In this impromptu episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert reconnect after being on the road for a few weeks. They discuss their recent “Love and LegalTech” mini-series, which featured eight couples sharing their experiences working in the legal technology industry. The series provided insights into communication, work-life integration, and the passion for innovation shared by the guests. 

The conversation then shifts to a recent webinar by Toby Brown and Ian Wilson, where they discussed the potential impact of AI tools on law firm hours and profits. While the idea of AI reducing billable hours may seem controversial, the hosts agree that firms must adopt these tools to remain competitive. They also touch on the importance of aligning innovation with practice groups and the need for subject matter experts and people with strong interpersonal skills to drive change management.

Greg demonstrates an example of agentic AI using a tool called Crew AI. He sets up a task to search for information on a company called Take 5 Oil Change, using multiple AI agents to gather, synthesize, and report the findings. The process involves using SERPER, a Google search agent, an AI agent (Anthropic Claude), and a reporting agent. The output includes a log of the actions taken and a one-page report on the company, its leadership, and industry classification.

The hosts discuss the potential applications of agentic AI, such as quickly gathering information for client pitches or identifying legal issues. They also explore the possibility of running AI agents within secure cloud environments to address data privacy concerns. While the concept of agentic AI is still evolving, the hosts believe there is significant potential for these tools to streamline processes and enhance efficiency in the legal industry.

The episode concludes with a lighthearted mention of Greg’s AI-generated song created by UDIO about checking conflicts before going on vacation, showcasing the creative possibilities of AI tools in the legal profession.

Listen on mobile platforms:  ⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠ | ⁠⁠⁠YouTube⁠⁠

Contact Us: 

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert
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Music: ⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠


Marlene Gebauer 0:08
Welcome to The Geek in Review, podcast focused on innovative and creative ideas in the legal profession. I’m Marlene Gebauer,

Greg Lambert 0:14
And I’m Greg Lambert. And even though we swore we would never try to do this again, here we are, we’re going to try and do a kind of a fast catch up episode, because we actually haven’t been in the same room. In a while.

Marlene Gebauer 0:29
We’ve been on the road, both of us for, you know, either personal or professional reasons for quite some time.

Greg Lambert 0:35
Yeah. One of my professional reasons last week was to go to New York to catch a Astros/Yankees game, which was amazing, even though we lost that one

I thought we won. No, we lost that one, we won that we won the day after.

Marlene Gebauer 0:50
this was prior to the rosin issue.

Greg Lambert 0:53
yeah. Apparently, they still don’t like Altuve. They’re don’t know why.

Marlene Gebauer 1:00
He’s really the nicest person on the whole team.

Greg Lambert 1:03
But we wanted to catch up in do a couple of things, mainly was work on or just talk about our Love and LegalTech series. We had eight couples on I thought that I thought it was fantastic.

Marlene Gebauer 1:20
I really did. And I really liked your your compilation that you put out yesterday. So I think that was that was very nice. It was like I was I was telling you like, the more I see them, the more I just, like think how great it was.

Greg Lambert 1:32
Yeah, it was it was fun, because we had it was a wide variety of different couples. And but I mean, a lot of the stories kind of, you know, repeated.

Marlene Gebauer 1:44
there were a lot of similarities. That’s, you know, in terms of like, you know, it’s really necessary to communicate a lot and all the time and sort of the the work life integration, and how, you know, and it seemed to like a lot of them. It’s like, yeah, you know, we talk about work all the time. Some couples said, Okay, we try not to Yeah, and there are certain things they were lying. And well, I don’t I don’t some instances, I don’t think that I think it was true, particularly where they had other things to focus on. Yeah, so but you know, some did, but you know, some really didn’t, some are just like, you know, that’s like, this is the nicest thing to be able to have somebody in the same space and be able to talk to about, you know, the, the challenges and the good stuff, and have them really understand.

Greg Lambert 2:32
Yeah, it’s really nice. I mean, I’m I’m married to someone who’s also a librarian, even though they’re an elementary school librarian, but there are a lot of things where

Marlene Gebauer 2:40
I’m not gonna make any comments.

