The Great Flattening: How AI Is Reshaping Teams and Management

29:21They're both in coordinating functions, not executing functions. And then if one goes, maybe you'd have a 10 or 20 % drop in productivity while you're finding a replacement or while they're out on disability or whatever. But you're really able to continue to go on and not suffer any more than you would with any kind of transition like that. What are your thoughts on that? Yeah, I mean, I think what we may be ushering in is this may be the end of the quote unquote middle manager. And it may be kind of the emergence of the department lead, which is not a new concept. You have in what is historically very large departments, you will have like in sales organizations, this is fairly typical, where you will have like a VP of sales.

30:09And then you might have some sales managers, but then, you know, you might have somebody who is, you know, a sales lead. And so they're not managing people necessarily. They're actively selling. But if the manager is out, they know enough, they're senior enough to where they can lead a sales meeting. They can give some basic feedback. They're essentially a player coach. Where I can absolutely see this going is we've got a lot more player coaches out there. There's no longer the need for the full-time manager. And you have kind of everybody is functioning in some sort of a player coach lead type role.

30:41And then there's just one person who's doing that lead. And it may be that it just rotates around, you know, who's doing that. And so now we got maximum redundancy. And what's interesting too, I think is the skill set changes because the skill set goes from high people skills and emotional intelligence to more technical skills. And that will be an interesting thing to observe. How does that work? And how does that affect company culture too? Right. Lends itself really well to remote cultures as well. Right. Because now it is less about, you know, needing to build up those relationships because we, gosh, darn it.

31:21We just have to be able to work together. It's like, well, do you, you know, Do you? Is that as essential? It does fundamentally change things. And I mean, I think there's societal implications to this as well. I mean, for so many people, work is also where they get a lot of their, you know, where a lot of the friendships happen, the implications that come from this. But I think that can actually be healthy. You know, maybe you can be friends with people who aren't in your immediate department. And so, you know, you're not necessarily, frankly, like the CEO guy who's shacking up with his HR person.

31:58From the Coldplay concert? Yeah. Yeah. And maybe you have more time to develop actual friendships with people that you have other interests in outside work. So, you know, that would be a very wonderful evolution. So this is kind of interesting. So this is the what we'll call the pancake maker flywheel. Um, the, uh, so 38 % of startups in 2024 were launched by solo founders without venture capital and solo led AI startups are reaching multimillion dollar revenues faster than SAS companies. And I know that our friends that teach SAS, support SAS, and our SAS are all nervous about being replaced by agents.

32:41Um, and this is to me a really interesting, uh, example. this is a guy named Banu Teja or Teha who started SiteGPT. And so this is the product-focused pancake. And it's kind of meta because his thing helps other people pancake. But basically, he's 24 years old. He created SiteGPT as a weekend project. So not a lot of development in March of 23. It's an AI chatbot that allows you to create personalized chatbots trained on your website content. And so the idea came, he said, when he created a chat bot that was trained on software documentation to answer support queries, which is what Google's notebook LM does, right?

33:24That like really, really well, although all the chats do. So he had basically, he realized he could create a new product out of it and did. And so it's generating around$15 ,000 a month in monthly revenue with only him running the company. And it basically replaces what would traditionally require a customer service team, you know, across a whole bunch of websites. And he's doing it all himself. And this is happening more and more and more. And so particularly as you see text to code allow people to create jobs to be done, apps that can be created within a few hours, which we're doing across the board in our companies.

34:05I think you're going to see more and more of this, like the one that does, you take a picture of you in your hat like that, or you're out fishing or on the beach, and then it makes you into a suited professional headshot, those kinds of things. The one where you take a picture of the blueberry pancakes with syrup on your plate, and it says all the nutritional stuff instead of having to enter all that. Those are all very, very successful multimillion dollar businesses that were created with not only a department of one, but a company of one. And I think you're just going to see that increase. A couple others, Lumen Technologies.

