Jeff Breunsbach: All right, welcome back to another episode of the Chief Customer Officer Podcast. this is coming out to you on Thursday, October eighth. Jay, how's it going? Jay Nathan: Going good, man. you ready to travel up to New Jersey? The first this is actually the first time in my life that I've intentionally gone to New Jersey for anything. I think. I can't remember having gone to New Jersey for a business meeting prior to this week. we've New York. Yeah. Yeah. Exactly. So it'll be interesting. Jeff Breunsbach: Always New York. You're usually New York, not New Jersey. Yeah. there's some there's some headquarters I've had to go to in New Jersey. but that's that's a funny anecdote. that you have. Jay Nathan: Ha ha ha. Jeff Breunsbach: I just got back from Portugal, which Jay Nathan: Yeah, are you are you over your jet lag yet? Are you you caught up? Jeff Breunsbach: yeah, I'd say so. I on the way back, I just stayed awake all the way up until like midnight East Coast time. and seemed to have kicked it pretty quickly. So it was it was, you know, relatively easy. but yeah, it was a good time. Just, you know, long long travel there and back. But our team got to do it we do a once a year off site. And so we got to bring our whole team there and you know, it's one of the perks of I guess not paying for an office is you can do some of these things. And so you know, we worked for about half the day, for about three or four days, and then we got to just hang out and go do activities with each other for the other half of the day. So the one thing we all walked away with is there is something different. Everyone can't pinpoint it, you know, I think everybody says the same thing. It's like the cliche now, but it's like sometimes there's just nothing better than like in person time. And I think you know, the little jokes, the little like learning about somebody, side conversations, just you just get so much more comfortable with people. And I think like we're such a Slack-based team. and also we're we're in different time zones. So like not all of us are always in the same calls or working on the same things. And so you know, being able to kind of get a glimpse into other people's worlds are pretty interesting. and then there's one thing that I walked away with that I was pretty excited about too. We got to do a who our customers are. we spent a f a full half day on that and I think we've probably said this, or maybe you've said this to me again. this is years ago when we were running customer imperative or doing something along those lines, where there is like as a as a company grows, there's just this natural, almost like ebb and flow where hey, we want the engineering team and the product teams to be kind of like as effective as possible. And to us, that means kind of like filtering things from the customers, right? Like almost like, okay, we need to we need to kind of keep them over here. In a way from like customer requests or custom things that we want to build, you know, we want we we gotta keep them kind of focused. and you know, I think like that half day of just talking about our customers, like our head of engineering, you know, came over and kind of said, those are some of the best things because engineering now, like the engineering team has a a better glimpse of, okay, here's some of things that we're doing with customers and is that intended, right? Do we intend to build it that way? Is that the right way it should be working? Do we really want our internal teams doing this kind of work? Do we really you know, do we want our external customers doing this kind of work? Like, I don't know. It just kind of illuminated to me again that like I deal with customers and you know, kind of on the front lines every single day with our team. And I get to s hear the hear and see these stories all the time. And then again, just kind of presenting that back to our entire organization, not not only engineering, but you know, product teams, our operations teams, some of our executive team, our HR partners, like. You know, it's just a a good I guess, I guess a good reminder that as much as you think people know about your customers, they they largely don't know a lot. And and Jay Nathan: They don't. Yeah. Jeff Breunsbach: like, you know, even just sharing little tidbits, like, you know, for this quarter, we're we're doing a big focus on, you know, kind of building and investing in our customers. And I think the engineering team and our product teams kind of walked away with like very things of varying degrees from like, hey, I could go build this in a day and and like it could help, you know, unblock something or like. Hey, we could go redo this entire experience and you know, it would take us like a quarter long or something. So there's kind of everything in between, which was fun. Jay Nathan: So what the the I'd like to dig into that for a second because I think when you think, you know, this custom this podcast is called the Chief Customer Officer Podcast. When you think about that role, one of the key roles in my mind of a chief customer officer is to make sure that obviously you're driving the the revenue of the business, right? Making sure you're retaining it and expanding it wherever you possibly can. But to be able to do that, you need the whole organization rowing in