Greg Lambert 2:43
Yeah, but there’s a lot of code that we know, we know the language that’s involved in that. And I think a lot of our guests talked about that, that it was really nice, because you did not have to explain to your partner, the nitty gritty, nitty gritty details that were involved in what you’re doing. There was already a lot. There’s like a shorthand. I did, and you, you were not able to do this on. But the last one I did have is with Alexis, Haman and in and her husband, and I’m drawing a blank on his name all of a sudden, but there, and I put this into the little clip was, you know, just like, if, if I don’t want to talk about it, I’m just going to tell you that I owe Jeff. And he’s

Marlene Gebauer 3:32
just like, yeah, we’ll interact.

Greg Lambert 3:35
So for the audience, if you haven’t caught up on all of those, and I have looked at the stats, and I know some of you haven’t. It’s a great series. I think even if you’re if you think that doesn’t relate to you, I think it still does, it’s really about communication. And I don’t know if I’ve ever said this before, but I always like to say all problems are communication problems. And, you know, living with someone that used to work in the same industry, or some of them worked in the same company, when you’re around somebody 24/7 Working out those communication details is super super. And like

Marlene Gebauer 4:15
I said in that like it was a masterclass and communication. I mean, I was just amazed at how these guys were so mindful about, you know, sort of how they approach this. And it’s like, they’re not constantly like arguing all the time. And, you know, I also said in my LinkedIn posts, you know, it’s, it was really infectious when they’re talking to you about sort of their passion about what they do. You know, a lot of these folks that we talked to were, you know, startup people, and you know, you could really get that sense of energy. So that was pretty cool.

Greg Lambert 4:48
Yeah, yeah. All right. So let’s move on to the next segment. And actually, we just got finished watching a webinar with Toby Brown and Ian Wilson, Serviant and it so every everyone on the show if you don’t know Toby is a good friend of ours and full disclosure. Full disclosure doesn’t mean we always agree with him. But I think there was a lot of things that he talked about with AI tools and processes, eventually cutting into the our in the profits of, of law firms. I think it’s, I know, he loves the fact that it’s a little controversial saying that. But, you know, it doesn’t take a big leap of faith to think, well, if it’s only going to take me 10 minutes to do something that would normally take me 10 hours to do. And I’m billing by the hour, that’s going to be an issue with the way that we are set up as an industry and as a business.

Marlene Gebauer 5:56
And yet if you you know, as as they mentioned, you know, as Toby mentioned, like, if you don’t adopt it, somebody will somebody will and they’re, they’re gonna cut you out,

Greg Lambert 6:04
yeah, it’s a it’s gonna be interesting times. And I laugh because you and I had a presentation to the whole group, which is the Houston Association of law libraries back in April. And our presentation was we are now in the trough of disillusionment when it comes to AI. And lo and behold, Gartner comes out with an article last week. And they copied us. We are now in the trough of disillusionment in AI. So in that sounds bad when you when you think disillusionment that you know that that’s a bad thing. I think what we’re seeing is the rubber hitting the road. As far as AI tools, it’s no longer this. Wow, I think it can do this, this and this. And now we’re actually going okay, well, let’s do we’ve got our use cases. Now. Let’s actually put it in use .

Marlene Gebauer 6:59
Ans we are starting to production and like experimentation to the, you know, actual, you know, how do we implement this in a commercial way?

Greg Lambert 7:06
And so and I think in and speaking of Toby, he was in a Bloomberg article today, I believe, or yesterday, along with David Wang from some (Wilson) Sonsini, who just announced that they were implementing a contract review, AI tool that had what a 92% Accuracy Rating

Marlene Gebauer 7:32
AGENTIC process, I believe,

Greg Lambert 7:35
yeah. And hold on to that thought, yeah. If you don’t know what it agenic means. Basically, it’s the AI agents, which is kind of the the new buzz word when it comes to how you’re going to be able to leverage AI in multiple ways at once. So it’s really kind of interesting. And I’m going to actually show an example of that here in a little bit. But so what’s your thoughts on I mean, we can tie Toby’s presentation to some Sonsiniq announcement this week? Get thoughts on what you’re hearing?

Marlene Gebauer 8:20
Well, you know, I It’s, it was interesting. I was seeing seeing this because I do think this sort of agentic workflow idea is really interesting. And I spoke a little bit about this when I was at Ark National in Brooklyn. Week ago, two weeks ago. And it’s, you know, it is it is reported to be more accurate. And it’s, it can use other tools that are actually hard coded tools. So, you know, if you’re concerned about if you’re concerned about Gen AI touching your content, you know, there are ways that you can do it. So it doesn’t, for certain types of tasks. It was, I’m sorry, now, I’m blanking on his name. [Andrew Ng] is I think the last name and it was AI brain. He’s, yeah, he basically said this is this is basically agents are like the next big thing. You know, when you had the aha moment, during, when, when when Gen AI came out like this is going to be like that, because it exponentially makes it better.

