The AI Productivity Tsunami: How Owners Must Adapt Now

Speaker A: 1, 2, 3, 4.

Speaker B: You're listening to Owner RX with Alan Pence, the podcast for business owners who want to scale without sacrifice. Each episode delivers battle tested strategies from the Owner RX Playbook library, showing you exactly how to build systems that run without you. Here's your host, Alan Pence.

Speaker C: A little off kilter, nothing short.

Speaker A: We are back.

Speaker C: Lots of money, lots of money for smaller things. Hey, that is in her new house.

Speaker A: Forgive her if she's a little upset today. She gets a little exact.

Speaker C: But uh, but I can't just go out and get bread next door, so. Right, right. Just what I need is more bread.

Speaker A: This is the European, um, this is the European value proposition. Right, so.

Speaker C: Well, not if it's just next door.

Speaker A: That is true. As it said, it's very good, Brad. Right. Well you, but you get your steps.

Speaker C: Yeah. See, doesn't that feel good?

Speaker A: Uh, that's true.

Speaker C: Did you buy a lot of bread?

Speaker A: But I was in New York over the weekend in Manhattan and I got like almost 17,000 stuff. You're so American just walking around so I see how everyone sits in. Yeah, it was great.

Speaker C: Well, besides bread and real estate prices,

Speaker A: I did not buy a lot of bread.

Speaker C: Let's talk about hyper productivity in AI. Like hyper, hyper productive teams. I know, I know in AI.

Speaker A: And what's, what's happening there, what's going on?

Speaker C: It's gonna down.

Speaker A: Yeah. Um, well after you have your bread then you get on to your, your agents, uh, and start, start doing your thing. But yeah, I read this article by a guy named Steve Newman. Uh, I think he works Microsoft on one of their products that does some kind of coding thing, um, amplifier I think or something like that. And um, but really good. So I signed up for his blog because I saw it connected from somebody else I read and he uh, had this whole thing about some like kind of anecdotal evidence, but people he's talking to and then some articles he had read that people are becoming what he called hyper productive. So essentially like what I took away from it is when you start realizing that AI tools can build tools and then you can build tools to monitor and improve the tools and you can build tools to monitor those tools and make them better. Like you start realizing that you can create these self improving systems and um, they can start achieving escape velocity on productivity. So like what, what they found is these people stopped actually doing the work. So they're, they're looking at a job, right? Or a set of tasks to do something and then they create agents to you know, so say it's like my newsletter and LinkedIn posting system, right. So I build a system that does that. So I actually don't do the work anymore. I talk to it, I give it ideas about what I want to do. I have like, like I did one yesterday on Hyper Productivity about this article. So then every couple of weeks I download all the analytics on each post and ask the agent to figure out what was it about these posts that did better than those posts, whether it's timing, time of day, the format of the, the subject matter, or like the way we structured the, the post. And so it can start learning about that. Right? And then you can start plugging in other things like, oh, now I can create an agent that goes out and searches for new, like, it would have like a set thing about best practices on LinkedIn. And then you could send it out once every couple of weeks to search Reddit and other, you know, blogs and stuff like that to find information about what works on YouTube. Sorry, uh, on LinkedIn. How, how the algorithm's changing. You could do it for YouTube too, right? Same thing. And so it could start going out and finding information from people that are like, oh, the algorithm changed slightly, so you should do this. And then you start creating the system where you can keep tuning it. And then you're like, then you start looking at who actually interacts with your post, right? It's like, all right, is this somebody I actually want? And then you look at like, all right, well, this post got comments from people who are in my ideal customer profile. This post got a lot more comments, but they're not people I'm really wanting to try. And then you can feed that in, right? So you start creating the system that the agents can work. Right. And so that's, that's probably not the best example, even though it's, it's a decent example. But like, you know, LinkedIn still prevents you from like using agents to interact with it. That's, that's like one of these things that I wrote about the week before with old kind of SaaS and social media apps where they're trying to hold on to this old way of doing stuff because it's profitable to them. So it's going to be more difficult, right? So it's going to be, you know, like when you're dealing with a LinkedIn, it's going to be more difficult. But you know, if you're doing like the newsletter. Yeah. Uh, you can just create a self, uh, improving process. Um, and you can like read who's opening and all that kind of stuff, right? So you know, you do that with that. You could do it with clients, right? You know, you record like I do all this stuff with meeting transcriptions. And so you feed every meeting transcription into a series of agents and the agents can do all the, you know, the follow up email and hey, what, what should the next agenda be based on this meeting? And then it can write to a ledger, like a project management document where it's like, what are we doing with this client? You know, and that keeps updating. And then it can feed into an agent system where you can rate me as like a client service or like how I enter. I'm a coach, right? So it would rate me on coaching, but I could rate you on, um, how well you updated the client on, um, whatever or talked to a customer or did a sales call, right? And then it can go out and start being like, okay, what are the things about what's going on with this client? Right? And it could go, maybe you're, maybe you have a client at a Fortune 500 company that you're doing, you know, IT services or marketing or whatever, and it can go out and research what's happening with that company. And so you get real time updates before you meet with a client about what's happening. Um, so you realize, you start realizing as you piece together these agents that then you can, you know, like. So first of all, I started talking about, hey, now I can do this other thing with the client and this other thing. So you're adding like another agent in the process. Then you start adding in.

