Greg Shove, CEO of Section and founder of Machine and Partners, returns with a candid and provocative take on AI’s next wave. From real-time AI coaching to business model shakeups, Greg unpacks why the real disruption isn’t the tech—it’s what comes after. He talks deflation, job loss, and why being in the “AI class” won’t save you anymore.
In this episode, Greg Shove, CEO of Section and founder of Machine and Partners, joins us for a "where are they now" follow-up—and doesn’t hold back. Greg walks through the rise of Pro AI, his new AI-powered coach, and why traditional upskilling is already obsolete.
We explore the overlooked friction points in AI adoption, from cultural taboos (“it feels like cheating”) to failed enterprise rollouts. Greg challenges the prevailing mental models and warns that the real upheaval is still ahead: business model disruption, not product disruption.
From royalty-based agents to outcome-based pricing, Greg lays out why service-heavy industries—from law firms to SaaS—are heading for a margin-crushing future. Plus: the moral responsibility of CEOs, the fallacy of lifelong learners, and why working with AI means holding onto your own judgment.
A sharp, honest look at what it really means to work smarter—not just faster—in the age of AI.
Key takeaways:
Linkedin: Greg Shove | LinkedIn
Website: Greg Shove | AI Strategist & Keynote Speaker for Enterprise Leaders
Section: Section | AI workforce transformation for real ROI
Machine & Partners: AI Consulting Services | Machine and Partners
00:00 Embracing AI: Changing Work Culture
00:29 Introduction: Meet Greg Shove
01:10 AI in Daily Work: Tools and Changes
03:59 Business Model Disruption: The Next Big Shift
12:45 Training and Adoption Challenges
19:14 The Future of Work: AI's Impact on Jobs
32:02 Leadership and AI: Strategies for Success
35:20 Embracing AI in the Workplace
36:51 Workflow Redesign with AI
39:39 The Role of AI Agents
40:12 Challenges in AI Adoption
45:14 Pro AI: The AI-Powered Coach
51:03 Disrupting Business Models with AI
57:52 Cognitive Offloading and AI
01:03:02 Final Thoughts and Reflections
📜 Read the transcript for this episode: Transcript of The AI Implementation Audit: What Section’s CEO Learned in 18 Months
[00:00:00] Greg Shove: You have to say to your team, this is not cheating. You have to say that working with AI is working smarter. You have to say that we want you doing this. We have all these deeply held cultural beliefs about work. Don't cut corners. Hard work is the virtue. Right. Don't cheat we've gotta shift all that. 'cause right now, for a lot of people it sounds like it's cheating Using ai, it sounds like you are getting an unfair advantage. Hi. I'm Greg Shove. I'm the CEO of section, the founder of Machine and Partners and the author of Personal Math. I'm Canadian, so I believe everybody should have access. I'm British, so I don't give up. I'm an American and I believe in outsized opportunities.
[00:00:44] Jeremy Utley: This is a conversation I've actually been wanting to have for the last six months. Because ever since we had you on the first time, there were so many threads that we could keep pulling and keep exploring. And I've continued to follow you and your work and sections work. And i've been really impressed at how you have kept your finger on the pulse of what's changing, what's developing. And I've been looking forward to you kind of doing a, where are they now? Episode. We've not done this before. This is the first time we're doing where, are they now? Episode. So talk to us for a second about what has changed, uh, in the last 18 months in your view.
[00:01:17] Greg Shove: All right. Uh, a lot and in some ways not so much.
[00:01:23] Jeremy Utley: Okay.
[00:01:24] Greg Shove: we'll focus on what's changed. Uh, here's one, just us started. I have an AI monitor now on my desktop. So I've got a third monitor, uh, on a vertical horizon, just out of my line of sight, but, in it as well, meaning it's my, and I can see it all the time when I'm working and on that is one browse with three tabs for Plexity, GPT and Claude Open all the time. Claude usually my default, so it usually says, good morning Greg, or Good Morning Captain, which is
[00:01:53] Jeremy Utley: Right.
[00:01:53] Greg Shove: eyes to address me, and that's kind of always there for me. That has increased my ai. Usage. It's kind of an upgrade from my Post-It note that I used to have on my monitor that said, ask ai, this is the a hundred dollars upgrade, which I started in January. So that, that's one thing that's changed and it's, it's been really interesting for me. And I think a, a hint of what's to come when ouris are really with us all the time. Right? Listening, watching you might have seen that Google feature, it's not yet ready for consumers, but it's in the development, uh, studio part of Google in terms accessible to developers where you can screen share with Gemini Pro. , When you see where this is going, you realize how pervasive these tools will be in our lives. And my little AI monitor was my experiment to understand what that feels like. so so that I don't forget to use ai. I make it easy to use ai, reduce the friction to work with ai, and then I cut and paste that work and bring it into my main monitor, my main workspace.
[00:02:46] Henrik Werdelin: Do you still use writing or do you use like whisper flow or something like that and you recently talked to it?
[00:02:50] Greg Shove: yeah. I just got, I just got, uh, uh, was it Whisper? What's it called? Super Whisper. Super there's Whisper.
[00:02:56] Henrik Werdelin: flow. There's a few different ones.
[00:02:57] Greg Shove: one of those up and running actually, this past week. And of course I still use a lot on, uh, events, voice on GPT on the phone. But, uh, that, that, that's new. I tell you what else is new for me. Obviously the reasoning models, uh, their capabilities, they still hallucinate like crazy. So that hasn't changed. We've, I think made almost no progress in hallucinations from my perspective in terms of sort of everyday consumer use. but the reasoning models, the powerful, and I think that mental model we all used a year ago that AI was like a summer intern, tireless, hardworking, but makes surprising mistakes. That's the wrong mental model or frame. If we're, if any of us are still using that model, you know, we need to update it. It's now an analyst, it's now a first or second Year MBA, it's now a very competent research analyst. it's moving up the org chart. AI is in terms of knowledge work,
and it's, you know, it's gone from a hundred dollars an hour to 200, $200 an hour is kind of my perspective on it in terms of its capability. An hour of, of human time at around $200 is converted to a minute of reasoning time. So I do think. What hasn't changed yet, and I do wanna talk about today if we have time, is we haven't seen any business model really, uh, disruption. We've seen mostly technology and product disruption, if you will, beha some behavior change in terms of, we don't use Google as much. We use ai. Uh, more and more. We haven't yet seen business model disruption, but it's coming and it will be more dramatic than the technology disruption.
[00:04:23] Jeremy Utley: Wow. , Say more about that. When you say it'll be more,
[00:04:26] Greg Shove: if you think about the great companies, they're really great companies. The well VCs called generational companies now used to be unicorns. Now we call them generational companies. But if you look at Airbnb, AWS, Uber, uh, Fiverr, companies, the significant ones. Have changed the business model as much as they changed the product So they certainly changed the product experience. First. They innovated on the, on the, product or service that they were offering using technology and using the disruptive nature of the new technology, whatever that might be, mobile or, or, cloud or whatever. But really what they did that was more dramatic that the incumbents could not match is the business model disruption. 'Cause incumbents can eventually catch on product. They, you know, they can throw more people at it, they're gonna be later, you know, and so it's gonna cost them more. Google is catching up with Gemini so, eventually kind of equals out at some point. But the business model disruption crushes the competitors and the incumbents changing how you make money, changing, how you charge for it. And I just can't see anything but a deflationary pressure.
[00:05:34] Jeremy Utley: Hmm.
[00:05:35] Greg Shove: significant deflationary pressure on any product or service where human capital is the primary input.
[00:05:44] Jeremy Utley: What are the implications of that as you, as you play it forward that in long-term deflationary pressure? What is, if I'm a manager or even, you know, a director, a junior employee, what are the implications of that reality on my, how I move forward?
[00:05:57] Greg Shove: I think the implications are in the short, if you, if you are a team leader, manager, CEO of a company selling a product or service where human capital is 50% or more of the input, that by the way, is all of software. All of software. The whole industry is its biggest input, is human capital. All of consulting, most services businesses, human capital is the primary ingredient, the primary cost of goods, the primary input, uh, labor, labor, input, knowledge work.