Greg Lambert 9:36
And so I think before we get to the agents part of it, I do want to there was one thing that Toby mentioned right at the very end, that I think it was interesting because someone in the audience was from a personal injury. Yeah, yeah, that was interesting. And a lot of us don’t deal with personal injury lawyers and those For those style of firms, it’s different than than the big law. But Toby had mentioned, like billing structure, he was like, Hey, you’re, you know, thumbs up to you. Let’s, let’s keep your contingent fee. Yeah, go for it. Well, and that made me think, you know, one of the things that a lot of firms get a huge bump in revenue, year over year is contingency fee matters, and they tend not to take those because there’s a high risk, obviously, the amount of time that you spend, because

Marlene Gebauer 10:34
you couldn’t figure it out right, so much so easily before.

Greg Lambert 10:38
I’m wondering could there be, I mean, I could see splitting, maybe even splitting off a section of your litigators to focus on contingency fee cases, and being able to take more of those use the AI tools to really reduce the amount of time and even evaluate.

Marlene Gebauer 11:04
So because he’s litigation, investment companies, I mean, that’s what they’re doing in terms of like, okay, where’s the risk? And I think, you know, even with with using Gen AI, ai tools, I mean, you have, you have a greater capacity for trying to figure that out. And then, you know, just internally in firms, firms could do that. I was really interested about the staffing, because I think that’s been a big question. I’ve just seen a lot of kind of buzz about that, like, you know, what does that gonna look like, you know, you know, you know, we all be out of a job and, you know, on the business side, or what are the new jobs that are coming through? So I really appreciated kind of that conversation, particularly when, you know, Ian posed, well, you know, are firms really positioned to hire, you know, all of these engineers, and, you know, I think the answer was, was No, for a number of reasons, but one of which is that the top talent isn’t going to want to go to law firms, they’re going to want to go to tech companies.

Greg Lambert 12:03
yeah, well, and they want to go to tech companies, because they can get stock, well,

Marlene Gebauer 12:08
they can get stock, they, you know, there’s, again, there’s greater potential for making a lot of money. And if you kind of have that mindset, you know, if you have that entrepreneurial mindset, you know, that’s, that’s kind of how your, that’s kind of how you’re driven to sort of make things build things, and not get kind of stuck in the, you know, the quagmire of getting approvals and things like that.

Greg Lambert 12:34
No, in law firms??

Marlene Gebauer 12:38
That’s necessary. But yeah,

Greg Lambert 12:39
if salespeople think the sales cycle is really long, the development cycle on internally is even longer. So that’s going to be interesting. But yeah, you’re right to can law firms acquire the talent necessary.

Marlene Gebauer 12:54
And it was cool about like, there’s gonna be different types of talent. Yeah, there’s no subject matter

Greg Lambert 12:59
expert. Yes, I think that’s one of the things that, that they hit on a lot that I don’t necessarily think law firms are really

Marlene Gebauer 13:06
like, aligning, you know, I don’t know if you want to call it innovation, but you know, aligning innovation with practice, you know, practice groups, and kind of becoming some subject matter experts, as you said, right, you know, in that, that space,

Greg Lambert 13:18
and again, I think both of them hit on the topic that this this is, it is a technology, but it is it is not a technology issue, it is much more of a process. That’s why you’re going to see your subject matter experts getting involved. And I think the firm’s that see this as technology only are going to be just hamstrung,

Marlene Gebauer 13:44
you’re gonna need more people with more people skills as well. Because you’re going to have to have that empathy, you’re going to have to have that ability to, you know, work with people and kind of work with change management and get them you know, in using some of these tools that might be you know, on familiar with them. Yeah,