34:39So technology company, but not software, customer service process, time from hours to 15 minutes. That was using Microsoft 365 Copilot, and they're going to save$50 million a year in time, which is crazy. Another one is L 'Oreal. So, you know, again, outside the tech space, but L 'Oreal's Modiface and Skin Consult AI effectively replaced in-store beauty consultants with AI-powered recommendation engines that allow one technologist as opposed to a, would it be a cosmetologist? To manage what previously required an army of trained beauty advisors across thousands of locations. That's pretty crazy.

35:23So, you know, like that's multi-locational physical store, personal service product based that has been shrunk from thousands of people to one. That's pretty crazy, right? Yeah, think about also the impact this is going to have on a lot of the overseas outsourcing type work. You know, there's been such a movement for that because that was such cheap labor. And now what you essentially have is free and infinite labor. I wonder how much that's going to impact the development that's occurring in some of these developing nations, some of these businesses that have been built up to facilitate all that.

36:09It's a huge threat. Yeah, it's a massive threat. Massive, massive threat. Think about places like China, the Philippines, Ethiopia, Colombia, India, where that cheap labor has really, really been able to thrive and help people there evolve. I wonder what the next evolution is for them because they are clearly going to mostly be out of jobs in the next few years. Right. I mean, certainly if you're service based, I mean, if you're doing, if you're doing physical, you know, you know, turning a wrench or, you know, a screw or type thing, like you, you probably got time there, but even there, the robots are coming.

36:49So got to be careful. I mean, robots can turn those wrenches way faster. And of course they've been around, but they haven't been smart. They've that now they're going to be smart. Right. I think you'll see actual minor surgeries and things like that starting to happen with machines too, which is crazy, crazy. But one thing that's really cool about this is if we think about, like, think about a marketing department and think about what our spend on the five people, like you were going to go to five people. So what would that, what would the budget for that be? Half million a year for that department or more?

37:22Yeah, more, more. I mean, when you're talking about where marketing was, the average marketer was definitely getting more than six figures a year. Okay. So give me that five-person marketing budget department fully built out. What's our budget annually? Probably$600 to$750. Okay. And the person coordinating that would probably make what? Oh, I've got them factored into that. Yeah. So I mean, the person coordinating that's definitely in the$150 to$175 range. So now think about this. If instead of paying somebody 150, we can hire a 450 ,000 person and still save 150, are we going to get a better marketing department result?

38:03Yeah, especially because you could put that same budget that you were going to spend into advertising. right so i mean that's like think about the the genius a player that you can get you're replacing effectively five b players or you know one a they're not a because we can't afford them right uh but now we can't that's my argument is like like so if we had you know two b players two c players and a d player um now we basically get rid of all of those and we've got an a player and money for budget for ad spend, that's a game changer. It again, it happened, man. It happened in one of our companies.

38:46We had an open to hire for a head of marketing. And ultimately what we decided mid hire was because we were looking at who we had and we didn't feel like we had the level of talent that we needed for the role. We said, well, why would we settle? you know, instead we can just centralize, we can pancake, you know, more of this marketing under somebody who is really talented and just get them more resources of an AI perspective. And what do you know that they can actually get more stuff done? It's been interesting how this has been sort of happening organically. And we just didn't really give it a name.

39:24I don't think until you and I had this conversation, I don't even think I quite realized and put my finger on on the fact that it was already happening and it's, it's clearly happening to other companies as well. Yeah. That's why we're calling it the great. Yeah. And, and, and, and thinking about doing it intentionally, you know, also, and, and there's, there's clearly going to be implications in the employment market. I mean, as, as an employer, I'm like, yay, you know, as a dad, who's, you know, son's about to be a sophomore, you know, in a, in college, who I'm wanting him to be able to go out there and, you know, maybe find employment, maybe he starts his own thing.