So if you are in that, in one, in one of those companies, you will enjoy short term margin expansion. in the short term, you're gonna think AI is good. And if you're not using ai, you're gonna miss out. If your organization's not using ai, you're gonna miss out on that margin expansion. That's gonna be deceptive, gonna be good, but deceptive, it's gonna be a sugar high. And then the crash will come, meaning prices will deflate rapidly in your sector, or vertical or category driven by AI native competitors that use the business model disruption more than the product disruption to win.
[00:07:11] Henrik Werdelin: Can I ask a little bit more the business model maybe, uh, just do, um. It sounds like I'm kind of, uh, flaunting a business I'm working on, but like, we're building this business that helps people make startups. So basically makes agenda businesses. So we have people come in through Instagram saying, I'd like to start up business. And then we help them identify what the business should be and we built, you know, like the agent and then we help them sell it. Now, the business model is not equity. It is a royalty. Um, because basically the business model, they'll never sell to anybody. So it doesn't matter to have equity, but obviously it will take, I think, over a lot of venture capital. And so we raised a bunch of money to kind of do this. Is that the type of business model change that you're thinking? Or am I, should I think about business model changing in a different way?
[00:08:00] Greg Shove: No, I think that's, that's, one great example of, of of a different business model. Another obviously is charging for agents and this, you know, you're doing something similar in terms of the royalty. When you think about open ai, what they're kind of hinted at is that they wanna charge enterprise for agents that are not like software fees. If you think about software fees, they're per seat fees. And by the way, OpenAI kind of screwed themselves and the whole industry, I think by charging 20 bucks for chat GPT, 'cause it's set
[00:08:30] Henrik Werdelin: Hmm.
[00:08:30] Greg Shove: A floor, and a ceiling at the same time that AI was worth 20 to $25 a month in that range, right? Enterprise AI costs a little bit more, but not much more. When you negotiate with discounts, you probably get it for less at volume. So they really kind of hurt themselves, I think, in the industry in terms of really for a lot of value, for a lot of capabilities.
[00:08:48] Henrik Werdelin: when they're now selling a hundred dollars kind of access, It's really like you'll buy like a hundred dollars MBA agent instead.
[00:08:54] Greg Shove: Yeah, well they're, they're saying they're gonna cost between 2000 and 20,000, and that's, that's what they kind of indicated a few months ago. And maybe they're kind of spit balling on future pricing and future products. I don't know if they can get away with that. It's still software. So if I'm the buyer, not sure that I'm gonna let you charge me a fraction of the human labor cost. That's what OpenAI is proposing or suggesting. Hey, this is an agent that takes the place of a human. You pay the human a hundred grand. So why wouldn't you wanna pay us 20 grand for agent that does just as well? That is a new business model. It may, may not work and they may may not even announce, you know, actually go to market with that. But you can see what they're trying to do. They're trying to reset the value of ai 'cause they set it at 20 bucks a month and sure they have a premium plan at 200 bucks a month, but it's still, still not sick of it.
Another example of the one is lawyers just think about all the guys in professional services. , It's the time and materials business model being switched to an output, business model. Paying for, you know, paying for output or outcomes versus paying for time and materials. Law firms know AI will make them dramatically more efficient. And they are quietly implementing AI and not telling their clients, or trying to at least not make it that obvious how much work is gonna be done by ai. Why? 'cause they don't wanna reduce their fees yet,
[00:10:10] Jeremy Utley: Mm-hmm.
[00:10:11] Greg Shove: enjoy this margin expansion in the short term. They're gonna lay off paralegals and they're gonna make their junior associates more productive with AI and all that stuff. Right. But the real disruption will be, the AI native law firm comes along and says, you're not, we're not, you're not, you know, we're not gonna charge you $20,000 to do a contract takes this many hours. 'cause it doesn't take that many hours anymore. Right?
[00:10:34] Jeremy Utley: So you talked about the, the, leadership perspective. What about kinda a day-to-day rank and file employees? What are the implications again on that, of that deflationary pressure on , what it means for work?
[00:10:45] Greg Shove: Yeah, the first thing you gotta do is war game it. The first thing you have to do is, acknowledge to yourself and your team. This is gonna happen faster, and even if it doesn't, why not be ready? So this might sound fantastical, this might sound very hypothetical and in the future, like, Hey, this whole, whole industry will change its business model from time and materials pricing to, you know, to outcome pricing or output pricing. But let's assume it happens in three years. So the very first thing you do is just war game. Get everybody in a room on Zoom, you know, in front of a whiteboard and just start doing scenario planning. What would you do? would you react? What would your pricing be? you were in a competitive situation for the first time in six months with an AI native version of your firm, or your product, or your service and the AI native guys were pricing it this way, would you do? Could you even compete? So the first thing you do in my mind is war game it scenario, plan it, and at least be ready, at least have a backup plan, you know, kind of in your back pocket. If this starts to happen, , you know, I'll start doing this. I'll start rethinking the product. I'll start rethinking the pricing. I'll get ready for kind of a different business model. The other of course, uh, uh, question is, should I do this? I
[00:11:59] Jeremy Utley: Right.
[00:12:00] Greg Shove: Right?
[00:12:00] Jeremy Utley: Disrupt ourselves. Yeah.
[00:12:02] Greg Shove: yourself. It's hardest thing to do. Who, Who, wants to do it?
[00:12:05] Henrik Werdelin: Hmm.
[00:12:05] Greg Shove: Which law firm. Which, which
[00:12:07] Henrik Werdelin: It must probably, I, I've read somewhere that Google's like AI kind of thing is just converting much worse than their normal kind of like, and, but obviously they have to do it. And so I. It probably would have like dramatic kind of internal conversation. They had dramatic conversations if they should do this or not, but they have to.
[00:12:24] Greg Shove: I mean, it, it, it is, it is terrifying, when you flow the changes through the business model at scale. It, it never looks good. A barter work. When I talk to consumers about those, you know,
the Google NI answers those summaries. Consumers love
[00:12:41] Henrik Werdelin: great.
[00:12:42] Jeremy Utley: of course.
[00:12:42] Henrik Werdelin: Let me just ask you another question. You were fast out of the gate. I think you probably was one of the first that made like a real robust training kind of module for people to kind of understand how to use all this stuff, and so good for you on that. Um, few questions on that. One is, what is the thing that. You've learned by now seeing a bunch of people kind of coming in and trying to, to learn this? What's your observation and maybe what are some of the advice based on that?
[00:13:08] Greg Shove: Sure. Two observations. Uh, one on the user side, if you will, the employee, one on the buyer side, the boss on the, on the, employee side. struggle finding their use cases fast enough, so. We are, able to get people more proficient, lower their anxiety, raise their proficiency. That's job one in terms of upskilling people, but they then struggle with finding their use cases. So a lot of our efforts in terms of our sort of training and change management are more focused there now. Get them quicker into the two or three or four use cases work that they'll get value from. Actually see a productivity gain, actually see a little bit of time savings, improve the quality of their output and so on.
And they find those gains faster at home. They find those gains faster with parenting advice, you know, therapy advice, travel planning with medical second opinions, you can see those really good use cases for home use. But at at work, it's harder
and
[00:14:05] Henrik Werdelin: Why is that? Is that just because people don't know how to think of product?
Yeah.
[00:14:07] Greg Shove: Yeah, I think it's just, you know, what does this thing do? How reliable is it? Am I really gonna use it to create a work product? And will someone judge my work product? and if it's hallucinated or is it cheating? Even though we still have some of those attitudes, I think, that are getting in the way at the employee level, which is, I'm cutting a corner, I'm cheating, I shouldn't be doing this. Or where should I be using ai? And, and, so I, I think that's still in the way that, that, that kind of attitude and anxiety around that. And also this idea of finding faster, a couple three use cases, we, you know, we're intolerant if we don't get a search result sub one second, know, we get angry. Right. And AI can take 30 seconds and then crap out.
[00:14:48] Henrik Werdelin: Yeah.
[00:14:48] Greg Shove: if you think about, so that in a work setting, if you're at home and you're, you know, trying to get a medical second opinion and you had to wait, you know, 30 seconds for a reasoning model provided you're gonna be patient, it has so much value to you at home to get a medical second opinion, that's good. Especially if you're panicked about something and AI can really deliver there at work, you know? Yeah. You don't wanna wait 30 seconds, you know, you're off to the next task, right? Your to-do list is endless. You're overworked, you're underpaid. now they're saying get good at ai. Now, buyer side. here's what's getting in the way. Just inflated expectations, inflated expectations. Leaders are not clear around that, plus leaders are not being clear around what's gonna happen. can't tell you how many leaders say to me, Hey, Greg, I need your help. Let's deploy, let's get high levels of adoption. I just don't want you or any of us talking about job loss. Like, Like
[00:15:49] Henrik Werdelin: Yeah.