the same direction. Consistently. So you don't want to wait a year again until that kind of information is surfaced. So my question for you is how are you going to operationalize those insights for the team without beating them overhead over the head with it? Because you'd also don't want to be the CCO. And I know that's not a technical title, but that's what you're acting as, right? You don't want to beat people over the head with it, like, see, I'm telling you again, this is what the customers want. But like, Jeff Breunsbach: Yeah. Jay Nathan: how do you keep Like what are some ways that you're gonna you're gonna keep that top of mind throughout the next year? Jeff Breunsbach: Yeah, so I think there's two things that I walked away with. one is a bit more tactical, which is it feels like we don't follow a consistent process around how do we document some of these learnings and things from customers in a way that our product engineering teams could then go like react to, right? And I'm I'm thinking again, like a simple thing of like, hey, customer mentioned I don't know, this nagging thing. It's not really a bug, maybe it's a feature request. How do I actually just take that fathom call, link it into a linear ticket, and then just kind of categorize it and put it into the right area? so that like it can be worked, that it can be like thought of as as a part of our our roadmap, right? Like I think some of some of that just isn't like a a durable process that we've essentially like rallied around. And so I think like that's a tactical thing that like to me, okay, how do we very simply just make sure that that's happening? and even could I make that easier for my team where like At the end of the day, can I just summarize all the fathom calls and find the little nuggets and then just let my team kind of like push a button that says yes, go create a linear ticket no, this isn't really one, and kind of give them the human in the loop. so like that's like one tactical thing. And then I think another thing is just, you know, we we have an all hands every other week. and I think we've kind of struggled with like shifting what that looks like and you know, trying to serve kind of too many. different things about like, okay, you know, it should have this section and these slides. And, you know, it kind of grows and then we shrink it and it grows and we shrink it and like we kind of go through that cycle. And I think you know, what I guess like to me, how can we use the all hands to consistently communicate the things that are that are important to the business? And so, you know, kind of what are our goals? How are we tracking towards those is clearly one. And maybe like who are our customers is the second, right? Like how is that evolving? What are changes that we're seeing? what are consistent problems that we're seeing, you know, challenges that our customers are asking about, but there's probably some way that we could just again kind of formalize that in in that way. So I could communicate it, or even our teams could communicate it through some stories, I think in more consistent ways. And so I think that's kind of the second is just how do we use some of the rituals that we already have? And like, like you said, not necessarily beating the same thing over the head, but like, how do we how do we find the right things to be communicating? how do we kind of like bubble up or surface some of the right things in those types of settings. Jay Nathan: Yeah, attention is finite even within the the company, right? So it's you really have to to work hard to smart brevity comes to mind, the book that Jeff Breunsbach: Yeah. Jay Nathan: I always talk about. Like you really have to work hard to to surface the right information at the right time. do you ever think do you all ever bring customers into your all hands meeting as part of like the storytelling of, hey, here's an actual live person that's using our product and trying to get value out of it? Jeff Breunsbach: here and there, but not enough, probably. Like it and I think you know, like one thing I did again, I think this is kind of like learning, you know, is like, I I have a channel that's called customer quotes and it just I run an automation with Claude Cloud or Claude Code in the cloud and it runs through our fathom and then it it basically marries up what are our customers both positive and negative, what are some sentiments that our customers are sharing with us about the product? But that to me kind of screams to this idea of like of like you're talking about where it's like attention is is finite, where like sure, I I see people go into the channel and every so often somebody comments or clicks, right? But it's one of those things that's like, well, it's always there. I can always I can always go look at it if I need to, versus is it really driving you know, in action? And so I you know, another thing I walked away with was if I was like, do I think that that's the right thing to do in terms of like an automation? I think the answer is probably yes, right? Like we should be using tools to kind of summarize, automate some of these these insights, but maybe the delivery is wrong, right? I'm delivering it every single day. It's probably five to ten quotes. It's kind of all over the place. And, you know, does that turn into do