Speaker C: Everybody wants to be antagonized.

Speaker A: The first thing I started doing was antagonist agents. And so now I have agents that like represent small business owners and they antagonize. It's like, you know, it's like a check. I love the word antagonist, so I use it. I know. Ah, I love, I love that. I love it. But you know, AI doesn't have emotions, so it's okay. Um, so you know, I have a user agent. I have one that's like making sure it doesn't make up stuff. Um, and like I had that the other day, like in the link in post that made up a bunch of stuff and I was like, hey, I, I had that on the newsletter, but not on the LinkedIn. I realized. So then I updated it, right? And then, um, you know, so like you need to be able. So, so then, you know, I use antagonist agents and then that improved quality and then you can start doing, you know, these Feedback. If you can get analytics, get any kind of feedback like that, you can put that into the agent. And so you start getting these loops that can go. Right. And what I'm noticing is a couple things. One is my ability to now get better and better at something has just gone off the charts. Like, I didn't know how to write LinkedIn posts before, and so I had a couple that did really well. Um, I had worked with other companies in the past, what did well and what didn't. So I fed that in and then I just started building on that. Right. And so, like the old service model of, hey, I'm gonna go hire some agency. Like, I don't know why you do that. Right. I mean, what you could do is go in and look at somebody and yeah, go into somebody in your subject interview. Right. You don't even need to hire them.

Speaker C: So when you're talking about hyperproductivity, you're referring to your, or a business owner's ability to, um, do everything you're describing without any more work, basically.

Speaker A: Right.

Speaker C: So you don't even, you know, less, like, productivity. Okay, Start with the.

Speaker A: Yeah, well, I, uh, wouldn't say that it's not without any more work, but it's like. So I, I would say there's two aspects to this that I think are interesting. One is really positive, one is really negative. So the positive aspect.

Speaker C: Negative.

Speaker A: The positive. Sorry.

Speaker C: Yeah.

Speaker A: Uh, so the positive is you can start. It's not like you don't have to do no work. You've got to be there, directing, monitoring the agents. Right? But you can start doing 10, 50, 100 times the amount of work you used to do. And it gets better quality, right.

Speaker C: As you do it even a year ago.

Speaker A: So, um, what you see is people starting to achieve breakout velocity where they can start doing things that would have taken teams of 5, 10, 25 people before. And of course it's. Yeah. Six months ago, right. I mean, and of course it's like a jagged frontier, right? So they call AI jagged. And it's like, so in one thing it can do like 100 times better. And in another thing it's like not that good. So it's like an uneven surface. So it's not like I can plug in magic agents and everything takes off to hyper productivity like that, right? So you have to experiment with it and you have to work on it. Right. And so that leads to the bad part. But like, let's talk about the good part in full, right? So in these areas where you can make this kind of progress. What I've noticed and what this guy is writing about is it isn't coming from adopting um, off the shelf tools now I guess. Claude code, right. You know, so the coding tools, yes, it comes from adopting those or Gemini or Codex from OpenAI. Uh, but what they're doing is they're building bespoke solutions with us. They're not going to the agent companies, they're not going to Google, you know, they're going directly. They're using the coding software to build their own tools and everything. You know my, my view of the world is everyone's becoming a programmer. Like programming is just talking to computers and so AI is making talking to computers really easy. You don't need these intermediaries anymore. Like they built software for you that you could, so you could talk to the computer. So now you can just talk to it. You just.

Speaker C: So you don't have to write diary anymore.