[00:15:49] Greg Shove: you, think your employees are that stupid? come on guys. Like it's, it's not an easy conversation to have. I'm not suggesting it is, but but not having it
[00:15:58] Henrik Werdelin: Do you think that's the same reason that every time somebody brags on LinkedIn that they've done something with, uh, ai? About one third of the comments, I like, I'm gonna cancel you now because basically you give,
[00:16:11] Greg Shove: Yeah, Listen, this, this is no different than people putting cones, traffic cones on the top of Waymo cars in San Francisco to disable the, you know, the sensors right there. It's sabotage. And we're gonna see versions of this. We're gonna see everything from more direct sabotage to, you know, just disengagement, hostility on social media and so on. It's, it's inevitable
[00:16:33] Jeremy Utley: Yeah. Will you play through that job loss statement? You know, you say leaders talk about, please don't say anything about job loss. If you had a leader that said, say whatever you think is true, what's the message?
[00:16:45] Greg Shove: Yeah. I think the message is, is simple in some ways. This is the message. That I deliver to my team every few months as I encourage 'em to use AI more and more and more like AI everywhere. We want to be fully AI enabled. And we're obviously a small team, 30 of us at a and we're an AI company, so we should be. But uh, what I say is, listen, in a year, one of three things will happen to your team. Some teams will be smaller. We will use AI in that team. The team will be able to do, do more work and will make the team smaller. teams will be the same size doing more work. 'cause AI will enable us to do more work some teams will be bigger. This is not most teams, I think most teams end up being smaller, but some teams are gonna be bigger. Meaning if AI makes someone that much more productive and you want more of, of that. In your business, you want more of those people using AI Sales is the office example. If sales is enabled by AI to hit quota more efficiently, then I want more salespeople, not less as a CEO, I probably want more software engineers if AI makes software engineers two or three x more productive, which is, that's what it seems like it does. And I, my roadmap is always, you know, never enough. I, I've never got enough software built on time. I I want more software engineers, not less. So. I do think in some teams, in some companies, depends on companies, depends on the industry, depends on are you growing or not? Is your business maturing, flatlining declining, or is it growing when you're growing? AI will have less of a job impact and will, will, make everybody more productive and the 'cause the company's growing or the business is growing. But that's what I say and I, and what I say is, I don't know which teams, let's just be honest about it and let's just go in knowing that there's one of free outcomes here
[00:18:33] Jeremy Utley: How does that affect folks' motivation and engagement?
[00:18:35] Greg Shove: I think it's mixed, let's be honest. But, you know, if we don't talk about it and face it internally, again, it's not like they don't go home and talk about it to their friends or their spouse uh, or their partner. Like, it's on everybody's mind. you know, I've got a 23 year old. Kid who's an inside sales, uh, uh, rep at, at LinkedIn. Like, you
[00:18:59] Henrik Werdelin: Yeah, of course.
[00:18:59] Greg Shove: like, he's sitting around like, you know, they're using
[00:19:02] Henrik Werdelin: Yeah.
[00:19:03] Greg Shove: they're using GPTs that he reads about a, you know, drives on 1 0 1 and sees the billboards that say, you know, ai,
[00:19:09] Jeremy Utley: right.
[00:19:10] Greg Shove: or AI sales, you know, stop hiring humans.
[00:19:13] Jeremy Utley: Let's talk about that. Let's talk about the employee for a second because you mentioned earlier that they struggle finding use cases. Um, one question I have is is it a bandwidth issue? I think there's this pressure of you need to produce more, you need to be more efficient, you need to be more effective, et cetera. And then the question of how do I use ai? It's like I don't have the bandwidth to even consider it. Whereas at home when I need a second opinion, that's something that I will give. I'll stay up late to do that. Right. What are you seeing as the primary obstacle? I.
[00:19:43] Greg Shove: I. Think it's bandwidth., I think it's poor training. And by the way, we just finished our, proficiency and AI readiness survey. We do it every six months. I. We survey 5,000 knowledge workers, us, uk, and Canada. So we just did , the march, uh, report, and we're about to provide the readout to people. The proficiency levels have not improved in a year. Employee proficiency levels with AI have not improved in a year. I think
[00:20:06] Jeremy Utley: What's going on?
Yeah.
[00:20:08] Greg Shove: It's poor training. It's, um, uh, expectations that are misaligned, meaning we are deploying this and calling it software. It is not software
[00:20:18] Jeremy Utley: Mm-hmm.
[00:20:18] Greg Shove: does, its behave like software. No. Does this, does this look like ERP or CRM or marketing automation or, you know, pick, pick, whatever SaaS platform people are using in their day. And then we give them AI and say it's, oh, you know, copilot Pros is another piece of enterprise software we're deploying. It's nothing like software. And then you tell the employee when you use it, it hallucinates and, and, and sort of, you know, performs unreliably. So good luck with that. You know, like.
[00:20:47] Henrik Werdelin: Do you see any of the different levels of the organization understand or adapted better? Like is this entry levels understand it, senior management does not, middle manage doesn't, you know, want this to happen 'cause they kinda like did all the hard work and now like how do you see it plays out in, across the organizations?
[00:21:03] Greg Shove: a, great question. What the survey shows, and again, we'll release this soon, is that managers and above more senior are actually more proficient. My theory on that is they're actually getting better AI training. I hear this a lot and frankly, our clients section ask us for more in-person
[00:21:23] Jeremy Utley: Yeah,
[00:21:24] Greg Shove: trainings for senior, for the more senior
[00:21:27] Jeremy Utley: it's, it's more expensive, right? They can afford it. Yeah.
[00:21:29] Greg Shove: expensive. They can afford it. They want, and they want those leaders to model the right behavior, and they want them to be using AI at least to model the behavior and drive the change. And then they do like asynchronous, you know, video training for everybody else at
[00:21:40] Jeremy Utley: Yeah, why doesn't, why doesn't our, um, defensive driving course for AI work so well and at Scale,
[00:21:47] Greg Shove: right. So that, that's, that's part of the answer. Um, yeah, listen here, here's the good news. I if you're on the side of ai, consumers love ai. mean, uh, open AI will pass a billion users in the next few months. That is insane. and small business solopreneurs, side hustlers. And this is a revolution. And it's not not happening in the enterprise, it's happening,
you Know, uh, with consumers. Really, these
[00:22:17] Henrik Werdelin: And I think that's actually such a ding point. 'cause I think you read like about the Shopify CEO e sending out their memos and you see all these different things and a lot of people get like very excited about it. A lot of these, when I read them, I read them as kind of like letters of despair. Like I read them as kind of people saying, like founders and CEOs saying, I've been talking about this now for two years. Nobody's doing anything. Like, come on. Is that, is that what you observation too?
[00:22:43] Greg Shove: I think they're a combination of, there are two things. They're a cry of frustration, you know, like what I, I'm using AI every day. I'm getting value from, and I can't believe, you know, you guys aren't using ai. Shopify's a, a good size organization, right? 8,000 employees. Dueling goes smaller under a thousand. The latest one was Fiverr. Uh, you know, and what that CEO is saying, I think they're all expressing a degree of frustration and they're putting employees on notice. They're basically saying,
[00:23:12] Henrik Werdelin: Hmm.
[00:23:12] Greg Shove: I, I will, where I can use my lever points to drive this adoption, you know, carrot and stick. these memos kind of have typically both in them. So, hey, I want you to do this. I'm encouraging, it's gonna make you more competitive, it's gonna make the company more competitive. And by the way, it's gonna be in your performance review.
[00:23:30] Jeremy Utley: So this, this, um, this whole conversation here is making me think of your phrase, the AI class, Greg. And I know last year or 18 months ago when we talked, you talked about one key metric an organization should be tracking is what percentage of our employees are in the AI class. Can You talk, and it sounds like there's maybe a, a, a divergence in terms of where the rank and file are versus where leaders are. Can you talk about other observations over the last 18 months of getting folks into the AI class and what it looks like?