I record something once or twice a week that's a three-minute loom that talks about these things, brings them off the page? Is that a deliver different delivery mechanism that somebody might watch? Or do I instead of doing five to ten quotes a day, Do I try to look for more impact? So let's summarize over the entire week. And how can I then categorize? Hey, here's 10 customers who said this and three customers who said this, and like start to look at impact that way. So I think there's some other like kind of small tactical things that you could do with like a channel like that to make it more impactful. Again, I kind of started it and I I like to look at it just because I want to have a pulse on certain things that customers are are happy and sad about. So I read it every morning, but it's like, does it drive action? No. Does it is it really doing anything for it? It's context building for me, but it's not really. there isn't, I guess, like the large benefit for the product or engineering teams that like it probably could be getting out of it, which is like you s I think like, okay, where's the more high impact stuff? how do I do less and get more specific and get like a little bit more granular? How do I engage more people around that? So, yeah, I think the attention is finite is a good good example. Jay Nathan: And I think there what you're describing, there are there are two methods, right? There's the there's the pull method, meaning I'm putting the information out there. Anybody can go grab it anytime and be sort of part of the constant feed, which back to the attention issue, you know, like the majority of the organization is not going to go read that channel, right? I I would guess. I'm sure you could get statistics in Slack to tell you whether or not people are using that channel or not. It'd be interesting to see, right? Jeff Breunsbach: Yeah. Yeah. Jay Nathan: but then there's these push things like the all hands meeting. one more idea. And I think you and I have done this before. I've done it at multiple companies. And I was inspired to do this by my product leader, Jenna Eggers, at, you know, when she came to Blackbot and I was in product management there for three years under her. But we actually pulled engineers onto calls. There was a shadowing rotation, both as part of the design triads for the product itself. And then we've also done when I was at People Matter, we did, you know, we had a rotation where executives would shadow support for an hour a quarter or sorry, a day a quarter. engineering folks would shadow support. We we had a a defined program that our support leader ran, and he pulled people in so they could actually hear real things that that customers were calling in about. Most of it was login issues in that company. But we did some things to solve some of those problems as a result of some of those calls. And then I think the third thing in the push model, meaning like we're we're actually pushing people into the information flow that we're creating, Jeff Breunsbach: Yeah. Jay Nathan: is like how can we use this information operationally in our prioritization and in our our executive team meeting and like how in our product planning meetings and our retention, you know, save kind of meetings that we're having, not save meetings, but Our retention forecast meetings, like where is this stuff all coming together? And I I I'll tell you about this book I'm reading in a little while. It's pretty interesting. But the the what hit me this week is I was just sort of thinking about like how does work change with all this AI componentry? I I still feel like it's the tail wagging the dog, it's a technology. Yeah, we're just Pushing technology here. That's all AI is. This is new tech, right? And it's still missing the point because at the end of the day, you know, things have to work end to end in a company. And not everybody's on the same page about what the technology is gonna do and how you you we could have we had robots and factories, which comes back to this book I'm reading, for for decades and decades, but it didn't solve the throughput and productivity problems that the the factory had, right? The robots Jeff Breunsbach: Yeah. Jay Nathan: weren't the answer alone. It was it was a much bigger kind of thing. But so I got to thinking about that. And how how AI is sort of changing all this is that, you know, it's lowering the barriers from the data. We have all these data silos today. Maybe it's the Slack channel. Maybe it's, you know, the data being collected through the product. Only certain people have access to it. But, you know, how do we sort of tear down all of that and use these tools to level the playing field so that everybody understands what's happening at the same time, but there's still human dependency, right? On the push or the pull. Jeff Breunsbach: The so a couple things that stand out. One, we did the same the support rotation. we set that up last week. So Jay Nathan: nice. Jeff Breunsbach: nearly everybody in the company went through at least an hour or two of a support rotation with our support team. And we just put people at, you know, we started at 10 in the mornings for our our sessions. So from nine to ten, you know, you could have breakfast from eight to nine. From nine to ten, you basically went and sat at a table with