide. And that's what we used as the EDRM diagram. And it's modified it slightly, but it's essentially the same now as it was that day, January 1st of 2006. Wow. So it has stood the test of time, is still widely regarded and referenced. It's inked into everything. I'm curious, how was the adoption of this? Because I feel like this is almost a exact mirror of kind of what's happening now with AI Right. In terms of something new comes onto the board. It's like this is going to be the standard. And then I would love to know, what was the adoption like when you first came out with this model? Well, I think there's a key factor involved in the adoption I had, while I was practicing, needed for a case I was working on to get a technical standard. And I naively thought that standards are standard, and if it's standard, everyone's supposed to try to comply with it and therefore it should be available for people to use. I did not know that you had to by standards. So when we started edrm, I said, no way, no how are we going down that path? Whatever else we do, the diagram and the content we publish around it, that comes at no charge to anybody. Because I don't want someone, especially in a law firm context, to try to find as little as $1, which can be really hard to do, to be able to buy a copy of something to use, it's got to be freely available. Now, there's risk in giving out stuff for free because often people value it, but they pay for it. But on the flip side, I knew the challenges of finding even a dollar to pay for something like that. So we made it available at no charge. That was one thing. Second was even though the diagram itself came from work I had done by myself, everything wrapped around that diagram was the result of Those, I think, 35 people coming from law firms, from corporate legal departments, from service providers, from software providers, from defense side and from plaintiff side. So bringing in all those different perspectives. So it wasn't any one person's work, and it wasn't any one organization's work where people would look at it and say, oh, they're just trying to use this to sell something else. There had been some similar efforts earlier, one from a large accounting and advisory firm or a person within an accounting and advisory firm. But he tried to brand it with that company's name, and the very first people to throw shade on it were the other large accounting and advisory firms. That just wasn't going to fly. So we had Something grounded in experience that met a need that nothing at the time was meeting, that was available without the requirement that you pay money to get at it. And that reflected the input and work of people from a wide range of organizations and perspectives. And then, probably most importantly of all, we just got lucky. George, you had a line that you sort of buried in your intro that I was really interested in, where you have this technical background and obviously quite innovative as well. But you mentioned just casually, that you have this liberal arts background that you think is really important. Why is that? Very much my own perspective on this. But I think what you can learn through getting a liberal arts abroad, liberal arts undergraduate education that is very hard to learn if you have a technical education focused on a specific area, are really powerful critical thinking skills. The ability to, if you've got a good enough education, to stand in the shoes of others and look at things from their perspectives, not just from one direction. To be able to call on foundational elements that come from any number of disciplines. When I have turned to philosophy, sociology, economics, history and any number of other disciplines just on our work on edrm, to say nothing of the other things I've worked on. And if I had spent my entire undergraduate degree focused on technical skill, not that that's not important, if you want to be an engineer, you better learn how to be an engineer in the discipline where you want to be an engineer, because otherwise you're not going to bill it for anything of value. Just to pick one example. But there are a set of tools available that can be used, called on to really wrestle with problems that no one has wrestled with before. And that's so much of what people have to do in this industry. I'm curious, how have you seen eDiscovery change to what it was in the past, when you've developed this framework to now, right. Where we're seeing like a large amount of technology be embedded into the process more than ever before. Are you seeing a drastic change? How are you confronted fronting this? I think we're seeing more rapid and more extensive change now than we have ever seen. And in some ways we're going back to the beginning. So when I first got involved in eDiscovery, and that would have been, I don't know, because I wasn't paying attention somewhere between 1991 and 1993, there were very few people out there who even had an idea of what might be eDiscovery. It didn't have that name. It didn't have a name at the time. There Were, as of, say, 1987, as far as I know, two service providers that focused on eDiscovery. One EED Electronic Evidence Discovery out of Seattle, and another, IBIS Consulting out of Providence, Rhode Island. And they were it, as far as I know, there were no companies with software for this. There were no courses or certifications or manuals or people with expertise and experience that you could turn to. We were all just trying to figure out what to do about this. And in some