[00:24:00] Greg Shove: I still believe that in, in terms of that, your advantage to by, by being in the class and then the company's advantage if more people are in the AI class. And unfortunately it seems stuck as we just talked about, uh, at around maybe, maybe 10% for most organizations. Hence, these CEOs are getting frustrated. By the way, I wanna say one more thing about those CEO memos. There's something important that they're not saying. I mean, I, i'm, I'm gonna go long on Shopify. I'm buying Shopify stock.
[00:24:25] Henrik Werdelin: Me too. I'm in, I'm into show fire.
[00:24:28] Greg Shove: yeah, the company is gonna be smaller in two years, not
[00:24:31] Henrik Werdelin: Yeah.
[00:24:32] Greg Shove: people. So what Toby didn't say, and again, it's a tough thing to say, is that I've got 8,000 employees now and about $8 billion in revenue, and I think I could have $10 billion in revenue in two years and 6,000 employees. What wasn't said. So I want everyone at Shopify and all of these companies to read between the lines.
[00:24:52] Henrik Werdelin: when you then read all these, uh, LinkedIns, which you know, is tough not to sympathize with, you know, some people go, Hey, you know, it it's, it's easy to dismiss, right? You know, like, Hey, you try humans instead, and you go, yeah, but I'm also trying to run a profitable business. Um, is there more responsibility? And we, and we kinda like, maybe go like all the way back and saying, CEO has the responsibilities of what social media had. We obviously, nobody understood that when we took pictures of our food and put it on Instagram, that that will kind of destroy like a, a lot of mental health, like. People didn't think about it and then business models and structures and things like that kind of made it less advantage for people who like mental health, like in the same Van Lane. When you have toby's and people listening and myself and other, like who kind of have a position where they can do those change, how much do you think they have a responsibility also to say, yes, I realize I'll be able to cut some head counts, but I also kind of need to do this in a way that's kinda like, say mad.
[00:25:51] Greg Shove: I, I think they do, but I'm Canadian, which means in America I'm accused of being a socialist. Uh,
so
[00:25:58] Henrik Werdelin: from Denmark, so I, I I, I hear you.
[00:26:00] Greg Shove: listen, there, there is gonna be some very hard downstream impacts of all of this. Job loss is already coming. The data we're now seeing, this is what's different than from when we talked 18 months ago. We are now seeing some real job data, right? Washington Post report about programmers. who are not software engineers, right? The level below programmers in the United States, $97,000 a year average, , income. That, that, that class of technical worker has seen a significant, contraction in open positions in the last two years. So we know what's going on there. Derek Thompson, the Atlantic reported this past week around the, the, you know, recent college grad, sort of hiring, you know, disparity, I guess, or, or slow down when compared to other ages in the, knowledge workforce, the implication being entry level jobs for college grads being impacted by ai.
I don't, I think that's more of a assumption versus we actually have the data that proves it, but it seems to be indicating that, so let's listen. This is coming and, uh, every time I suggest that companies have some obligation to. They're gonna become more profitable. Do they have some obligation to the employees that are impacted, you know, here in, in, the, in the US I get blank stares. I get it. That's not the purpose of capitalism. It's not the purpose of enterprise You know, purpose is to profit, maximize, as you said, pur is to deliver shareholder returns that are outsized. And so reserving money or training programs or whatever it might be to support those who are impacted this, it's not gonna be, gonna be in most companies plans. And, and frankly, uh, therefore, who else? The government. I, I just don't think we have, currently governments don't want, wanna deal with this 'cause they've got their own challenges in terms of budgets and, and we wanna pass tax cuts. So you, you wanna pass tax cuts, you wanna shrink government. do you want to handle what's about to happen? The AI industry doesn't get, know that. So in terms of who's creating this technology and deploying it and pushing it, the AI industry, they're not gonna sign up to, to, to, to handle any of the implications of this. They're signing up to make a shit ton of money and become the most powerful and influential companies in the world. That's all they care about. Sam Altman's not trying to cure cancer, right? And, and he still doesn't care about the workers that get laid off. Uh, so I, I'm not sure what the answer is. Uh, obviously you can tell,
uh, I, I'm worried about the, about the implications. And as a minimum, I think our responsibility as CEOs at least get everybody into the AI class, at least get them ready for what's about to happen. And then if they do leave your organization, either by choice or not by choice, they're at least capable to work in the age of ai. I wanna say one more thing, Jeremy, I think I was wrong about the AI class, meaning I thought it would be, uh. So those would be in it and those would be out, out of the, and those in it had an advantage. We're all gonna be in the AI class faster than I thought. So
this idea, this meme, right, that went, that went around for the last two years, you won't lose your job to ai, you lose your job To someone who uses ai, that was bullshit. losing our jobs to ai. Being in an AI class will not be enough. Being able to work with AI is gonna be a mandatory requirement, I think, for all knowledge workers, but it won't distinguish or differentiate you or save you in any way in terms of companies are going to deploy these technologies as fast as they can to expand operating margins and create business advantage. And frankly, the recession that we're in, if we're uh, or about to be in, depending on what data you look at caused by the current economic uncertainty will be the best thing for the AI industry. Not so good for workers, but it will accelerate the deployment of ai. Every CFOI talked to, I spent last week in New York
as a minimum, backfilling has stopped in terms of hiring. New hires are on hold. You know, we're, we're at the beginning of what is going to accelerate, which is the recession will induce CEOs to double down on ai, try to push through all these deployment challenges drive operating efficiency.
[00:30:22] Henrik Werdelin: do you see any, um, kind of industries. That goes through your classes more than others? Is there like any pattern in kind of who is grabbing on this? You say service industries of course have a lot to gain and to lose. Is that that the people coming through or is it just whoever, CEO kinda like, like newness.
I.
[00:30:40] Greg Shove: everybody. I, I would say that we are our client. Basis of a mix of small, more ambitious, more aggressive, , organizations, less concerned about risk, less concerned around data leakage and, you know, and those kinds of, uh, concerns or issues. And then, big kind of a barbell, we have very large organizations that are just very committed and frankly, many have failed in phase one or, or their first deployment basically landed, you know, with a thud. They deployed this like software, you know, the CTO or the VP of it was, it was a technology initiative. They bought it, they paid for the licenses, they deployed it, and there was no training. There was no change management, there was no AI champion program. They, they weren't like Moderna and these other organizations, and obviously, you know, Bryce, you know, they didn't have those kinds of people really driving, uh, adoption. And it's kind of failed. And so we
[00:31:34] Jeremy Utley: Hmm.
[00:31:34] Greg Shove: called at that moment, which is, we're looking at our dashboard and 5% of employees are using this thing, but it's costing us $3 million a year. You know, what do we do now? And you basically have to restart and do the hard work. It's not rocket science. The good news, if you're the leader, this is not rocket science. Making the AI is the rocket science part. You know, we're not making the ai, this is chain management. This is, you know, the, the, a lot of this we know how to do. just hard
[00:32:01] Jeremy Utley: What do you do there? Say you're the CEO, say you you've got a failed first deployment. , You treated it like a tech initiative. There's no change management, no training, as you said, and you're at this, this pivotal moment. What are, what's the playbook for the first three or four actions to restart on solid ground?
[00:32:20] Greg Shove: Well, uh, you need some goals. So re just reset. First of all, reset, reset the plan. What level of adoption and weekly clear daily active usage are you targeting in what period of time? So, take a 12 and 24 month time horizon if your organization is larger, over a thousand employees. If you're under a thousand employees, you should do all this in a year and you have no excuses. , And you'll be held responsible if you don't do it. Uh, add this quickly. 'cause you know, your organization will suffer either from a, from an operating margin perspective or from a competitive perspective. Over a thousand employees takes a little bit longer, but not, but not that long. That's the first thing. Second thing is, and you guys, you guys talk a lot about this. You need to have a point of view about ai. You need to have a manifesto, not rules. You know, AI governance, AI policies, depress usage.
[00:33:04] Jeremy Utley: Yeah.
[00:33:05] Greg Shove: that, that that was the point of them. You know, if you brought your general counsel and your ai, you know, technologists come up with the rules, you know, that that was stupid. 'Cause they came up with a bunch of rules that just, scared people from using AI and they couldn't put data into the ai and they, you know,
[00:33:22] Jeremy Utley: Right.
[00:33:23] Greg Shove: so you gotta reset that.