kind of one or two support people and then a different, you know, it's a salesperson that's a CSM, it was engineering, Jay Nathan: Yeah. Jeff Breunsbach: it was operations. And so, and so we did that for like three or four days in a row. And we had kind of, you know, two to three hour sessions of of every day was going towards like helping support and like seeing these tickets and whatnot. Jay Nathan: Awesome. That's so cool. Jeff Breunsbach: it was yeah, it was really well run. Our our our team did a good job with that. And and so I think like to your point, like that also people walked away with like such a glimpse of like, you know, like the complexity of our business is that we are You know, we're partnering with people on the back end that like, you know, logistics and we're moving items around that, you know, is essentially blood and lab testing. So there's like, you know, there's a complexity and there's also like a a severity of a if something goes wrong, right? And so like our support team handles that on a daily basis, which I think like people finally kind of got more of a glimpse into, which I thought was was was cool. so there's there's that, which is interesting. And then to your point, like one of the I guess one of the things that I've been walking away with recently is just the like AI almost like levels the playing field, right? In the sense of like I could like anybody, I'm I'm building a set of internal tools for my team. And that is not the thing that is going to set us apart, right? It's Jay Nathan: Right. Jeff Breunsbach: like the that is almost like table stakes. Like anybody could go the tools that I'm building for my team is like, what's the problem? What's a potential solution? Can I go chat with, you know, Claude or Chat GPT about it? Can it build me the solution? Can my team use it? And like that kind of order of operations is not like rocket science, you know? It's really not that hard for somebody to go solve for. And so I kind of keep coming back to this idea of like, yeah, what what can AI not do? That's a part of my job is really making the connection Jay Nathan: Mm. Jeff Breunsbach: of like making the connection of like where's our business going? What's the strategy that we have right now? What are we really focused on for this quarter? How do I communicate that to my team very clearly? How do I set the tone, the strategy for my team? Like those are all things that need to be communicated and consistently communicated to my team. And that's a human to human thing, right? I can't automate, like, I can have Claude, I can I can use it as thought partners. I can have it, you know, I can have ChatGPT help me build a plan for that. But when it comes to communicating that to my team, if they see a little hey, sent by Claude, they're gonna be like, that's not Jeff. Like that's not, you know. Communicating it. And then if I, you know, if I don't have the right rituals, if I don't have the right mechanisms in place for us to communicate about these things openly, then my team's gonna go adrift and we're gonna be off course. And then it's gonna again, I can't use AI to just say, hey, go, go get Jay back on course, right? Like, hey, go, let's go communicate with Jay about like what this is. So I don't know. I I've kind of found myself in the last couple of weeks to your point of like coming back around to this realization of like almost yes, like we need to focus on AI and it's a great tool and mechanism. Like you said, it it's It's lowered this silo barrier. It has increased my ability to create solutions for my team more directly, which is awesome. But it still doesn't solve this like leadership that I am in that I'm in charge of for owning this team, right? Like I I'm Jay Nathan: Yep. Jeff Breunsbach: owning the the CS team here, which means that all of those things I mentioned need to be had this alignment, the goal setting, strategy, how do I get my team aligned to all this stuff, communicating every single day about this, like openly, like those are the things that I am leaning into more and more and realizing that that's to me, I guess like that's what's gonna be the differentiator over the next 12 to 24 months for our team is can I get my team to consistently execute at a high level? And that's going to because going to be because of leadership plus technology, not just because I've built a bunch of internal tools for them to use. Jay Nathan: Hundred percent. I heard a stat last week, and I used it in a talk that I gave last week too, that seventy eight percent of people if they detect that they're reading AI, they will quit reading immediately. And everybody can detect AI now, right? We've all got that filter automatically in our heads. We know when it's AI. and then, you know, if you're if you are an author, the thing to know is that seventy five percent of those people will never come back to you to read your stuff again. Like So interesting stuff. The other thing that you just triggered for me, I got a so we have these evergreen job postings on our on our website. We have a four-deployed engineer job opening right now. And we got a resume yesterday. So first of all the resumes we get, I I see them all. They all come into our recruiting channel. this is the first one of its kind that came in this way. It was somebody whose agent. sent