40:01I'm like, geez, this is, this is kind of scary. Like in terms of, is there going to be anything, you know, for them? Well, you mentioned intentional. So let's talk about the pancaking cookbook. How do we cook up these pancake companies? Um, how do we go from department to individual? Um, I think, uh, the first one would be, we need a pancake test. Is this pancakeable, right? Is this, uh, something that we can do? So, you know, from an assessment standpoint, I think we'd say, can this department's core output be produced by one exceptional person with AI support? And we could say, can this department's core output or can the core result we desire this department to deliver be accomplished and produced with one exceptional person and AI?

40:52and AI. So what are the natural pancakes? You know, the functions that are already carried by one star performer would be a good thing to say. You know, we've got rock stars in our company. We know who they are. You do too. Whoever's listening or watching, right? Who are they and can they lead the way? They may need some skill, some upskilling or some cross-skilling from what they're doing now that makes them a rock star to what will make them a rock star in this new. But if they're a rock star, to me, it's once a rock star generally always. And then what is the coordination tax that we're going to say?

41:22What are the hours that are spent in meetings and approvals and handoffs and miscommunications and that sort of thing? And then mapping the decision tree to think about how many people are touching each decision now and all that goes away if we can pancake. I think that's a decent way to think about that test. What are your thoughts on that? I mean, it, so yeah, I mean, how many times do we think, oh, I wish I had another mat? I wish I had another Sally. I wish I could clone this person. And what do we do? So we think that already. So if you're listening to this right now, think about that person.

42:02But at the same time, what is the perfect way, more times than not, to ruin that person? Make them a manager. Promote them. I mean, we get a term for it. It's called the Peter Principle. Talented people will be promoted to the level of their own incompetence. And why does this happen? The reason it happens is because we take these people who are talented in the role that they've been given and we remove them from that role and we give them a new job called management, a role that they're not trained for and are frequently ill-suited for. And the classic example of this is sales. You take somebody who's a really great salesperson, you put them in a role of a sales manager.

42:37And, you know, the old cliche is you trade a good salesperson for a bad sales leader. Typically, great sales leaders are not the most amazing salespeople. And typically, the most amazing salespeople don't make the best sales leaders, just like in sports. The best players rarely make the best coaches. the best coaches usually weren't the best, you know, the most, the most talented people. But what we're talking about here is now we actually can clone these people. Now we actually can make them a 10 X version of themselves because we're not giving them a new role called manager. Right. We're just saying, Hey, you know, we essentially want you to have bionic arms.

43:17Like we, we want you to be, you know, kind of Neo in the matrix where now, you know, Kung Fu, in addition to all the other voodoo that you do so well. It is a, it's a way to multiply somebody's output without calling them manager. And that's something that before, I don't know that we've ever really been able to do. Yeah, it's an amplification of what they're able to accomplish of their rock stardom as opposed to a change of roles, right? And that's a huge, huge thing, I think. So that's kind of the pancake test. And then how do we find that person that's going to run that department, that's going to effectively be that department?

44:00That's the super individual contributor, right? Who is our rock star? So who are the people that already outperform their peers by 10 times, right? And the skills that they're going to need, you're going to have to basically say they need to be strategic thinkers, not just brute force performers. Like the person that's working 18 hour days might not be the best choice for this. Like if they're a rock star just because they're outworking everyone. We like the work ethic, but they need to be strategic. They need to be fluent in AI or educatable and trainable and upskillable into it. And then they need to be able to execute autonomously because they're not going to be managed like a traditional mentorship manager.

44:47They'll still have whoever they report to, but it's definitely more hands-off. So you want them to have kind of an ownership mindset test that they can pass. So are they thinking like the owner of the department? Maybe not the owner of the company, but are they owning the department and the things it's going to do? Are they self-motivating? Are they, cause there's nobody to motivate them. Are they self-executing? Are they okay? Not having social interaction with a bunch of people in their department to support them and praise them and, you know, lift them up. Obviously we need to lift them up from above, uh, down, but those will all be things to think about, which kind of goes into like, can they be a cultural fit in a pancaked organization?