[00:33:25] Jeremy Utley: Can we double click on resetting that? I mean, I realize just to, just to put a bookmark, we're in number two and there's more. I know, but say more about that because I see so many organizations say we can't do anything until we have our policy in place. And so I just, I want you to double click on that point.
[00:33:40] Greg Shove: I, I say the first thing, uh, you need to know, or we all need to know, is there is little risk if you're using enterprise ai. So if you are, or even the teams based ai, meaning chat GPT for teams, or Claude for teams, or products in the last couple years have been built to be enterprise or company safe. Certainly the enterprise versions that if you're buying that from OpenAI or Microsoft, know, a lot of the concerns around data have been dealt with in the technology. Now, you might not trust big tech you, you know, you might not trust that they're not gonna change their business models later and use your data in a way, you know, that you didn't necessarily think they would today. That's fine, that's a different issue, but this idea of your data is gonna be leaked into the model or, you know, and I hear that still excuses and I think they're just
[00:34:29] Jeremy Utley: All the time, all the time.
[00:34:31] Greg Shove: I'm executives saying, oh, I'm not sure it's safe, and, you know, no, that's just bullshit.
[00:34:35] Jeremy Utley: But so you've got a policy or, or the legal team has written something up. Right? Well, how do you shift from policy to manifesto as a leader?
[00:34:43] Greg Shove: You have to say to your team, this is not cheating. You have to say that working with AI is working smarter. You have to say that we want you doing this. We have all these deeply held cultural beliefs about work. Don't cut corners. Hard work is the virtue. Right. Don't cheat we've gotta shift all that. 'cause right now, for a lot of people it sounds like it's cheating Using ai, it sounds like you are getting an unfair advantage. It sounds like. It's not my work and I need to be credited for my work 'cause that's how I get promoted and so on. Right.
[00:35:20] Jeremy Utley: Hmm.
[00:35:20] Greg Shove: we, you just need, as a leader to, to, to be really clear around you want people to be using ai, it will have some downstream impacts. Which will include people's jobs will change, though. We're gonna create some new jobs for sure. I'm not worried about that over time. There's all kinds of jobs that, you know, we don't do today that we're gonna create and do with AI in the future. So there's gonna be all kinds of new jobs created, but there's gonna be some stuff in the transition that's little more painful. So, you know, we, we, just need to model that behavior and talk about it in terms of, let's use ai, make the organization more efficient. Let's create some new products.
Like let's have fun with it. Let's outsource the drudge work. of a cliche, but it's true. Like, I can't tell you how many little use cases for AI that we see at, at, at my companies where, yeah, you're not gonna do a press release about it, but the team or the individual that's figured that workflow out
[00:36:14] Jeremy Utley: Right.
[00:36:14] Greg Shove: outsourced that eight hours of
[00:36:16] Jeremy Utley: Hero, hero.
[00:36:17] Greg Shove: And they're happy.
[00:36:18] Henrik Werdelin: And how much of the, uh, well, you, you mentioned, how many people using AI in your organization. I think for many companies, increasingly that's kind of like not a solved problem, but like there's something of that is the next level. Then how many agents do you have deployed or like, how do you see if like the next level of goal setting?
[00:36:37] Greg Shove: Yeah, I, i'm smiling about agents 'cause uh, you know, don't get me started. Um,
[00:36:43] Jeremy Utley: Oh, oh, please, by all means, start by all
means.
[00:36:46] Greg Shove: I, there's a step in between. I wanna talk about a step in between, then we'll talk about agents.
[00:36:50] Henrik Werdelin: Step three then. Okay.
[00:36:51] Greg Shove: So the, the step in between is what we call workflow redesign. So I do think that there are two ways to deploy AI successfully in organizations of any size.
And I would suggest everyone should do both. Either at the same time or one after the other. The first is give everybody a full featured good ai. So not some crippled old model, but give them, you know, Gemini 2.5 Pro. Give them copilot pro, right? The upgraded paid version. Don't give them bad ai. Give them good ai, uh, that, that's the first thing. And train them. Support them with change management with an AI manifesto that says you encourage and reward and value people who use ai. I call that. So the bottoms up. More organic use of ai. You, and then aim for 50% plus adoption levels within 12 months, at least 50 in an organization under a thousand employees. Adoption defined initially as weekly active usage and then then daily active usage. That's part A, or that's the first, you know, second redesigns. Take a team of people, one or two in a small org, maybe more in a larger org, and go into teams, people and decompose their workflows. Write them out, like literally describe these workflows on paper, the inputs, the outputs, the dependencies, and the data required to make the workflow to create the outcome or output, whatever it's human only, describe it, then redesign it, see which ones AI can help with. Prioritize that list. You'll have a hundred or hundreds of potential workflows that can be redesigned with ai. That's the good news. Hundreds of, of potential use cases, overwhelming. That's another reason why, uh, employees struggle with ai. Back to your question, uh, Jeremy, , you know, at, at the outset, they, they struggle in part 'cause the, the software, 'cause it's not software is so performant. It does so many things, but nothing really perfectly, Again, it's not like software, but it does so much that people get confused, well, where do I use it? Same thing with use cases. When you kinda look at your, human workflows or human use cases, you'll get hundreds in a typical knowledge workforce organization. Then prioritize five or 10 or 15, pick a number, prioritize them, redesign them with ai, codify that redesign.
How do you codify it? Well, you build a prompt library, build a one hour seminar and show everybody how to use AI to do that workflow in the new way, build a GPT or in Microsoft, that's called Microsoft Studio. Uh, you know, uh, build off the shelf bot or an agent. So, yeah, I think we are moving to agents. I think they're overhyped. is what the AI industry always does
[00:39:48] Jeremy Utley: Mm-hmm.
[00:39:48] Greg Shove: existing product doesn't work very well, and it hallucinates like crazy. They're like, oh, don't worry. Agents are coming. You know, they're, they're always doing another. It's, It's, it's, a playbook. Tech is always used.
[00:39:58] Jeremy Utley: It can't, it can't quote a document that you give it, but don't worry it will outsource. Yeah.
[00:40:03] Greg Shove: Exactly. No. And
[00:40:03] Jeremy Utley: But.
[00:40:04] Greg Shove: account will solve for all this, and
[00:40:05] Jeremy Utley: Before. Before agents, though. Before agents on, on, you know, call codifying and redesign workflows. When we last spoke, I think OpenAI just earlier in the week or the previous week, had launched the GPT store, which say what'll about store, forget that, but the capability to codify workflows. What impact have you seen of that ability on adoption? Because I'll just tell you my expectation. My expectation was it's gonna transform adoption. I've been surprised that it hasn't.
[00:40:35] Greg Shove: , I share that sentiment, meaning I, I think some organizations have been able to really leverage GPTs. We have at section, and we, you know, you and I both know about Moderna and they, they talk about hundreds of, gPTs deployed. I interviewed Michael Domini, uh, from user testing recently, and he has a lot of GPTs deployed internally at user testing. So I, I, think some organizations have figured out they are a great way to codify, , AI assisted workflows. But, uh, it's, it's been, it's been a struggle. It's been slower, I think for people to realize their power, uh, and then to deploy them. They're also, in some ways hard to deploy, like who builds them, who manages them. If you think about an organization, again, for an individual, for us, for solopreneurs and, and startups, they're easier to, to, kind of build and deploy. And if they, if they break, it's not a big deal. You go back and fix it. When you think about GPTs, like,
[00:41:25] Henrik Werdelin: how do you create authority in them? right. You know, like we have five brand bots internally.
[00:41:30] Greg Shove: Exactly. Things like that. It's kind of the wild west, right? So, you know, I could imagine a lot of heads of technology or it are like, no, we don't want those things running around. They're, they're like these little bots and, and, and yeah, there's different versions. And then the person who made it left the company and now this bot's like,
[00:41:44] Jeremy Utley: Right.
[00:41:45] Greg Shove: people are using it and like, who owns it? So i, I think it, it was, love the idea I was gonna build a thousand GPT and stick them in the, in the GPT store and own, own that real estate. Like I, I bought that hook line sinker. I love that idea. Hey, this is like the Apple Store 2.0 and the early
[00:42:02] Jeremy Utley: Yeah.