their application in on behalf of that person. And I was like, okay, well, it's a it's an FDE, so creative, yes. But am I going to even open this email? No, I am not. Because I know it didn't come from a person. So I don't know if this person actually cares about this company. We just matched some criteria that this person had set up for, you know, companies, probably anybody that had a FDE job opening. Jeff Breunsbach: Yeah. Jay Nathan: open on the internet, right? And it's just scouring and and going through and making a list and and crafting an email and like it's doing a great job of of what it's supposed to do, but I will not open that email because it it's irrelevant to me. So Jeff Breunsbach: Yeah. Jay Nathan: anybody looking for a job, don't do that. Right. And by the way, the other tell there is like if you're these beautiful cover letters that are coming through and these Grand descriptions. Like if you really want a job, don't do it, right? Because of what I just said, 78% of people will stop reading when they know it's AI. Like I know the AI can produce a conglomeration of what my company does and how your skills match it, right? Why don't you just if you if it's really you on the other end, why don't you just give me a signal, right? Tell me something that really, really touched you about our company and about our mission and what we're trying to do. And I think, you know, back to your point. 'Cause I got off track. But back to your point, your people, they're not looking to your agent for inspiration or the Jeff Breunsbach: Yeah. Jay Nathan: words that it produces. They're looking to you, like, do you actually believe this shit? Right? That we're trying to do. or, you know, we're we're not. Jeff Breunsbach: one of the things that I just did by the way that reminds me of our old days. remember when we we used to build these like elaborate segmentation models and like I just had ChatGPT or I had Claude build me an interactive tool in like seven minutes yesterday to do something that I felt like took us weeks back then of like and you know, it like intended well intended, right? Like we were trying to figure out what Jay Nathan: Yeah, yeah. Jeff Breunsbach: are the right mechanisms for this and it just went in like scraped HubSpot, scraped the web, scraped all of our like internal customer data, came back with basically like three or four categories that I could essentially toggle up, toggle down. And now I have a a tier one through four strategy with, you know, our customers pretty easily. And now I'm going to like, you know, change where a bunch of accounts live and and move a bunch of stuff around. But I just felt thought that was like a funny anecdote of like, I remember back in the day this used to be such a a big thing we did and we felt we took a lot of pride in that of like, okay, let's develop a a strong segmentation that we can then align engagement models to. And you know, again, it's like A great thought partner and Claude helped me do that in like ten minutes yesterday. Again, that's not gonna help me go communicate. I have to go convince my team it's the right thing and I have to go communicate these things. But the model Jay Nathan: Hundred percent. Jeff Breunsbach: building and some of the the thought partnership, some of the criteria, some of the data gathering, like that part, you know, essentially done in an instant versus me having to spend weeks trying to go through and filter all the stuff, build spreadsheets. and now I've got an interactive little Vercell app that, you know, allows me to change certain things to, you know, kind of increase, decrease here. so I thought that was interesting too. Jay Nathan: Yeah, you still have to go roll it out and and Jeff Breunsbach: Yeah, yeah, yeah. Jay Nathan: and you know, do the account transitions and that's a human thing probably. Cause Jeff Breunsbach: Yeah. Jay Nathan: I I was thinking about it last night too. You know, we we spend a lot of time. This is not a customer success podcast per se, but we talk a lot about it because it's you know part of the of the model. But what i I I think customer success in the future probably does not exist in the same way unless there's a very high touch sales motion. Right. And then it probably does, but it has more responsibilities directly tied to the revenue. So, but anyway, like you s you have to go do all the human things around all those around all those decisions that you're making. it's funny. Actually, I think didn't we walk through? Yeah, we walked through a framework on on this podcast of the segmentation stuff again. And I did the same thing. We we were thinking about it more in the context of, okay, here's a framework for how you think about it for your organization. Right. Jeff Breunsbach: Yeah. Jay Nathan: Like what are the factors you should consider in your but yeah, and I think we've always had this idea that like segmentation should just be as simple as possible. Jeff Breunsbach: yeah. Jay Nathan: Simple as possible, right? So everybody understands that if you can make it match what in with what what the sales team is doing, that's even better. So everybody's talking the same game. Jeff Breunsbach: Yeah. Jay Nathan: that's cool. So did you pull data in from your platforms and and your revenue? Jeff Breunsbach: Yep. Yeah. Data. I tried