ways, with generative AI and the agentic capabilities that are out there now, in some ways we are back at that same starting point again. I mean, it's different. Just as it's often said that history doesn't repeat itself, but it definitely can rhyme. You know, we're in a rhyming stage right now where it's at same type of open range of possibilities, very few things set and standardized, and no one quite sure where any of this is going over time. So, like, go from 91, 93 up through, say, 2003, before or whenever it was when ChatGPT hit the world and changed the world, as we got closer to the 2023, which is what I meant, date to period of time, as we got closer, maybe 2023, things became more standardized, they became more of a routine. There were fewer and fewer things that were unsurprising. Data sources kept changing, and we still haven't really, as an industry, figured out how to deal with things like chat messages or any of the various types of short messages out there. And we're still wrestling with what to do with content off mobile devices, but with what many people saw as the core data. We worked with eDiscovery. A lot of people were email, a lot of people were saying, it's done, there's nothing new, there will never be anything new. EDiscovery is old and boring and done. And let's move on to something else that's all topsy turvy and all over and back to the beginning again. Now, what does that mean to you, George? I mean, when you hear the rhyme of the past now sort of exist today, where does it take your mind? What do you think the challenges are? Are there things that scare you? Are there things that sort of excite you tremendously? I mean, how do you react to it? I don't know that there's ever been stuff that scares me in this so much as excites me in this. And what I see is a whole range of possibilities from several perspectives. The area of ediscovery that always has been of greatest interest to me is not necessarily the area that the ediscovery industry has focused on. The industry is focused, I think, primarily on how do you find stuff initially, preserve it, get it somewhere processes so you can search it and then search it for responsiveness or relevance. And it stops there. I did practice as a lawyer between student practice, two different law firms, just about 20 years. My greatest area of interest always has been and what can you do with this stuff once you got it? We are now seeing, with all of the capabilities that are emerging again with the generative AI and agentic possibilities that are out there, a whole array of opportunities for lawyers and those supporting them to work with the content that we get through the discovery process to more effectively either prosecute or defend the matter you're working on. If it's a lawsuit or more effectively conducting an investigation, it might mean doing it, but a far lower cost in a much compressed time frame, it might mean doing it with much greater depth than previously was achievable. It holds the possibility for much more consistent actions and results. It holds the possibility to allow people to get past so much of the drudgery that we've unavoidably had to do in ediscovery so that they can spend much more time doing things like figuring out what stories can I find in the data, what can I tell, and do it in an affordable way. I had a project I worked on many years ago where we had for then an enormous volume of data. And we had a situation. We were the defendants in the lawsuit, and the other side had a simple story to tell, but it didn't seem to quite match the information we had. Including it was very unusual. I got a court order that required them to turn over the entire contents of the server that ran their whole company. And they were a major company, they could hold back nothing, including privileged materials. They had to turn over everything. So we took all that data, the other data, we got through this very time consuming and expensive process and mapped out their story as basically a bell curve. And then we looked for places where the data available to us didn't match up with that curve. Especially we looked for spikes on either end of the curve with what we learned from that. Then we tried to figure out different stories that might be told in the data and came up with a story that had its own bell curve, but far fewer spikes off of there. For a variety of unfortunate reasons, we didn't actually end up using that story at trial and lost as a result. But the work we did was phenomenal. And we now are on the precipice, I think of being able to have that type of capability available for people even on routine matters. That was a million dollar project doing that five or so years ago. A million dollar project. You know, from all these stories and experiences that you've been telling us, I could tell you're a creator, right? You see processes and you want to create something new that helps make sense of what's going on. Are there any projects that you're currently working on that you're really excited to dig into? It could be with AI. AI or just in technology in general. The ones I'm most excited about that I'm working on, I can't tell you about. That is fair. That would not be a good thing for me to do. I can tell you that along with every other major ediscovery software provider, we have been working on first rolling out gen AI and then rolling out agentic capabilities also. I'll talk a little bit about what we have rolled out as opposed to what we're going to roll out because you know, I don't