[00:42:02] Greg Shove: store gonna win. So I was gonna build a thousand GPT overnight, and I said to one of our board members, I'm thinking about doing this. He's like, are you outta your mind? , This is like a concept, this idea of a gPT app store. Like, dude, like slow down, like wait, a bit like, figure out is this really gonna stick? Then when you get more signals, you might wanna jump in and, you know, put a thousand gpt in the app store and see if you can turn that into either a lead generation or a revenue stream. Anyway, we never did, obviously we didn't build one GPT or we built a few and stuck 'em in the app store. The rest we use internally
[00:42:35] Jeremy Utley: Mm-hmm.
[00:42:36] Greg Shove: love em. You know, listen, agents are coming, the big reason agents are coming is, uh, is AI industry open, AI in particular, but all, all of them have realized a couple things. One is these applications really are what's driving the value. The models aren't driving the value, right? Then the models have all really been commoditized. So what's really different from 18 months ago is the frontier models of all converged basically with the same set of capabilities. So it is in fact the application layer where the money's gonna get made and where adoption really happens and the business value is generated.
And if you think about chat, GPT, what it is, is the first AI application to get to a billion users. That's what Chad TT will be.
And that has really opened everyone's eyes to no. The way, we win is you build applications you drive adoption of applications and applications essentially to some extent over time. Take the human out of the loop. So agents are the next generation of AI applications. The AI industry wants them, 'cause humans are getting in the way of deployment. This might save us ironically, Our, our challenges with adoption. Our challenges with using
[00:43:45] Jeremy Utley: That's fascinating.
[00:43:47] Greg Shove: actually be something, know that we need, it's slowing AI down inside of our companies.
[00:43:53] Jeremy Utley: These pesky humans are keeping us from deploying ai
[00:43:57] Greg Shove: Right. They're getting in the way. So,
[00:44:00] Jeremy Utley: Well.
[00:44:00] Greg Shove: for your open AI because you've raised so much capital, you're burning whatever it is a minute, you know, in terms of compute,
[00:44:06] Jeremy Utley: Yeah.
[00:44:07] Greg Shove: and energy. So agents are a way to take the humans out of the loop and are a way to deliver to enterprise, larger enterprise where adoption is really stalled out in terms of chat bot adoption or LLM adoption. Let's bypass the humans, take 'em outta the loop, generate the business value, extract that business value. If you're open AI in whatever pricing model you can come up with that sticks, uh, and, you know, we're all gonna be happy. At least the CEOs will and the, and the, and the builders and providers of the agents.
[00:44:35] Jeremy Utley: You actually, you kind of, I feel like, um, you foreshadowed agents a little bit even in our call 18 months ago. I don't know if you remember this, but you talked about at section, you're an educational organization, but you, and we kinda shared some cynicism about people's desire to learn. Right? And specifically you mentioned somebody doesn't wanna learn how to create a strategy, they want a strategy. And you talked about shifting from a class that teaches folks strategy to, I don't know what words you used, copilot, whatever. That actually just delivers the strategy. Talk about how your offering is changed based on infusing ai. Not as the subject matter, but as the, not the what, but the how.
[00:45:14] Greg Shove: Yeah. Uh, it's changed in an important way 'cause we've launched Pro AI two weeks ago. So Pro
[00:45:20] Jeremy Utley: Hmm.
[00:45:21] Greg Shove: is an AI powered coach and the only thing it's teaching and may, may ever only teach is ai. I, at this point, pro AI doesn't teach other things coach other things. It's coaching ai. So, pro AI is powered by currently the, uh, anthropic models. We built it initially on, , GPT, on the GPT APIs. Uh, now we're using, uh, anthropics models instead. We like the output better, and it teaches people how to get good at using ai Talk about disrupting ourselves. There's lots to talk about with this. The, the first thing I wanna talk about is it's an amazing learning experience.
It is because it's personalized almost from the first moment. So when you play with an AI powered learning experience, or an AI powered coach, or an AI powered tutor, I think it, the first time you do it, it is, it is one of those magical sort of technology experiences. Like, like playing with chat GT was, you know, two years ago when we all first started doing that.
Because right away the coach or the tutor knows who you are. So the exercises in content inside of the experience are immediately customized for you. 'cause you tell it where you work, what job you're in, what country you're in, what level you're in, you know, in the organization. And right away profit AI starts to work with you and coach you knowing who you are.
It really is amazing. There'll be no value in video-based learning in a year or two. I mean, chegg is dead, the rest are going down. You know, uh, Udemy, Coursera, Skillshare, Skillsoft, you name 'em. Anybody who's made a living producing video-based learning content and then asking people to watch it inside of
learning management systems, all those companies means, you know, uh, there won't be around. these experiences are magical. The, The, AI powered ones, the content's generated on the fly, the content is personalized, the content quality is high. And it's not just content. It's actually giving you exercises. It's producing, in our case, profit AI produces prompts with you, works with you
[00:47:27] Jeremy Utley: Right.
[00:47:27] Greg Shove: the prompt, so you get the output. You don't get the, you know, you get the learning, but you get the output. You wanna learn how to prompt and you actually want to cut and
[00:47:34] Jeremy Utley: The prompt Yeah.
[00:47:35] Greg Shove: it into the ai, right? You
[00:47:36] Jeremy Utley: Well, and that's, that's, that's, kinda what I was wrestling with even as you're talking, because as at least, and maybe this is feedback or whatever, but when you start talking about it, it's still a teaching tool. And maybe that's what, maybe there's this want versus need. Right. I think people want to, to, to be a lifelong learner. But people don't need education. They need the output. So you, so is the package teaching, because that's what people think they want, but really the, the, content, so to speak, or the, the, the, sugar inside of the wrapper is actually the output, because that's what people really need.
[00:48:07] Greg Shove: I think it's both. I think people don't want really to learn. Frankly,
there's very.
[00:48:11] Jeremy Utley: yeah.
[00:48:12] Greg Shove: few lifelong learners out
[00:48:13] Jeremy Utley: Uhhuh, Uhhuh.
[00:48:14] Greg Shove: no. It's, it's a mix of this is what we could deliver today. and it's, it's, it's presented more as a coach, I'd say. Uh, it's sold to, our enterprise customers, uh, as a learning experience. Cause that's how enterprise buys upskilling. They buy it as a, as a learning experience primarily. But you're right, what people really want is get me faster to prompting and working with my AI to get good outcomes from my ai. So, uh, and ultimately, profit AI or, or other learning experiences should be living inside of the AI almost, if you, if that makes sense, li like, living inside of the chat bot. We can't do that. Prop AI is a, you know, it's a separate experience, but you can certainly sa save your prompts from Prop ai. You can cut and paste them over to GPT or cloud, whatever LM you use. Uh, and eventually we'd like to make that integration as tight as possible so that you Yeah, you're working and learning at the same time, essentially, which
[00:49:07] Henrik Werdelin: at the last conversation you also mentioned, uh, you were the first that I heard talk about taking your board decks and then basically synthetic role, play it out before, uh, you had what We still doing it. Learn something new. What's the, what's the latest board management track?
[00:49:22] Greg Shove: We did it last week. Uh, I'd say , this is what's newest but different, uh, from 18 months ago. So Claude used to be top of leaderboard for the last, 18 months. You've done it. Now I 'cause six or seven board meetings. So, uh, GPT oh four, uh, jumped to the top of the leaderboard.
[00:49:36] Jeremy Utley: Not oh three, just oh four.
[00:49:38] Greg Shove: For some reason, yeah. We used, yeah. And, and maybe oh three could have as well. I dunno. We used oh four, uh, this month.
and yeah, Claude was close behind. Yeah, we still do. It's great. Uh, I.
[00:49:49] Henrik Werdelin: And then on the, on the using, maybe that's a little bit of a jump, but do you have, like, you're a monitor with the three different kind of like foundational models? We talk about 3 0 4. What's your go-to kind of mental model for? Should I use deep seek? Uh, deep think, should I use research? Should I use ideation? When do I go to gr You know, what do I, what do I image generate with mid journey? Where do I, how do you, what's the go-to navigation structure?
[00:50:15] Greg Shove: I get confused like everybody else. I mean, the, I mean, if you, if you, had to do a a, case study on the worst go-to market strategies in the history of technology, it would be the
[00:50:27] Jeremy Utley: Mm-hmm.