Speaker A: Alanization thing from every dot, uh two called monologue. I hit option key twice and I talk and it transcribes what I said into the Claude code window and then Claude goes and does it.

Speaker B: Right?

Speaker A: That's right. My diary can be in Claude code. Right. And so um, that is allowing people to start building these stacks. And what I think is happening you're seeing is that individuals and small, um, very flexible, highly uh, agent, you know, well, the people are agentic and productive people. Right. So they're able to adopt these tools. They're very flexible. They, they can go do this like that, like they can just go rocket ship. Whereas companies have a huge problem because one, they're, they've got legacy pro processes but they just don't have every. Well and every person on the team is not as capable. Right. So what, what you'll find is that if someone who can't keep up with that is involved, it really slows the whole thing down. So it basically kills you. So it's really only individuals in these very small teams that can do this at this point. Now of course like there's sort of an exhaust from that where like what they're doing will eventually get adopted and implemented and companies. But it's going to be a big lag between what they're doing and what everyone else is getting. And so you're going to see this increasing split where very small hyper productive teams are able to do incredible things and other people are going to be like how do I do this? I'm still like typing in my Word document. Right. Um, and I think that it's not fair and inequality will get worse. And um, because the returns to a highly productive person to adopting these tools is hyper productivity, hundred times capability. And you know, he cites a guy like in China who's built like 20 companies, just spins up companies using agents that do stuff overnight. And like they select the name of the company. Like when he has an idea, he has, Claude could go out and plan out how to build the software. And uh, another one goes and searches for domain names and then actually pings the register to see if it's available. And like, and then he wakes up in the morning and here's the name and the plan. Right. And so he's, I think he's doing like a, like a million in profit right now. Just like selling little apps to people. Right. And um, I found it with my own work that I probably didn't have to hire two or three or four people to get the OwnerX stuff going. And even now, you know, I had these developers.

Speaker C: But you didn't know what you didn't know in the beginning, which was such a short time ago relatively.

Speaker A: I mean they're great and there's certain things you still need someone who understands programs for. But I actually feel like they're slowing me down now. And that's right. Yeah. Right. And so now, now what I found is every one of the contractors I had, I had.

Speaker C: Isn't that amazing?

Speaker A: Different points. I had people helping me write the newsletter, helping me recruit people for subscribers. I had LinkedIn posting, I had developers. In every case I've gotten rid of them, um, because it's just easier for me to do it with agents. And like they are actually slowing me down. Yeah. So I've replaced, I wrote in LinkedIn, I probably replaced well in the bat.

Speaker C: I mean you talk about this clear bifurcation between basically the haves who will be able to do this. So uh, it's pretty forward who are more skilled at it and those that can't. So is that, well, that must be bad or that is the bad.

Speaker A: Right.

Speaker C: Smart people.

Speaker A: Yeah. So that's, so that's one aspect of the bad is like I've tried, you know, I taught this um, course to owners on how to use AI and it was like pulling teeth. Right. I mean they're all great people, I love them all. But like. And so yeah, some of them even are early adopters. Right. Like I have a couple of guys in there that. And gals in there that um, are really doing stuff, they're building things, but they're too Distracted by their business to like figure out how to build the tools that do the work and then build the tools that monitor the tools that build the work. Right. So it's like they, they are not, they are not like uh, I don't know how to turn someone into what I'm doing. It's almost impossible. Like I, I thought about it and thought about it and thought about it and it's like I literally have to take over your company and redo everything.

Speaker B: Right.

Speaker A: So like what? Right, yeah, like that's what I'd have to do. Right. And, and like a lot of things would break for a while before you got there. So to me it's like I can get you to what, what we're going to try to do with owner rx, uh, is do like a mini version. So I've been thinking a lot about what we're going to do with the tool because it's gone through some iterations and now that I'm going to take it over, I'm going to take over the development so we'll be able to do stuff faster. And um, I'm really thinking that I need to implement it with the owners like and then yeah, set them off to use it and then come back and build more agents for them and then send them back and have always operated. And like that's the only way I can get this to happen because the change management is massive. I mean it's like I gotta tell you to change how you operate completely from soup to nuts. And this is, yeah. And so this is very, you know, people are using this steam powered factory versus electric factory analogy. So I think it's very apt. Like I guess at the end of the, you know, like in the early 1900s factories uh, were automated and powered to a certain extent. But it was like one big steam engine in the middle that would run like everything. And so everything was set up around that steam engine and electricity came out and clearly it was a better technology. But the old factory, it was actually more expensive to run it, ah, the same way with electricity. But what electricity let you do is break up all the machines and plug them in individually. Right. So now I can move this machine over here. But that required a complete refactoring.