want all our competitors to hear what I'm working on. But one of the first thing we rolled out was a seemingly simple set of capabilities and we gave it a very simple name. We weren't the first to market with this, but I think when we rolled it out it was the most elegant version of that there we just called it Ask. It's baked right into the review platform and now Reveal has two review platforms. Reveal, which is largely for much larger and more complicated matters and Logical, which is almost a self service function and the capabilities available. And what do you do? You're in the platform, you hit a button, brings up a place where you can type in a question. So you ask a question, typically in about 25 seconds you get back a narrative answer with footnotes that shows you where it got the information it used to give you that answer so you can check its work. And as a lawyer I never want an answer without the ability to figure out where that answer came from. Just giving me the tool just gave me the answer. The answer would be worthless because it would not be grounded in anything I could point to because I have have the underlying stuff. When I am meeting with someone, say a witness, when I'm taking or defending a deposition or otherwise involved in the getting of testimony, when I'm putting together motion papers, when I'm appearing before a judge, I've got to be able to point to where this came from. To having all of that there in the system. Get your answer 25 seconds back. You can go back to it later. Others have access to it as well. You don't like the answer, reword your question, would it be lost 25 seconds of the system doing stuff, longer for you to figure out how to rephrase your question and baked right into the platform using only the data that's in there. So if it doesn't find the answer, it doesn't try to be kind to you and make up an answer to make you happy. It says, sorry, don't have an answer for you, you want to try again, which is really important. So grounded in the data, doesn't go elsewhere looking for data if it can't find an answer, doesn't make one up, tells you where it got the answer from, and lets you repeat the process as much as you need to in 25 seconds or so each time. Deceptively simple in what it does, but it's enormous power. When we do demos, we're stuck with having to use the Enron data like just about everybody else. And I could go on about why that's the case and why we still don't have anything else to replace it. But one of the things I can put in as an example is a question about who were the people who ran the company during whatever timeframe I choose, what were their positions and what were their responsibilities? And give that to me in a table form. If I were sitting down with that 1 million documents that I'm using for that demo and trying to do that with any traditional approach, I might spend months, I get my answer back in 25 seconds. And if it's not what I'm looking for, what have I lost? Almost nothing. And what have I gained? Well, I know that direction didn't work. Let's try something different. Let's try something different. It gives me the ability to pose questions to the data and get answers back in a much more powerful way than I could if I were talking with a person. The computer doesn't forget. It may not have the information in the first place, but it doesn't forget what it had. It's not going to color its answer to meet its objectives. It's just going to tell me what it finds. So that's one that I'm particularly pleased with. The second thing we rolled out is our answer to doc review, and I know there's several different versions out there. I think we've taken a different and, from my perspective, better approach, grounded in my experience answering over 10,000 individual requests for documents. If I had to calculate that for an expert project I worked on once, it's grounded in that experience. It's amazing. I think as a lawyer myself, using. One of the things that's always interesting to me about using AI is quite frankly, some of the questions that I get from other people who are a little bit skeptical is like getting some sense of assurance about how do we know it's surfaced. Everything you're talking about a tremendous swath of documentation, the data set is huge. The thing that you're asking is very specific or could be, doesn't always have to be. How do you account for that from just a user experience perspective? How do you let a user feel like, yes, it might be returning meaningful information to me, but how do I know it's returning all of the meaningful information to me? There's much more depth to that question than might appear on the surface as well. Because you think back to what you've done as a lawyer. When did you ever actually know for certainty that you found all of anything but the simplest case? I suspect never. I never did. I had no client that was going to pay the money that would arrive at that assurance and no court that was going to let me drag a case on long enough to do that. And then if you look at civil. We'll stick with federal court. Civil matters in federal court. That's not what the rules require. They don't require you to achieve perfection. They require you just to make a good solid effort. And if you look at the rules of professional responsibility, whatever the right name for them is, it's the same thing. You're not expected to deliver perfection. Because if nothing else, perfection is way too expensive and time consuming. And you can never get back to Rule 1. If you tried