Greg Lambert 14:02
well, you’re gonna need people like in office space, or the guys like, people person. All right. Let me think, Oh, I’ve been playing. So a couple of cool tools. And I think you you I’ve sent you some examples of this. There is a tool called UDIO which is basically audio if you drop the A you on do U D I which makes a which makes music. It you give it a prompt, and it will create music for you. So I don’t know I can’t remember if I mentioned this on the podcast last year, but I oversee conflicts at my firm. And one of the things that I do before summer starts, is I send out a notice to the entire firm, that if you’re going on vacation, you should let the conflicts team know. Because if you don’t check conflicts for a certain period of time, you may get into trouble. If you’re on vacation, there’s a there’s a waiver process for that. And so last year, so it’s been 2023. I had AI create a song lyrics about what would happen if you didn’t check your conflicts. This year, I had actually write a song. And I think what I’ll do is, before we have Jerry, do the outro. Do the outro. I will put in a snippet of my of my song here. It’s, it is fantastic. The Grammy Award winning No, it’s, I’ve I’ve enjoyed playing with it. I think I heard it, it’s fun. It’s fun. Yeah, it’s fun. And for something that is something like

Marlene Gebauer 16:06
very dreary, and people like, you know, I don’t want to hear that. It’s like, you know, it’s it’s light hearted and you know, makes people makes people smile and makes it you know, a lot less tedious.

Greg Lambert 16:16
So I was really trying to do a put a little snippet of that song toward the end. But I did want to want to see some agents want to see some agents, agency. All right, well, I will try for the audio only people I will be very interesting thing I will I will break things down what we’re doing, if you’re watching this

Marlene Gebauer 16:40
on YouTube, or am I looking at my looking at the screen once

Greg Lambert 16:43
I’ll put this up on the screen. So I’m going to share my screen. So let’s see if I can do this without

Here we go. So I’m gonna, I’m going to share the entire screen, I think. There we go. All right. Now let’s make sure. So I can see it over here. It’s just yeah, you can see it up on the big screen. So here’s when we when we talk about AI agents, or you may hear it referred to as agentic AI. Really, what it means is that you are able to set up task and assign those tasks to different instances of AI. And in fact, it doesn’t even necessarily have to be AI. And some of it may be a local python script, it’s that’s running that may be processing text,

Marlene Gebauer 17:48
like the tool that I was talking about before it can use pythons to do things exactly.

Greg Lambert 17:53
And this has been one of those things that I’ve been saying for months, and that that AI is going to be a layer, or maybe in some cases, multiple layers within a bigger process. So it’s not a so it’s not just AI doing everything. So what I’ve set up and I did this is just kind of a side project using Python script is we’re going to do searching on a on a company. And I think I’m going to use Take 5 oil company, I got Jiffy Lube here. So let me change that. And the only reason I’m doing this is because as soon as we’re done here, I gotta go take one of my kid’s cars and go get the oil change. So I’m going to do, I’m going to search on the company name of Take 5 Oil Change, which is the official name of it. And what this tool does is there’s a tool in here called SERPER which you can connect to, and it will do Google searches. So I’m basically going to give it some instructions. It’s going to go out and search Google for information on Take 5 oil change. So it’s going to have multiple agents. The first agent is going to be a what we call a What did I call it here? I think we call it a well, I should have this ready, but basically just an information gather. This will be my Google searcher. So it’s gonna go out it’s gonna take the instructions that I give it go out and find as much information on Take 5 oil change, and then bring that information in is going to pass that off to an agent that will then synthesize that information based on the instructions that I give Have on things I’m looking for. And here really, I’m looking for essentially three things. I want to know information about the company itself, just general information. I want to know news and legal issues that it may be facing. And I want to find out information about its board of directors or leadership within the company. And once it does that, the those

Marlene Gebauer 20:27
are three different things. So you kind of have many processes going on. Doing that to compile it together. And there’s just a difference with with an agent,

Greg Lambert 20:35
right. And the way that I’m doing this one is essentially it’s going to be doing one task at a time, however, you can have it doing multiple tasks at the same time. For the AI agent, I’m going to be using Anthropic Claude, and I’m going to be using the version that is, it’s new, but it’s one of the lesser expensive ones, haiku. I used Opus before. And I’ll get into the pricing here in a second opus, it makes a big difference, it gathers a lot more information. But Haiku, for what I’m doing here, I want to be quick, I wanted to just come back with good information that I need, the output is going to be two things. One, it’s going to have a log of everything that it’s done, which was really cool. And then to I told it, just to write a standard report, which is basically a one pager that gives me the information on the company. If it finds information on the directors, it will give me information on them. And then I asked it also to give me the best guess on what it would be for next, or an SIC code, which is the industry code. So I’m literally going to run this right now. Which is like a big no, no, yeah,

Marlene Gebauer 22:01
let’s see.