[00:50:29] Greg Shove: would both win the worst award
[00:50:31] Jeremy Utley: Well, Google's right there. Google's right there. I mean, it's terrible. It's terrible.
[00:50:35] Greg Shove: marketing, in terms of naming, in terms of, uh, conventions and so on. Yeah, I, I get confused. You know, I, I, when I think about bigger projects, I think about deep research. When I think about everything else, I think about GPT or, or cloud then perplexity for research. Uh, but frankly, I'm, I'm confused. I'm very frustrated.
[00:50:50] Henrik Werdelin: Is. Sometimes you even don't even know, right? You're like, okay, remind me, is oh three better than four? Oh, is that.
[00:50:57] Greg Shove: I
[00:50:57] Jeremy Utley: No, it's, it's absurd.
[00:50:59] Greg Shove: it. Sam Alvin's talked about it. They, they need to bring it all under one, kind of product umbrella. But I wanna go back to profit AI for a sec because I wanna talk about, uh, business model disruption. Just,
[00:51:06] Jeremy Utley: Please. Yeah, no, I love it. Love it.
[00:51:08] Greg Shove: here's what's, here's what's crazy about profit ai. It's a, takes about an hour of conversations with profit AI to become very proficient in ai. And because we're measuring you, right? We, you're doing exercises, we're grading you, essentially, it's a, so the time you get completed, you're sort of certified as aI capable. and then we, we, uh, you know, auto release, uh, a LinkedIn badge, if you want one to your LinkedIn profile takes about an hour. The, so that, those conversations, the tokens, the AI cost, the inference cost of that for me is a dollar, $1.
[00:51:49] Henrik Werdelin: That's crazy.
[00:51:49] Greg Shove: So let, let's, let's, uh, you know, put that in context. We charge section $750 a year for unlimited access to the AI Academy, to consumers, and we absolutely discount that. So our, our probably net selling price over the course of the year is probably closer to five 50, something like that, right? Seven 50 is the list price for unlimited access to the AI Academy, which includes all live sessions, and then anything that's recorded and some other benefits, right? We have a Slack channel and we have other community and, and, and benefits and assets. So it's not just the, , courses, but the, core value proposition are the ai, is the AI academy, the courses. So seven 50 bucks discount to 500 profit AI can do most of that, not all of it, not yet, but it can do most, it can't do the community, but can certainly do, you know, the upskilling, uh, the learning, the, skill acquisition hours or less for the average student, and it costs me a dollar.
[00:52:47] Henrik Werdelin: How do you press it right now?
[00:52:48] Greg Shove: Oh, I don't price it, so, so, it's a combination of I'm not sure what to do
[00:52:53] Jeremy Utley: Yeah.
[00:52:53] Greg Shove: frankly, I want enterprise leads. So here's what I'm doing right now. It's gonna be free. It's gonna be free to consumers. our members who are paying hundreds of dollars a year will get profit. Ai, obviously included in their membership, I'm betting what they're really paying for is access to the live events, the live lectures and workshops and so on. If they just want the upskilling, if they just want the skill acquisition, then AI is gonna be free for everybody. All consumers are gonna be able to use profit AI at no cost. That's my launch strategy I'm launching in a couple weeks. I launched the enterprise version a couple weeks ago. The consumer version's gonna go out as a freemium version. So I'm doing that because I can bear for now the inference cost of a dollar. If we
[00:53:40] Jeremy Utley: Great.
[00:53:40] Greg Shove: of users, I'd be like, oh shit, I need some capital. You know, I gotta fund the inference cost. , But for now, it feels like the smart thing for us to do in terms of getting, , it out there, frankly, helping others get ready. It's a mission. That section as, as you said, Jeremy, to bring a million people into the AI class. I don't think that'll be enough, uh, to kind of save you, so to speak, in terms of your job if your job changes. But you need to be in AI class as fast as possible. So we want prop AI in as many, you know, many people's hands as possible. It's gonna help them, we hope, uh, upskill themselves. But yeah, listen, if I was an AI native startup, I'm not. Right. I'm an incumbent with an old, and I'm a digital incumbent. Uh, now with an AI product that coco a dollar to deliver a tremendous amount of value, uh, to the student or to the employer that might be deploying profit ai. So this, this is my point around disruption, from a business model perspective, these are gonna be very significant business model disruptions. And so, uh, you you gotta do it to yourself or at least be ready when someone does it to you.
[00:54:42] Jeremy Utley: How did you decide, how did you, how did you as the CEO of an incumbent digital player, how did you decide? Because what I'm hearing you say, just to read it back to you, is we decided to disrupt ourselves, or we decided to at least get in the self disruption game. Walk us through your thought process. I
[00:54:58] Greg Shove: I think it was, uh, I don't know, three inputs probably. One is what's our mission? Why are we even doing this? I don't, I don't need to be doing this for a living. This is hard. running a, you know, a, a startup. That's that. You know, it's got ambitions and not enough capital and, you know, , investors that are expecting a high return and all that stuff, like, you know, it's not exactly easy running a startup.
So like, why are we doing this? Uh, I don't need to be doing this. I'm doing this 'cause I want to help as many people as possible get into AI class. That's our mission. How do I get to a million people? How do I help 2 million people? It wasn't gonna be through what we were doing. It wasn't scaling fast enough.
We had to create something with much less friction. Much, much more accessibility and very high value. And that's, that's an AI learning experience. That's the first thing. Second thing is, I could not look myself in the mirror in two years and say someone did it to me. Like I had the insight. It wasn't
[00:55:48] Jeremy Utley: Hmm.
[00:55:48] Greg Shove: I was clueless if I was gen, but genuinely, if I was blindsided, if I hadn't seen the future. You Know, if, if I was in my own tunnel or whatever, you know, and not seeing the future, then okay, I got blindsided. That's on me. But I, I had the insight, someone was gonna do this, so I could not look myself, my investors and my employees in the eye, you know, in, a couple of years or a year and say, listen, you know, we didn't act and someone else did it to us
[00:56:13] Jeremy Utley: Hmm.
[00:56:13] Greg Shove: else had built profit ai, and we didn't. I mean, to your point, we were early in AI training, like 18 now, two years ago. So give up all that advantage and have some, you know, two dudes and a dog and an AI in a garage. , Beat us with their own AI tutor. Man, I, I, shame on me like I just, I, that that wasn't gonna happen. thing is I have an amazing board. I have amazing investors. , And we're aligned. We're aligned that this creates risk and significant opportunity. And so, you know,
[00:56:47] Henrik Werdelin: That makes a lot of sense,
[00:56:49] Jeremy Utley: The question of testosterone for my brain, one. thing that I'm particularly interested right now in Greg is. The tendency of older folks. We actually talked with Evan Ratcliffe, he's a podcaster, amazing guy. He's got this great new podcast and he referenced the fact that it's a consistent theme throughout the history of humanity and technological process to resist change. I think AI is particularly well suited to experienced individuals because they have more context. It's like in an MBA class, right? The experienced person gets a lot more out of the class than the person straight outta undergrad, right? The same is true in collaboration with ai. More experienced individuals actually have far more context to glean better outputs from it, and yet the tendency is to opt out, checkout, say, uh, or resist. Right? And your comments about AI being testosterone for your brain, specifically in regards to call it cognitive decline, that's been on my mind. Have you learned anything or seen or observed, or felt differently about that as a kind of a concept or paradigm in the last 18 months?
[00:57:52] Greg Shove: Here's where I've ended up on, on how we think about using ai. I think there'll be two types of AI users. This is what's of most concern to me right now, which is we'll all be cognitively offloading. I. Because we always have, right? We've always looked for these edges and uh, you know, we used to be able to recite the Bible or the Koran from memory.
Humans used to be able to recite home Resili ad from memory, 15,000 lines of text from memory. And then books came along. And so we cognitively offloaded the books, right? And used that cognitive capability for something else. GPS is the obvious example today, right? We used to know how to, you know, navigate that part of our brain has actually been electrifying. Kinda that, that spatial sort of mapping capability. 'cause we rely on GPS, we've cognitively offloaded that part o of our brain to GPS and, and on our smartphone. So this is the mother of all cognitive offloading tool. This is like, we've never had this before. So we are gonna use it and we should, we should all cognitively offload as much as possible. Borrow those 30 points of IQ at any age and, hopefully get the gain. But I think what's gonna happen is there'll be two types of people who cognitively offload freeloaders. Managers, and I think most of us sadly, are gonna be AI freeloaders. We are gonna be lazy. We're gonna cut and paste from ai, we're gonna take AI's work and call it our own. We're not gonna add what's unique and different and special about us and our experience and our judgment to the AI's work. We're just, we're just gonna use it to, to cut the corner, get home, you know, put the kids to bed, walk the dog, and watch Netflix.