Speaker C: Yeah.

Speaker A: Of the factory setting. So it wasn't really, it took like 20 years for factories to just completely switch over and it was new factories coming in that drove it. So I think we have an analogous situation where like I have to take your entire way you do work and shift it and Then you've got to get into this world where we're not, I'm not giving you a SaaS product that's going to work perfectly.

Speaker C: An individual.

Speaker A: The problem with that SaaS product is it's one size fits all. What I'm giving you is an agent system that you have to continuously improve and work with. So this is a big shit, right? I just kind of had this insight right now, so I'm going to write about this. It is not a plug and play system. It is a way of doing work and evolving.

Speaker C: It's like breaking, it's like breaking what they have. That's what it feels even though it's not uh, but that's what it feels like.

Speaker A: And so there are a lot of owners are like I don't want to deal with this, I don't want to deal with tech, I'm not a tech person. It's like well companies are tech, right? So, so am I making an argument here that like my tool won't work maybe because like, or at least for the purpose of helping other owners, like maybe I just need to build everything myself and just do it, you know, I, I, I don't, I think we're going to experiment with this and see what happens. Like I'm going to try to get people into this mindset and say look, what I'm giving you is not going to be perfect. We're going to have to do this over and over and over again. M and like you're going to get, but if you do it, you're going to get on a hyper productive loop, right? So if you really commit to that, all of a sudden you're gonna be like oh my God, my company is like five times bigger and I didn't

Speaker C: hire what will be the.

Speaker A: But you've got to commit to that process and you gotta work that way and you gotta stop like trying to do all the work. You gotta start working on the work. It's almost like, I don't know, I think it's gonna be really tough. I mean they gotta be, I don't know, they've gotta be like I want to get my hands dirty with this stuff. Like, you know, you just can't. Like, like I can't come into your company and implement a product that's radically shift how every single person in the company does work and like the owner's not going to be involved. Like how's that, how is that going to work? So every single person that's going to go to the owner immediately Be like, wtf? What's going on here? Um, so I think probably like just thinking it out real time. It's like sections of work can start and you probably have returns in discrete areas where you're willing to blow stuff up a little bit. Um, but uh, I think that the change is massive and the, the return's massive, but there's risk, right? So like the agents aren't going to work perfect. Like I said, they're not going to work perfectly. You've got to, you've got to be on top of them and, and some mistakes are going to happen. There's no question that that's going to happen. But it's like you can play the safe bet and wait to get washed out by the tsunami or you can get on the hyper productivity train, right? Um, so I think it's a way, I think it's just a way. And it really requires, so it really requires a mental shift in. First of all, you got to get an intuitive feel for what the AI can do and can't do. And so you really target the places where it can be more effective. But that requires a lot of imagination to really understand it. Um, and you have to be able to conceive systems as a whole. It's really benefiting systems thinkers like strategists, people like that. Um, and uh, then you've got to, um, understand where it can and how you have to match that up. And you've got to realize, to me, this is the other thing I've sensed from owners. They want everything to be perfect. So they want this optimized system where I just push a button and it's like, no, that's a waste of time. I was just talking to one of my clients about this who wanted this perfect dashboard that was built with real time data and blah, blah, blah. And it was like, all right, we could spend $150,000 to build like the perfect connection, or we could just like download a CSV file once a month and run it through a prompt. Like, why don't we just download the CSV file? Like, like, what are we doing here? And that's what I think we got. People have got to get out of that. It's like we've now, of course you need security, you need processes. So like, you know, if you're hacking it together a bit, it can get out of control. So you gotta, there's a downside, right? But it's like, you can't just waste your time like doing that crap. You gotta get stuff that's actionable for your company. Um, and like yes, at some point I can't download CSVs and create a scalable process. But do I really need to, to like look at a dashboard once a month? I don't.

Speaker B: Right.