45:34Right. That, cause we don't want to put, you know, a square peg into a round pancake. So what are your thoughts on that? Yeah, I mean, I think it's got to be somebody who is good enough at what they do, but not so good and proud and entrenched that they're the old dog unwilling to learn new tricks. Yeah. And I think what makes this a little bit hard is that can be a bit rare. Very often the person who is that 10X performer, they see themselves as being so good and as being so special and as being so precious that it's like, just let me do my thing. And so to find somebody, and I think we've been fortunate in this area where the people that are those high performers, they've also been naturally attracted to AI.

46:25And I do think you have those people as well, but you definitely are looking for both. And I think if you have somebody who is this high performer, but they just absolutely refuse to adopt this, then probably as talented as they may be, that's not your person. Yeah, I agree. So once you've identified that person, then we say, okay, how do we amplify them? So what's our AI amplification setup? And the first is going to be, what tools are you going to give them? Because we're basically thinking we want to use AI for analysis to understand everything that exists now and that we want to make happen.

47:02How do we actually make it happen? So AI for execution. And then how do we have our different AI agents coordinated with AI, right? So how are they coordinated and talking to each other? And I think the way that we make that happen is we need to do a process map where we look at everything in the department that's going on now, and we document every team process that AI is going to handle now. And then we're giving the AI agents the full authority within that defined box of each of the things that they're executing on. Does that make sense? Yeah. I mean, and this is really simple. If you go through the process that we go take our clients through that I talk about in the Get Scalable book of value engine mapping of business process mapping, that's exactly what you do.

47:51And not enough businesses do this where you visually map each step and stage of your value creation, whether how you go about getting customers and clients, how you go about fulfilling and delivering once you have a customer or client, how you go about, you know, actually creating, assembling the products and services that you make. Like every business has those three core value chains. If you can map them and visualize them, now it becomes pretty easy to go through an audit and say, okay, which of these are AI-able that that 10X person touches? Yeah, I like that. And then we don't just do that, set it up, and then assume everything's going to work out all right.

48:29We need safety nets. So that's going to be alerts, dashboards, override mechanisms, some monitoring for quality control so that we do have a human looking at it because the AI won't know if it's off base for what we want other than the constraints that we build into it. So that's going to be an important part too. How do we build that safety net in? And I think that's it. It's alerts, dashboards, and override. So then the last phase. And human touch, right? I mean, it's always the 108010. Like what you described is that 10 % of inputs. Like let's identify and clarify the awesomeness that is the person you're multiplying.

49:09That's the first 10%. AI is going to do 80%. Having that person who's there to do that final check, that last 10 % of the check, but also the choosing, you know, that kind of let's spice it up a little bit. But if you think about a fancy restaurant, the chef creates the menu. The chef creates the recipe. Their cooks are the ones making it, but it's still going to go to the line, and they're going to sprinkle some parsley on it and wipe any spots off the dish before it gets sent out. And so that last 10%, I think, is going to be important, and they need to own that still. Yeah, I agree. And then I think the, like, how do we, how do we launch this?

49:53The communication I'm kind of interested in thinking about how do you suggest the transition happen? Because I think like we definitely soft pancake to start. We're going to run it parallel for 30 days to be sure that it works before we fully commit. How do we, how do we measure performance? You know, we have to set up KPIs to be sure that like, are they the same KPIs? that we had departmentally before, or did they change because some of those were human-based and now they're machine-based, so we need to modify them? And then how do we know that we were successful? And how do we communicate what's happening to the employees?

50:34And are they going to be redeployed? Are they going to be let go? Are they going to be upskilled? What happens there? How would you say running that transition process would be most efficient and effective? and say how we've done it is, you know, because we've said, hey, everybody, good news. Instead of going in and hiring a bunch of new new people, what we want to do is see if we can just make you all more efficient first, because that's going to make the company, allow the company to be more efficient, which is going to create a lot more opportunity for everybody who's here. And so So we don't want everybody just working harder.