Greg Lambert 22:03
So I ran it early. Or if you do the Opus One, it could take up to 10 minutes to run because it goes through this very thoroughly. With haiku, the Haiku is much lighter and faster. And I found that it actually does it in less than a minute. And what I’ll do is I’ll go through and explain looking at the logs, some of the things that it’s done, and where I think there’s some value in a process like this. So,

Marlene Gebauer 22:35
so question for you. Like, I know, agents can check their own work, you know, they can spell check, they can check facts now. Is that something that you have to build in? Or is that something that’s sort of natural, naturally part of the process?

Greg Lambert 22:49
Yeah, so the agents that I’m using, I should have put this up front, I’m using Crew AI. And so it’s done. So I think that took less than a minute. And so crew AI has instructions that you can build into the call. And that would be? Well, one thing that you don’t want it to do is get into a loop, right? Especially if you’re paying for it. So you can set it up so that if it if it attempts a task, say five times, it can you can tell it to stop, don’t don’t do more than five times that will help prevent the loop. You can also have it go back and forth between the agents and the agent that say the agent that is writing the report. If there’s not enough information, it could go back to the information gather and say, find me more information on this particular issue. And it’s doing this all on the fly. And it’s using the large language model to help it craft what it thinks is the good output. Now, you are the way that the human that’s developing us controls it is through the prompt. And so the prompt list exactly what it is that you’re looking for, what it should review, and what would happen if it needs to review that if it’s not complete. So you still have a lot of control over what the agent does. And I always suggest that the first times that you tried to do this, run it on the cheap models, because if you do get into a loop, it’s you know, 15 cents is a lot better than $15.

Marlene Gebauer 24:38
Not a lot of questions.

Greg Lambert 24:41
All right. So let me open up I’m going to open up the log files for this. And so you just saying so, here is an opening up an edge. And essentially it’s going to go through And I’ll walk through this for the people that are audio only here, essentially it’s given me the search query here, and it’s looking for Take 5 oil change. And then it’s going to summarize each one of those new webpages that it finds based on its Google search. So in a way, it’s almost like a RAG type system in that it’s taking the information, it’s summarizing it. I’ve got the links here in as well. So here you can see it’s looking at rocket reach, which is I think, a company kind of a company, information aggregator. Here’s the Take 5 franchise information that it’s gathering

Marlene Gebauer 25:51
citations. Yeah, just in a group? Yep.

Greg Lambert 25:54
Okay. And so here, you can see where it’s found. Here’s the output agent. So it’s Take 5 oil change, and it’s actually breaking down. Here’s the leadership, here’s the CEO, here’s the president. Here’s other key executives. So it’s gathering this information. Going through and again, this is doing step by step, it’s going back and forth. With the with the multiple agents, and each one having their own task, each one, either gathering information, synthesizing the information or writing a report,

Marlene Gebauer 26:32
have you found that it goes to different levels of websites to get its information? Or is it just sort of the the top level? And

Greg Lambert 26:41
you know, I haven’t dived in on on that. I’ll have to take a look at that. So here’s one of the things here’s where it’s like, okay, it’s it’s hit this exception is it’s telling the agents that all right, now’s the time for you to start compiling this information, and writing it. Now, I’m going to show you another trick that I that I do with the log files, but let me show you the actual report. And so go.

And I’ve looked at a few here. So take five, Intel, I’ve run this a couple of times. So here’s the most recent one. So again, I told it just to write a short report is saying take the title of the report is take five oil change driving convenience and quality in the quick lube sector. Take five oil changes a leading automotive maintenance franchise that has been servicing drivers for over 35 years, founded in 1980, for over 1000 locations. It’s a key player in the quick lube industry. And then it gives a little bit more information. The keeps now it did not. And maybe because I changed the script, it did give me the next code. I found that the higher dollar version of the LLM does a better job at identifying that one. So for example, this found that it as a general automotive repair, the the more expensive LLM actually found that it was oil change, which makes a huge difference. It can make a big difference in that. So again, it’s not perfect. I just want to show what the agents can do. But I did want to do this. So I’m going to take that log file. And let me go back. So here’s the log, I’m going to just copy the entire log file. And I’m going to go and for this one, I’m going to actually use Gemini, which is the Google’s tool. And I’m just going to say review the following log file for any potential legal issues for Take 5 oil change. I see if I can move that out of the way just for a second.