to pull in configurations and complexity of our product, like basically like configurations of workflows and setups that our customers have, growth potential. So do we have any open opportunities with them? logo, you know, if it's a if it's a logo that we care about, kind of helps filter up and down. yeah. So so like pulled in a bunch of that criteria and it, you know, spit out kind of four segmented tiers and And then I, you know, have a tool that's basically like, okay, I need to go reassign a bunch of accounts. So current owner, new owner built me tables to show, okay, here's what, you know, they're this person's going from this many accounts, this much revenue to this, which tiers they kind of break down into. So, some helpful things like that. And then that's flowing into to your point, like now I have to go handle a bunch of account transitions. And so that is going to be backed into like HubSpot as well. So I've built like a a UI in our customer OS tool. Where we can now do these CSM to CSM transitions. And so think about kind of pulling in fields from HubSpot directly and then having like some notes and some activities and some other things that we've done with customers. But cool, now it's in an account plan and the CSMs can hop on a call together. Hey, let's walk through all this information, let's share some stuff back and forth. Anyone can be jotting down notes as like a part of that, press a button, it logs that on the record, it changes the CSM, you know, owner and does a bunch of stuff behind the scenes to like make the transition happen. And and so now, you know, we can go use that as a way to help filter through a bunch of account transitions in a way that, you know, is is con coordinated, consistent. we have logged activities around it, right? I've got I've I've got kind of capacity to see all those things now, which is gonna be helpful as we go, you know, make some of these transitions just 'cause you realize, you know, there's a lot of risk and moving accounts around and Want to create consistency. You don't want, you know, twenty seven different types of documents floating out there. So now it's all gonna be like backed into like, okay, here's the here's the one way we're gonna transition accounts and all this information needs to be filled out before you have the meeting with your other CSM and cool, it's start, you know, transitioning ten, twenty a week and we'll see how far we get. Yeah. Jay Nathan: Cool. It's great, man. Jeff Breunsbach: we I've got I've got only ten minutes, but I wanna talk through some of these acquisitions you were you were mentioning about earlier. Jay Nathan: Yeah, yeah, I was about to change course here. So all right, so Salesforce acquired a company called Listen Labs. Listen Labs is an AI first customer research platform, takes over most of the work of a market research team or agency would normally do, designs a study, the AI writes the research questions from a brief, such as a concept, an ad, product idea, recruits participants, interesting, runs the interviews. AI moderator holds live audio and video conversations, asks follow up questions, runs around the clock in 120 languages. That's pretty cool, synthesizes the results and simulates the the customers to sort of predict how they're they're gonna buy. So evidently, this is unconfirmed, by the way. I don't I don't know if this data is accurate. I'll say it just because it's provocative and interesting. And it's probably not too far from the truth, but they bought this company for two billion dollars. Reportedly, the piece that's unconfirmed is that it was sixty tim sixty-seven times revenue, which would put them at thirty million ARR that they bought Jeff Breunsbach: Yikes. That's crazy. Jay Nathan: from two billion. So, but at this point, I don't matter I don't think it matters, right, in terms of like what what Salesforce is paying for this because they're probably doing it mostly in equity, right? Salesforce stock, which doesn't you know, cost them a little dilution, but not, you know, I don't know how what is Salesforce's market cap right now? Three hundred billion, two hundred billion? Tell me, you're looking it up. Jeff Breunsbach: Hundred eighty nine billion. Jay Nathan: Okay, 200 billion. So it's 1% of their shares, right? They they've diluted themselves by. but I guess the this I I don't know, like a couple of things. I don't did you listen to the podcast we did, Ziv and I did last week. He had a couple of Jeff Breunsbach: Yeah, it's good. Yeah. Jay Nathan: interesting ideas, right? Like one is you know, running agents 24 by seven. That's where things are headed, right? And and work becoming more Flexible as a result. So this sort of matches that. what was the other thing I was thinking of here? Jeff Breunsbach: The one when as you think about that, the one the one thing I'm I keep thinking about is how it feels like people are trying to, I guess all these companies, all these like frontier AI companies and I guess like the ones who are investing in models and whatnot, feel like they're all trying to figure out like what is the harness that's going to unlock Jay Nathan: Yeah. Jeff Breunsbach: most amount of usage. Like it feels like, okay, the chat window is like a means to an end. Now it's like voice, how do I talk back and forth? Now it's like, I don't