to do that, you'd never get the just speedy, et cetera in there because it would take you forever. So I don't think the right objective ought to be find all of it. The right objective, I think should be find enough of it so that you have a reasonable basis for taking the next step. And one of the practices I developed, and since I'm never going to prepare a set of responses to answers to interrogatories or set of responses to requests for production of documents, again, I can say this for sure. I never once had this strategy fail me. It's pretty good. It took time to develop it, but I would get a set use set of document requests. Of course, I prepared the written responses that I have to put in the objections I have to. But in that document I'd have a preface, and in the COVID letter I would repeat myself. And in essence, what I would say is, I'm doing all the things that the rules require me to do. Now let me tell you what I'm really doing. What I have done is gone through your request and tried my best to identify those documents I think you are asking for. And I'm giving those documents to you unless I need to hold them back because of privilege or something like that, as well as the documents I intend to use. Even if you didn't ask for them, look at those documents. If you think there's something I did not give you, let me know. I'll try to give that to you. I might not have it. I might have it and not be in a position to give it to you, but I'll try. How can someone challenge that in court? I never lost that argument. I got deposed twice over that argument in the same case. Initially it was a telephone deposition. The case was based in New York. I was in Minnesota. And then the judge, at the urging of the plaintiffs, required me to fly to New York for a deposition in the presence of the special master, or rather it's a special master required. And I had to go out and there was a full day set aside before lunch. She stopped the proceedings and told the plaintiff's lawyer he needed to apologize on the record to me. So, you know, it never failed me. And I think it's because really it's not about all and every. It's about how much do you need to prosecute or defend your case. And you're going to have to stop short of all or everything. Almost always. The technology is getting better and better at letting us find enough of what we need to go to the next step. There's my long answer to your short question. Yeah, it's a really good clarification, honestly, and it provides context. I would love to know from you what is a big misconception people have about ediscovery or maybe when you've seen that even established lawyers are like this big misconception. Well, the number one preconception, I think it's still out there. It certainly was there when I was practicing and I ran into it a fair amount as an expert witness as well. Is this discovery stuff is just a waste of time and money. What do you do in a lawsuit? There are two things you focus on, the law and the facts, because you have to combine them together in order to reach an outcome. Discovery is what gets you the facts. If you don't have the facts and just the law, you're probably not going to go anywhere. And if you have the facts but no law, that's not going to help you either. You've got to be able to put the two together. And if you do discovery well, you're much better placed to do that. And if you do it poorly, good luck to you. So I think that's one of the biggest misconceptions. This is not really going to help you. Not exactly a misconception, but a challenge in many ways is if you as a lawyer in a law firm focus on discovery, especially ediscovery, your career is going to dead end. You're not going to make partner, you're not going to get clients, which means you're not going to make partner or stay partner. That should be something, a concept that we can sign to the dustbin of history. I know folks hitting up ediscovery practices in major law firms who are responsible for more revenue coming into the door in their firms than all but a handful of partners. So who's most important to the law firm then? You know, revenue is king. Right. And again, how do you build a case if you don't have the facts? George every platform now claims its own AI. And so I'm from your perspective, how much of it is there real differentiation versus sort of foundational models behind different logos? So the answer now is completely different from the answer from say four years ago. And we're pretty much all working with the same foundational models. Now there's going to be a question of to what extent people can build their own small language models or even medium sized language models, build them and then maintain them, which is a big problem, versus make use of the large language models. But more and more I think it's realistically, Even if you $500 million over a five year period of time, are you going to be able to build and maintain for the next 20 years the large language model you need? Skeptical I think we're starting with essentially the same array of foundational models, large language models, all of us. And it's a question of then what you build on top of those and what sort of capabilities you put in there, how you make the pieces work together, how well you ground what you're doing in the needs of the people working with them. One of the things that helps for me is that I do have both the grounding of all those years as a practicing lawyer and then the grounding of all those additional years As a consulting expert