Speaker A: But like if I'm doing something that's repetitive for customers, yes, I need that to be like scalable and adaptable to different people. So I'm going to concentrate my effort there and just kind of just get the data where I need to. And so like I think so there's that there's like this capability of rethinking how you do work, what you really put your effort into to like make it uh, pretty and use in like fault tolerant for like you know, lower grade users. Right. And what you just kind of get done because it's like easier to just do it and then you've got the, the other thing I think that negative that I think is un. Underdiscussed and he mentions this in the article and I definitely like resonate with it is like it's exhausting. Like the agents never stop. Yeah, the agents, first of all, the agents never stop. They just run whenever you want them to and then you know, they can run 24 hours a day if you want. So they can be producing results for you all the time. So how can you even consume some of the results? Right. And then I find the really exhausting part, I call it like AI anxiety is like, oh my God, I could do this. Oh, I could do this.

Speaker C: I can see how that could be like drawback.

Speaker A: Like okay, there's an all day endless

Speaker C: and eat dinner set, go to bed

Speaker A: that you could do to use the AI to improve the business. So it's like. Yeah, right, right, exactly. Right. So I think that there's a big problem there. Um, but I think what you're finding is these people, the people are really breaking out. They are going crazy, they're going to hyperproductive and it's probably burning them out to some extent but like they're going to be able to sustain it longer than anyone else. Right. And um, we'll see where that goes. And you know I, I think we're going to have these things where it's just like you got to unplug for a certain period of time to rejuvenate and you know, just similar to work. But, but I do think that that that is real and especially as the technology is shifting but in the beginning, quickly.

Speaker C: It's kind of like an irony though because AI is supposed to make your Life hard to feel like you're gonna miss something.

Speaker A: You know, I think there's a time,

Speaker C: but in a way it's actually evens out a bit. At least now where things are capabilities doing more and more precisely because of what you're saying. Because like it doesn't stop and you're always going to be thinking, I've got to see what, what was the analysis of that? I've got a tweet that agent. Mhm.

Speaker A: Yeah. So I think I would say I firmly disagree that AI is about making our lives easier. It's this economist wrote about Jayvon's paradox, right? It's like when you like Eli Whitney invented the cotton gin to get rid of slavery, but what did it do? It made cotton production more effective and they actually ended up importing more slaves. Right. And so like, I think there's something going on here where it's like it's not. I mean, yes, it makes things easier, right? But then it just makes more things possible. So you just keep doing more things. So like if, if, if human desires were finite, then but they're infinite. So we just come up with more stuff we want and then the AI enables it. So um, there's no like easier. Right. And um, yeah, I think that's a real down. I mean it's a really good side and it's a real downside for people. You're going to have to learn, we're going to have to learn how to manage that. Um, and I do think it'll get better as the technology hit hits plateaus, but that has not happened yet. And the other thing I'm seeing, which is also like another part of hyper productivity that he doesn't address quite as much or. No, he does, I guess. Yeah, is. And I actually went. So he talks about this other developer, um. Oh no. So the guy Steve Newman, I think does something else. And then the developer works for Microsoft. And so this guy Jesse something. So he mentions him. I went and read his blog post about how he's using Claude code today. And um, they developed this thing called Skills and plugins. So Claude, now you just have little files that tell Claude how to do things so it doesn't have to have it in the code. So it first started with, hey, um, make Word documents. Because it didn't. It made alt markdown files, make PowerPoints and those were kind of things. And then it's like I started down anthropic has a GitHub repo with all of them in it. And you're like you just download them and use them and it's like they have a skill for making a skill. They have a skill for um, committing stuff to GitHub. They have a skill for, oh, you could put your brand identity into it. So like every, every uh, webpage you build would reference the brand identity and make sure it complied. You have a skill for you know, anything basically. And so this guy basically has built a huge skill lab, uh, uh, archive of all the stuff he does in programming. So he's a 30 year programming for 30 years or whatever it is, you know. And so he's built skills gradually over time for all the way he does everything. Like he does this test driven development where you write the test first and then the code has to meet the test versus like writing the code and then testing. Right. So that's like a way of doing stuff that I didn't do. And now I just downloaded all his skills and now I can program somewhat like him. So like to me that, okay, now talk about hyper productivity. I can go find the best people in the world and if they're willing and enough will be to share what they do freely. I mean you can adapt, you can adopt superpowers.

Speaker C: So you'll never.

Speaker A: The thing he puts out is this thing called superpowers.

Speaker C: You're never gonna sleep again.