know, now you have Muse, I can, I can, you know, do either or I can but it's on my phone. I don't it just so it it constantly feels like they're all in this fight for like, okay, how am I gonna make it as easy as possible to interact with my models and you know, the work that needs to be done. and the thing, I don't know if this is just the thought that I keep having as all these tools get released, which is like I I have such a divert I I I have such a division of like work and home. That like I I don't know if anybody's I'm sure they're thinking about it, but like it Jay Nathan: Yeah. Jeff Breunsbach: just is it's just so confusing to me that like no one has come out with something that like almost is like so seamlessly being able to like switch between them because like again, I like have to log into my work computer to use work tools and then I like log into my personal computer to use personal tools and it's like maybe that won't ever go away, but I just like I don't know. Like now I'm just thinking Jay Nathan: I think that's more of a I think that's more of a a personal choice than it is a technological limitation. Jeff Breunsbach: Well, like it I guess like it's more of a it's more of a risk thing, right? Like of of like, okay, Jay Nathan: Yeah. Jeff Breunsbach: what what goes on my c a work computer is owned by my work owned by our company and and therefore is like under the risk of our company that our company's assuming. And I guess like that's the point of like, okay, so Jay Nathan: Yeah. Jeff Breunsbach: that means I have to use, you know, models that we've essentially bought and aren't being trained and you know, can kind of have self contained limits of those. so yeah, I guess like it's maybe less the it's more so I guess of like the com Like I would just like something where I could just like toggle back and forth very easily of like, okay, I'm in work mode or I'm in home mode, but like those streams don't cross. So that like it still it stays where it needs to go. Versus me having to log into two different computers and then also like think about like my cell phone of like, okay, Jay Nathan: Yeah. Jeff Breunsbach: where am I on my cell phone? Okay, I have to log into this other thing in order to like get something done versus like I don't know. Jay Nathan: Well, to your point, like I've been using town and instinct over the past few weeks. And I've come to like both of them very much. But I'm hitting the end of my my initial batch of like evaluation, free evaluation tokens. And so now I'm getting the bills and it's like, okay, these things are expensive, right? Like Jeff Breunsbach: Yes. Jay Nathan: I mean, relatively. I think instinct No, town is the one that I'm I'm really running out on. And they were like, okay, it's you know, sixty bucks a month now per user. And I'm like, Woof, okay. So that's more expensive than any pretty much any other piece of software that I run except for LinkedIn Sales Navigator, which has very clear value in ROI. Although I think this is valuable too. But anyway, I I'm I have the same dilemma. I'm trying to think through like what what do I connect my personal life to in my professional life too. And I mean, I'm a part owner of this company. So it's it really all does blend in for me. But for the average employee, I don't think that's true. And even for me, that that's not necessarily true. Right. Like there does need to be a firewall between some of your personal stuff and your in your professional life. So Jeff Breunsbach: Yeah. Well and I just saw something I well I'm f blanky on the name, but they just there's a new AI product that just came out or or somebody's creating something where it's meant to be like your autonomous AI agent that's like living with you and it's like connected to also also like all your home devices. It looks like so you can like almost like connect everything and again like it just continues to make me think, well it's like I don't I don't want my work to know that I have a s a light bulb that can change colours in a room. You know, like I don't know, it's just like Like it just in some Jay Nathan: You're right. Jeff Breunsbach: cases I feel like the I feel like these people are just like pushing the boundary and and yeah, like work and life is like all together and harmonious. And then in my mind I'm like for most companies I feel like there's it's like no, that's not. Like whatever's on my work computer like needs to be my work. anyways. Jay Nathan: Yeah, yeah. Yeah. All right. So let's go back to listen labs. Like what what do you think about this idea that an AI moderator, both live audio or video, conducts the the interaction with the subject? Do you think people are actually doing that? Do you think people are actually participating in those? Again, back to this last thing, right? If you don't care enough to talk to me directly, are you gonna talk to my agent? Jeff Breunsbach: Yeah, like I s I yeah. I I find them I find that hard to believe, I guess. Like I I still and maybe some of I don't know, maybe I'm already dealing with some agents that like I don't know about, like an, you know, American Airlines or whoever, like I'm sure I'm I'm dealing with agents to some degree, but I find a hard time I have a hard time with the like audio visual of like and then also like if if you've seen