witness and consulting expert and then testifying expert witness, which gives me a much broader perspective than I ever could have when I was just working in a law firm. So having that type of grounding to be able to say, okay, this is what people want, I mean, I'm working on right now roughly 20 different pathways to build out additional capabilities for practicing lawyers. That is now a thing that can be done when you marry together those foundational models, the agentic capabilities, the generative capabilities, and the access to the discovery data. So we're not talking about what you can do with just 10,000 files, but what you can do with 10 million files. That's the exciting area for me. That's, I think, an area of enormous possibility. And if we are, as an industry, successful with that, ultimately, I hope we can get to the area that practically from day one of law school, at least, some folks were telling me, you're not supposed to think about which is better delivery of justice, which is what I've been trying to do all the 40 years since I got out of law school, for nearly 40 years, 39 years, I think. Do you think that AI is allowing better access to justice? Not yet, but I think it holds out the possibility. Will we end up going there? I would like to think so. At the same time, I know there are all sorts of reasons why that might not happen. So I hold hope that now that, you know, I want to think we get there. I hope we get there. I don't know whether we will. Where's that skepticism? I mean, I hear you, too. I teach. I'm very firmly sort of entrenched in the access to justice side of. I mean, I run a public defender office, so there is a tremendous amount of work that could be done in that area. Where do you see 40 years as a practicing lawyer and expert witness? Time spent people in all sorts of different situations hearing what the folks who build the tools and the services have talked about. Meeting with the clients. Not so much when they were my law firm clients. I got much less insight out of my clients then than when they were my consulting clients or when I was working at an expert project. And they needed to make sure they came clean with me because I was the only thing between them and a really bad situation, which is its own interesting set of juggling, because you gotta be independent. And I learned that as a testifying expert when I got to the point where people were taking on my report, deposing me or questioning me at a hearing, those people had one job and one job only destroy my entire career. If the case goes south on a practicing lawyer, you can explain it away in any number of ways. Your testimony goes south. If it goes south in a really big way, you got to go do something else. Well, George, we always ask this question at the end of our conversation, and that is, what is your hottest take on the industry right now? I'd say my hottest take on the industry right now. It's hottest place that I can remember ever seeing. I think, one, because of the new technologies, so many possibilities. Two, because unlike any time before, every time until now, the technologists among us have been trying to convince lawyers to use something they have no experience with. Who hasn't used ChatGPT or something similar to it? Everybody has used something like that. So now the lawyers come to the technologists and say, I want to do this. And the technologists are going to, let's see if we can catch up with you. So that's a whole new dynamic. So the level of interest all the way around is higher than it's ever been. The range of possibilities are greater than they ever have been. So if you've used those as a, you know how cold it is that no one cares, nothing can be done. How hot is it on a scale of 1 to 10? We're probably at like a 15. All right, well, completely agree. I can see where you're coming from. I do think we're in the hottest take hottest time for technology and the way things are evolving. And I just want to thank you so much for joining us here today. This has been an incredible conversation. George, thank you, Adrian. Jo, thank you very much. With that. That's a wrap on today's episode of between the Briefs, as Adrian said, a big thank you to George Socia for joining us and sharing his perspective here today. Adrian, do you have any final thoughts before we wrap this one up? No. Thank you for joining us, George. And for all those listening, be sure to subscribe so you don't miss future episodes. Thanks for listening. Stay curious, stay inspired, and we'll see you next time. Up next on between the Briefs. One of the biggest mistakes that I see is underestimating fear. People won't say, I'm afraid that this is going to make me less relevant, or they say I'm too busy or the tools are not ready or we need more guidance. And sometimes that's real. But that's the language people are using when they don't feel safe to use that tool. So it's really getting those signals very early on to kind of work through those changes within an organization. Stay tuned for the full interview coming to you soon. Between the Briefs is brought to you by Steno. To find out more about Steno and how we combine exceptional court reporting and litigation support services to deliver a superior litigation experience, visit steno.com that's S-T-E-N o.com and then make sure to search for between the Briefs in Apple Podcasts, Spotify, or anywhere else you get your podcasts. And click subscribe so you don't miss any future episodes. On behalf of the team here at Steno, thanks for listening.