And then I’m just going to literally just paste the log in. The nice thing with Gemini is it has a large context window. So even though that was multiple pages, kind of documents, you can see it. So I’m going to run this. And so there you can see everything. So it’s saying the lock does not reveal any major legal issues, however, that they can gather from the log that there’s financial performance, customer satisfaction. And so potential areas of concern, I will say that I ran this using the Opus version, the more expensive one and it located about six different legal issues that it found. So there is output differences between the different models. And so your mileage may vary. So change it change your oil, every change your LLM every 10,000 miles, right. But it but there’s just a number of things that you can do with these tools. So So again, agents is just what are

Marlene Gebauer 31:02
you using this for? Like, what were you gonna what, what’s sort of the, a

Greg Lambert 31:07
lot of this, we were talking about pitches. So if we’re looking to pitch to a new to a company, that this can get us some very quick information. So I don’t think it’s as good as what you would get from Hoover’s or a cap Capital IQ, or one of the high dollar ones. But if you’re looking for something quick, you’re looking for something current, you don’t have a lot of time, if you get one of these, you popped company and you get the output, you know, at least you can get that first step out of the way, and identify some things very quickly. So well, you got, I

Marlene Gebauer 31:51
think it’s pretty cool. Um, you know, I’m, I’m very bullish on agents at the moment, having having learned more about them. And, you know, I, you know, I like the fact that this sort of does multiple things for you. I like the fact that it, I mean, this one doesn’t, but it can check its work, you know, because again, the you know, what are the the hang ups is the, you know, the consistency and the accuracy like that, that is always that just continues to be a problem with just using sort of straight LLM models. And also, the security now, you’re running this, you’re running this outside your firewall, right? Yeah. But I know you can run them inside your firewall.

Greg Lambert 32:36
Yes. So one of the things that that we that I have tested and I’m speaking as Greg Lambert not as the Chief Knowledge Officer my opinions are my own my opinions are my own is that you can you can run LLM open source LLM comes on a laptop, it can be extremely slow, depending on what your laptop is, where I’m where I’m seeing some potential, and that is probably and running them in a in a cloud, secure cloud environment. So if you’re in Azure, you’re in Amazon’s web services, and it’s secure. You know, for pennies an hour, you can run LLMs for use cases,

Marlene Gebauer 33:34
like yours. I mean, I’m guessing you could batch it to like me, since this is multi step. I’m guessing you could ask it to do multiple ones at the same time.

Greg Lambert 33:42
Yeah, I can totally see that. You could do that. Right now. I’ve just got this one set up to do one at a time, but it’s just more just for a sample of

Marlene Gebauer 33:52
change instructions. Yeah. Yeah. Very cool.

Greg Lambert 33:56
Very, you know, I think there’s a lot of potential. I know, there’s going to be a you know, there’s a lot of press out there on agentic AI, which even I have known what agents were. It just doesn’t sound right to me.

Marlene Gebauer 34:14
You know, it’s like when when you’re talking about it, like it’s actually you get tongue tied on it a little bit, too. It’s like, sometimes

Greg Lambert 34:20
AGENTIC. Yeah. Yeah. So all right. I think that’s,

Marlene Gebauer 34:28
that’s good. Great, great live session.

Greg Lambert 34:30
Yeah. Now Now let’s test you to see if you can do the outro. No.

Marlene Gebauer 34:36
Alright, let’s try it. Well, we don’t say thank you to the guest. So it’s like, thanks to you, our listeners for taking the time to listen to the podcast. If you enjoy the show, share it with a colleague. You can reach me at on LinkedIn, and you can reach you on LinkedIn.

Greg Lambert 34:54
LinkedIn is pretty much all we are and yeah,

Marlene Gebauer 34:56
lately I was like we you know, we were doing all the other ones and I’m like, Can I really don’t look hadn’t any more sorry. LinkedIn has it.

Greg Lambert 35:04
All right. And so, again, Marlene, thanks for this impromptu session. And the music

Marlene Gebauer 35:13
that and as always, the music you hear is from Jerry David DeCicca that we’re going to hear a little bit of music from Greg, a little bit. Thank you, Jerry.

Greg Lambert 35:21