like I f there's another company that just put out a a person you can chat with on Zoom or Google Meet and it like is actually like acting like a real person. And like some of those things that like you said, I just have a hard time feel dealing with where it's just like, this feels like it's gonna be harder for me to actually get the outcome that I want. I'm gonna have to like I don't know. It feels like I'm gonna have to go through more explanation. It feels like I'm gonna have to like like you said, I'm dealing with delays and other things like I just don't wanna deal with versus just like chatting with a person or chat talking with somebody. It just I don't know. It feels It still feels like we're not there yet, maybe, but like I don't know. Jay Nathan: We met with a company who's essentially building they are building onboarding for software companies using these kind of agents. And I I think there's a difference between push and pull here. Again, back to that idea. But if the customer actually needs something and that's the way you want to give it to them to interact with, I mean it's no different than an IVR. What is it? IVR, not IVF, that's that's different, right? Jeff Breunsbach: Yeah. Yeah. Jay Nathan: The IVR of like the phone tree, you know, we've dealt with that for a long time. Like that's just, you know, necessary friction in that process. Maybe the these agents become necessary friction. Hopefully they're a little bit better than an IVR. But like I forgot where I was going with that. But like are you are are people gonna actually if they if you're reaching out to them, are they actually going to respond if it's not? Real and authentic? Like surveys, I think, have taken that as far as it could possibly go so far. And survey response rates are abysmal. So it helped that I have A AI Jeff Breunsbach: Well, it feels like it gets into Jay Nathan: agents doing it now. Jeff Breunsbach: Well, it also just feels like, okay, at what point is my agent working with your agent to do stuff, you know? And then but that that Jay Nathan: That's true. Jeff Breunsbach: but that also I still find that hard to believe and far fetched, right? That means like I'm going to have to invest in standing up an agent. You're then I'm gonna have to figure out a way for that agent to communicate with other agents. And again, that the when you I I guess when you start to think about When I think about these these problems in the context of me personally, like that seems easy. Yeah, I can set up an agent. I can tell it that Jay's my friend and I want him, I want it to communicate with Jay openly whenever we need to. But now again, think about like the context of okay, now I need to roll that out to 50 people at my company where we all have agents and we all have the same guardrails, who are we interacting with, who's a customer versus a prospect, like who's a competitor that I can't, you know, my agent should be interacting with, right? Like, I don't know, as you start to think about I guess there's like two schools of of thought in my mind, which is like one, this is I I continue to think this gets more and more complex as you start to think about the scale that these things need to operate on at the largest companies in the world. And so to me, like that is so far off. that is like, but I just don't think people think about that. And again, we're like, I forget the number we saw the other day, what, 2% of our population pays for AI right now. So like we're so Jay Nathan: Yeah, it's true. Jeff Breunsbach: far off. and then the second thing is that like. Deploying AI inside of enterprise businesses seems like the number one challenge to solve. And if you're like starting a business right now, it's like the business to be in because it just feels like it is there's no rules, there's no regulation, you know, there's nothing today that's like really doing this. And like it seems like the biggest problem that's going to come to these Fortune 500 companies is like every every CEO of a public company is going to start to get the pressure of like, you know, is your team all using agents? How effective are your agents? How much work have you guys automated? How much work is going through agents versus your people? Right. Like it just feels like those questions are going to start coming and then the pressure is going to continue to mount of like, okay, we haven't adopted this yet. we need to go adopt this like tomorrow. And all of a sudden every public CEO is gonna be looking for a service partner to go do that. Hence, you know, I mean Jay Nathan: Yeah. All right. I know you got a job. Jeff Breunsbach: hence the Accentures of the World and others are probably investing in, you know, in these types of services, right? Like that's all the Jay Nathan: my God, that's it. Jeff Breunsbach: big consulting agencies are trying to figure out how to win this race, probably. Jay Nathan: That's all it is. Yeah. Well, it skits into the book. We don't have to get into it now, but I'm gonna share this book with you next week. It's called The Goal. Very interesting. Very interesting. And I mean it it's sort of second nature for us in this in our world, I think. in tech world, but we'll come back to it. All right. Good chat. See you. Jeff Breunsbach: Cool. All right. We'll talk to you, man. Later. Jay Nathan: Bye.