51:14We want to make you all a lot more efficient. And so if we can give you the tools to do that, then that means we don't have to staff up as much, creates more margin, which ideally eventually means that everybody can make more money. And so that's how we rolled it out initially, which was important because when we first talked about AI, and I do think that this is important. When you roll out AI to your team, you need to know that they all are assuming that they're going to get fired. Yeah. And I know because we had, yep, we had people come around and say that. Yep. They're going to assume the worst.

51:51It's human nature. And what's the worst possible version of the story? That's the one they're going to tell. And so you have to inoculate against that and say, our goal is not to do this, to have an immediate reduction in force. Our goal is to do this to make everybody here as efficient as possible. Now, look, if that's not your goal and your goal is, in fact, to have a reduction in force, I would never recommend lying. But just know that if you do roll this out to the team and your goal is to have a reduction in force, then I would look to get that data and make that decision, you know, quickly and take care of the people who you are going to, you know, release to the marketplace because that's going to be tough.

52:34That's going to be tough for them. They're going to know that it's coming and it's going to be a really, really, really painful process. And you mentioned at the beginning compensation. So let's talk about compensation and then let's finish with talking about what Digital Marketer has created and how that department of one agent organizational structure is something that we're putting out there in the market because we've done it ourselves. I think it's important to acknowledge that AI is different, but AI is still technology. And so it's unique. It's unlike any technology that we've seen before.

53:12But I do believe that it's technology and that what it does is it is a multiplier of human performance right now. Like so far, it's not doing anything that humans don't do. Now, we will get to the point of super intelligence, where AI is truly doing things, thinking of things, calculations that humans could not have not ever done. We're not there yet, is my understanding. And so still everything that AI is doing is building upon and is a multiplying force of what a human being would do. That's simply technology. That's the wheel. That's the hammer. That's the pulley. That's the assembly line. Every time technology has been introduced into the workforce, into the labor force, it has resulted in people having better, safer, higher paying jobs, period.

54:07I mean, the industrial revolution, while there were some definitely some like painful, gross working conditions at different points in time, there is no doubt that the end result of that was a lot of people were pulled out of poverty. They ultimately did have safer working conditions and they did make more money. I believe that the same thing is going to happen, you know, with AI is that you're going to have people doing better jobs, more interesting jobs, more, way more fun, you know, interesting work. And I do believe that as these humans become a lot more efficient, employers are just going to have to pay more.

54:44We're going to have to pay more because the market is going to demand it. Like when the people who work for us, when instead of hiring five, We only need two. We're going to need to pay them more money. Just period. Now, we don't need to pay more money today. And right now, today, we can't because it hasn't all caught up yet. Right. Like we're not we're not yet at a point where the revenue is there, but like that's going to come. And the rest like we're at this weird point right now where the gains are just starting to be made. but the output, you know, the gains are starting to be made on the productivity side, but the output hasn't been realized yet from a revenue and profitability front.

55:28And it hasn't been realized at a large enough scale yet that it's impacted what everybody across the board is earning. But that is going to come. And I think it's going to come quickly. And what that's going to look like is for a while layoffs. I think it's going to look like layoffs. I think it's going to look like. I think it's going to look like hiring freezes, but for those who have jobs, it's going to look like wage inflation. Yeah. Then what I think is going to happen is I think you're going to start to see these teams that got pancaked. I think you're going to see them grow again and de-pancake.

56:08Yeah. But they're going to grow again and they're going to deep pancake, um, looking a little bit different and being far more efficient. And so now they're going to get bigger again, but they're going to get bigger again with each and every person being five, 10 X more efficient and productive than they were before. Um, and that will be the output because that's kind of what it's always been. Um, you know, a factory started out only needing a couple of people because they had this amazing assembly line. And then what do you know, they were super profitable. So now they have 10 assembly lines.