Speaker A: A bunch of skills for development. And I downloaded, I started using them and it's like holy Christ. Like this is, this is mind blowing. So that's where I. What's that? I know I gotta take off Thanksgiving I think. But um. Yeah, so I think what, what I wanted to talk about today is just like we kind of got into some other stuff I've been thinking about is like I am really torn about how to proceed with this with the company because I'm going to try this adoption with business owners by working with them using the platform and then kind of taking over the platform myself from the developers and just using these skills and superpowers to keep building it out and see if I can get people to change how they operate and get traction with that. But I almost, I'm starting to really believe that. I mean it's such a trope, but I hate saying it, uh, but the change management is more important than the tech and getting people to just shift how they think and how they operate is really difficult. So I am seriously thinking about what industries can I just start a business using my AI, uh, agents and like outcompete other people? Because like I'm trying to get people to change. If they won't do it. The only thing that's going to change them is getting put out of business and the competitive threat is going to change people. That's, that's what's going to make the change. So I, I'm in this situation where I'm like yeah, like how much, how much do I want to bang my head against the wall trying to get people to do stuff? Um, versus just like identify industries where like iterative self improving agents will give me a huge advantage over everybody else. Like in marketing I could definitely do that, right? I could build like the ultimate marketing agency. And somebody said that uh, it was either on a podcast, I think it was a podcast. Yeah, I was listening to a 16Zs or no, it was a 20VC. Um, a guy who built of these coding apps, base 44 or something like that. He was saying that, he was saying that like it. So one of the big areas of adoption right now is there's a company called Harvey, there's another one I can't remember that are selling models to law firms and help them with you know, research and stuff, like case law research and stuff like that. And um, of course everyone wants to talk about the ChatGPT thing that the guy cited in court and got burned for. But these, I mean just show you these models are only trained on case law, right? So they don't hallucinate like that. And uh, they're much better and they're getting adopted at a really high rate. So he started saying well is that a better business than just becoming the AI first law firm? Like what if somebody just figured out how to use AI really really well created self improving agents themselves and didn't sell it to anybody else, they just used it to out compete them. That's where I think like is the whole SaaS model going, like if software becomes completely plug and play or as this guy said, liquid like I can create it and I can throw it away. I just have a database with all my data in it. And then I'm like hey, I want to look at this, I want to do this. And then Claude go just does it for you. It has a skill, right? As a skill for a document, has a skill for a dashboard, has a skill for. I want to do this kind of analysis, right? Anything you could do in a, in a um, piece uh, of SAS software, like does it's really the processes that you use and the creativity of the agents and your knowledge repository. So like does it bring like do pure play Software companies beyond the model makers really just go away or some tooling, you know, around. And really it's the services companies that use the software, the ones that get built AI native. So the AI native marketing firm, the AI native accounting firm that. They're the ones that take over because they, um, they just have the. They basically build the intelligence into their own system.

Speaker C: But you are, but you're thinking about,

Speaker A: you're thinking intelligence because it's theirs. So that's a. That. I mean, that might be a little heady at this point. I'm not sure I'm ready to say that that's where we're going. But like, that's crossed my mind several times when I'm, I'm thinking it, uh, I mean, it's a complete shift, right? Everything was like before is like, oh, you have this crappy services company, it's worth five times profit. And then your, your sas, uh, company, your software company was worth ten times revenue. I mean, totally different, you know, valuations. I don't know, maybe that's not going to be the case in the future. Like, what if you have a law firm that like executes a little bit better because its agent processes are better, continuously improving. You can go buy your Harvey model, but they've built such like. Or. Or they're going to get into niches, right? Like the best.

Speaker C: You just have to go trade law

Speaker A: firm and the best IP law firm and they're going to have like so many iterations. That's that, like Harvey doesn't. That's heavy, right? So you can't buy. You can't buy it.

Speaker C: It is.

Speaker B: It's, um, all.

Speaker C: That's all I have to say. That's heavy because it's a lot.

Speaker A: So that could be possible.

Speaker C: It's a lot to think about. Does that mean you have some thoughts?

Speaker A: Heavy, man. That's heavy.

Speaker C: Yes. As I lie on the floor and cry.

Speaker A: Yeah, it's a lot. It's a lot. Well, you can think about it as you decorate your new house.

Speaker C: Yeah, well, m. I'm going to be thinking about all that. Lie on the floor because there's the only space to be

Speaker A: moving is hard.

Speaker C: I do. I weep over change management.

Speaker A: That's it for this week.

Speaker B: You've been listening to Owner Rx with Alan Pence. Want to apply what you just Learned? Try our AI business advisor, uh, @ownerrx.com it has all the insights and lessons from this podcast, plus hundreds of playbooks ready to solve your specific business challenges. Owner Rx, stop being the bottleneck. Start being the owner.