[00:59:33] Henrik Werdelin: So the poster won't be, remember to use ai. It'll be, remember to use your brain.
[00:59:37] Greg Shove: absolutely. I, I, think, we'll, we're gonna have to develop new habits turn off the AI or work with AI and then. Improve that work and acknowledge and show the difference to yourself and to your boss. Things. I mean, I'm not sure how we're gonna do this, but we are going to have to not lose our minds. I wanna be really clear about this. Big tech wants us to lose our minds. They want us to be a hundred percent reliant on these technologies and stop thinking will make them the most influential and powerful and valuable companies and individuals in the world.
[01:00:22] Henrik Werdelin: So if you had one human skill that you think that we ought to train ourselves in, keep training, like we stopped having to, uh, run after animals in the forest, and so now we go to a gym, what's the kind of like the innate. Human skill outside, like the broad of thinking that you would, uh, go to the, mental gym for.
[01:00:45] Greg Shove: What's right or wrong?
I.
[01:00:49] Henrik Werdelin: I'll take that.
[01:00:51] Greg Shove: We must never lose that judgment. We must not offload that question, especially when the ais are run by companies that don't care.
[01:01:06] Henrik Werdelin: How do you think we, I don't know, like, but you, you run a company that teach people, how do you go through the process of understanding how to codify your own right and wrongness so that you can train it? Like how do you do that?
[01:01:23] Greg Shove: it's you, you need to write it down. I, I think we need to begin to describe ourselves to ourselves better. We need to stop, reflect on ourselves.
[01:01:40] Henrik Werdelin: So when we drift, we know that we drifted.
[01:01:42] Greg Shove: are our values? What are our operating principles? How do we make decisions like codify those, meaning write them down, understand them. Make sure you align your AI to those, this idea that, that, you know, 200 million young men are gonna be using X ai, that's not comforting to me. 'Cause X AI's positioning in the market is it's got no guardrails.
[01:02:09] Henrik Werdelin: yeah. Yeah.
[01:02:11] Greg Shove: I mean,
[01:02:12] Henrik Werdelin: Yeah.
[01:02:12] Greg Shove: they turned it off, but they used to have a, a feature called unhinged. Like this idea that, you know, that someone thinks it's a good idea
[01:02:20] Jeremy Utley: Rain.
[01:02:20] Greg Shove: to release an AI with a feature called unhinged.
[01:02:24] Jeremy Utley: I like that as a, I like that as a frame as don't be unhinged. It's our, don't lose your mind. I mean, there's something there that's actually really, really profound. Yeah.
[01:02:33] Greg Shove: mind,
[01:02:34] Jeremy Utley: and and it requires that we actually connect to our own humanity as a protection against our, our worse impulses. Yeah.
[01:02:45] Henrik Werdelin: This is awesome. Greg, you're awesome. Thank you so much for coming back on. I hope we can invite you back on maybe before 18 month and so that we can hear what,
[01:02:55] Jeremy Utley: We gotta hear, we gotta hear it. Uh, postmortem on the pro AI launch and hear how it went.
[01:02:59] Greg Shove: Absolutely. Yeah. No, we are looking at the data as we speak. It's fascinating.
[01:03:02] Henrik Werdelin: so Jeremy, so good to have him back on, huh?
[01:03:07] Jeremy Utley: I mean, so much has changed and yet so much remains the same. I thought that was a really, really fascinating, uh, insight.
[01:03:14] Henrik Werdelin: Do you wanna go first? Kind of what we, took away from this conversation.
[01:03:17] Jeremy Utley: I mean, I, I always challenge myself to take notes. Sometimes folks just, you know, Henrik tells me I can hear your pen in the background, but it's because I know that this, like passive vessel can only hold so much and I'm trying to capture it and it's.
[01:03:32] Henrik Werdelin: of wisdom.
[01:03:33] Jeremy Utley: It is the sound of wisdom being transcribed into stone tablets. Anyway, I took a ton of notes. Uh, there's almost so much my, my thing that I, that stood out to me is there's so many times I always know if it's a good interview because I pull out the highlight function, not just the pen function on my remarkable tablet. And I'm highlighting a ton of stuff here. I mean, it's so much that it's, I, I, it's, it's pages and pages. That's actually one piece of feedback I would've to remarkable because it's really hard to scroll through your notes. But, uh, I think one thing I would say, if I had to highlight one thing as I'm scrolling frantically, um, in the interest of time, the encouragement to leaders to shift from policy to manifesto and what he said, three things specifically.
It's not cheating. It's working smarter. We want you to do it. I think that is a message that is so sorely lacking. There's always a but but be safe, but don't, but, and it's the, but that is biting people's Achilles heel and keeping them from exploring and using, and I know a lot of leaders who say, yeah, we tell people to use it.
Just do it in a safe way. And it's the. Ambiguous fear of an amorphous risk that's actually holding people back. So that's, that's probably the biggest thing that, that resonated with me. What about you?
[01:04:53] Henrik Werdelin: You know what I have thought a lot about? A thing that he obviously framed much better. Uh, and so I put a, a kind of very, uh, distinct kinda like, uh, word on it, which is output outcome pricing. Um, what is it that you're going to, as an entrepreneur, be making. In the future. And I don't think that you can kinda like deliver content.
You can't just deliver text and you can't just deliver hours. You have to deliver, here's this thing you ask from the strategy or here's this outcome. You ask for 20% better conversion on your funnel, whatever. And so thinking in that way from day one, also even as a human, what is my output? How do I become better of doing?
That's interesting. And that kind of goes to the second one, which is, you know what I, I've meet a lot of people and you show them rep a lovable and you show them what agents can do and stuff like that. They have a very difficult time kind of converting The awareness of those things are there to something that they can then change in their work life.
And so I've kind of always put it into. People are just not used to thinking products. You know, people are used to thinking, managing their boss or, you know, the
[01:06:07] Jeremy Utley: but. Not products. Yeah.
[01:06:09] Henrik Werdelin: So I think what he was talking about was really how you learn how to think of use cases. How you really just take the time to write down your workflow and then you atomize them and then you figure out should these be redesigned or any of these components, are they able to be redone with ai, I thought was an interesting way of doing, but the whole thing about like, how do we become better of, of productizing instead of solving problems, uh, I thought was fascinating. , um, I do think. This kind of, he's so straightforward and honest. Right. You know, and I think this idea that , you won't get out competed by somebody, you know, a person with ai. We will all have to learn AI and there will be people who lose their job and they might find a new job. But like there is just, I don't think there's really any excuse anymore in most industry to not learn it if you want to have a career in the long term. And so I
[01:07:06] Jeremy Utley: Not even an edge, you're saying? Not even an edge, just a career.
[01:07:10] Henrik Werdelin: I just, that's what I think he was pointing out and you know, in many ways I hope he's wrong, but
[01:07:17] Jeremy Utley: Wild. Wild stat. Wild stat of the day. They just surveyed 5,000 knowledge workers. Employee proficiency has not improved in the last one year. That's staggering. Given that, I would say the last year has seen the most attention towards proficiency, that of human history.
[01:07:37] Henrik Werdelin: But it's also, it sounds like it might be the good news for everyone, because that's the thing that's gonna slow everything down. That and what Mark Zuckerberg in, in that YouTube video you sent me, which basically that it also should just take a long time to build hardware. Like build the centers. And so the two things that are slowing everything down is not the models, it's basically human's ability change and then
[01:07:59] Jeremy Utley: our, it's our neural nets. Yeah. That's great. All right, folks, if you enjoyed this episode, if you enjoyed this conversation, please use the safe word I.
[01:08:11] Henrik Werdelin: The safe word is right or wrong.
[01:08:15] Jeremy Utley: Right or wrong, right or wrong question mark. And no question mark.
[01:08:21] Henrik Werdelin: No question mark.
[01:08:22] Jeremy Utley: Ah, I see what you did there. Until next time, thanks for listening.