56:43And so they needed a bunch of assembly line workers. And so now they needed a floor manager. And so now they need it. And I think the same thing is going to happen here. But I do think it's going to take some time. And I think the interim is going to be weird and painful. I agree. All right. Let's finish by talking about what we are doing to help people, to help ourselves in the marketing side through Digital Marketer. You want to talk about that kind of that we've created there? Yeah, I mean, so at Digital Marketer, and what we realized is that for years and years and years, we've been preaching this concept of the full stack marketing team, right?

57:22That digital marketing, there is no such thing as the full stack marketer. Like there's no way for like one person to know everything that there is to know about marketing. It's just gotten too complicated. It's gotten way too specialized. and that there are these eight core kind of critical core functions that you need within marketing, whether it is social, content, email, you know, on and on and on, like all the different functions that you need within a marketing team that are going to be there. And so what digital marketers focused on really for the previous decade is in training humans to do those functions.

58:01Well, the pivot that we made earlier this year is instead of training humans, let's train AI. And so now what we have the ability to do is to, because we've trained these AI agents, is we can essentially say, hey, head of marketing, here is essentially a fully staffed, and I'm throwing up the air quotes here. Here's a fully staffed team of robots that is an expert marketing team that specializes in all the critical core functions. So here is a amazing world-class social media marketer. Who knows every, who's an absolute social media rockstar. And here's an amazing, you know, rockstar content marketer, you know, all the email marketer, like all the critical core functions that you need.

58:45And then what we do, we work with our, with, with the clients to intake everything about their business, train these agents on everything about the company's business. So now they know everything that there is to know about the, you know, the thing that they do. They don't yet know anything about the business that they're working for, but we input that. And now all of a sudden what you have is essentially the perfect employee. In fact, the perfect team that one head of marketing can run. And it's what we've shifted over to. It's what, you know, we're working with a handful of folks to, you know, to begin to test out.

59:24And we really do see it as not just the future of what digital marketer the company does, but we see it as the future of marketing teams as a whole, whether you have a marketing team of one that got pancaked or if you have an amazing content marketer. So, I mean, we'll work with teams today and they're like, well, you know, I've got a content marketer. Do I need to fire him? It's like, no, we don't need to fire him. But like, give him this amazing marketing sidekick. Right? Exactly. Give them this amazing marketing sidekick. And not only do we need to train, should we train this agent on everything about your company, but let's also train them on everything that this person knows.

1:00:00So they're going to know everything that we know. They're going to know everything about your company. They're going to know everything this person knows. And so now if this person ever leaves, you still have like the best marketing, you know, content marketer that, that your company has ever known. And so that's the idea. And yeah, this is where I kind of see basically all functional teams, certainly the ones that are doing internal functions going. I think you're right. So that's, I'd love to hear you guys' thoughts on what we've talked about, this great flattening and pancaking. It's happening, whether you realize it or not, and it's going to happen to you and your competition is going to be doing it.

1:00:42So if you don't, you're going to be left behind and you're going to have costs and talent that is not able to keep up. So it's not, I think, really a choice. It's something that is going to happen to you one way or the other. So definitely love to hear your feedback and thoughts on it everywhere on social, obviously, forward slash my name, forward slash Ryan's name, and Business Lunch. So if you found this fun and interesting, share. Let us know what you think. And if you're interested in maybe being part of our beta program with the digital marketer stuff, Ryan, what would the best way for them to access that be?

1:01:18Yeah, I mean, hit me up on either Twitter, Instagram. Or maybe just go to digitalmarketer.com because we're going to have something about it there, I'm guessing, right? Because it's still in beta, there's nothing directly there on the website. So I would say if you want, if you kind of want to cut in line, DM me directly. I'll know. Tell me that you heard about it here and I'll make sure that you get to the right place. Just DM me beta on Twitter or Instagram. If you DM me beta, I'll make sure that you get to the right place. Fantastic. And by eye, somebody on the team will see it. Your AI will do it.

1:02:01I like it. All right, guys. Thank you. We'll see you next time on Business Lunch.

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