In this episode, we speak with Section's CEO, Greg Shove. Greg Shove is the CEO of Section, an educational technology company. Previously known as Section4, the organization was founded in 2019 by NYU Professor and serial entrepreneur Scott Galloway. Section, under Shove's leadership, focuses on being a new type of business school for the tech economy, catering to a growing base of students interested in this field. Greg brings an awesome perspective, having founded five companies, resulting in three major exits and being at the forefront of reinventing education. Together, we’ll discuss real-world examples of companies using AI-powered tools to increase productivity, boost efficiency, and improve the customer experience. This episode is filled with great tips for people looking to introduce the powers of AI into their company.
As an extra holiday gift, Greg has kindly given us a discount code to AI for Business Mini-MBA (led by Greg, coming up in January). You can use code BEYONDAI to get 20% off.
Greg: https://www.linkedin.com/in/gregshove/
📜 Read the transcript for this episode: Transcript of Greg Shove, CEO Section: 'AI is like testosterone for my brain'
[00:00:00] Henrik Werdelin: Welcome to this very first episode of Beyond the Prompt. I'm Henrik Werdelin, here together with my cohost, Jeremy Utley, in a podcast that explore our companies and leverage AI to streamline operations and better serve their customers. We're thrilled to have Greg unpack real world examples of using AI to increase productivity and making a better company.
So a very warm welcome to you and to be on the prompt. Here's Greg.
[00:00:25] Greg Shove: My career is the typical Silicon Valley career, 30 years of hard labor, no unicorns, some exits, good quality of life, financial security established for a family, not easy, lots of pivots, lots of heartache. Lots of dead ends. That's typical.
It's not what they sell us at Stanford business school or what the media, the myth that creates about building companies. But fired from Apple was from my first job out of business school here in, in, in us. I came from Toronto and after that serial entrepreneur,
[00:01:05] Jeremy Utley: just by way of background. If you want to talk briefly about your role at section and then specifically, I think where we want to go is.
What have you been trying? I know from our interactions that you felt real passion and purpose around being forward leaning with AI would love to understand maybe how you came to section when the AI moment dawned upon you and what were some of the early decisions you made and then we can take the conversation from there.
[00:01:33] Greg Shove: Yeah. Uh, great. Scott Galloway is a close friend. I've known Scott for over 30 years. He'd started the company, had raised a seed round and initially had launched the company as a media business. And I came on about a year and a half after it was launched and decided to pivot it to an ed tech business, maybe the second worst business model in the, in the digital kind of landscape.
But Scott's a great professor, a great educator, and I thought we could marry his abilities with. A lot of lives, uh, video based learning live, not asynchronous. So I felt that online learning hadn't yet fulfilled his potential. So that's Achilles heel was that still no one really wanted to do it. And no one really showed up and completed.
And the metrics for platforms like Udemy, LinkedIn learning, I think, confirm that over the last 10 years. And so I thought we could build a different experience. Without, you know, kind of a higher bar for the student in terms of learning outcomes. So we did that. We enjoyed an incredible growth spurt via the pandemic.
Amazing catalyst, right? Yeah. Amazing catalyst and a false signal to some extent, right? Like other companies that enjoyed that kind of boost, right? Uh, when it was over. There certainly was a hangover. We had raised a fair amount of capital, which we invested in marketing, but also in curriculum development.
So that money was well spent in terms of building out our curriculum. And, and here we are now really figuring out how to build a capital efficient, uh, learning business that will, that supports the enterprise. We, we still serve consumers and they're a great way to, to access, uh, happy consumers are a great way to access enterprise customers, right?
So we said that consumer enterprise flywheel. Diving
[00:03:12] Jeremy Utley: to the AI moment, you're on this journey, you experience the bump and then the hangover and all that. Where in the midst of that, can I call it CEO heroes? It was simple.
[00:03:22] Greg Shove: It was simple for me. The moment was I had decided this year. I'm two years cancer free.
I decided this year to work for 10 more years. And I hadn't yet decided with what level of intensity across the whole 10, but I decided to work, uh, intensely for the next five years and to, and at least somewhat intensely for the next five for a total of 10, I'm 62. And I realized that basically AI could be testosterone for my brain.
I realized that if I was going to be as productive as I wanted to be, I also set a goal of creating 10 million of additional family wealth for my kids and grandkids. And so when I made those decisions and then basically started playing around in December, January timeframe with AI, I thought, okay, you know, if I could combine my ambition and my experience with the cognitive boost of AI, then I'd have a chance, I'd have a much better chance of having a kind of making the impact and having the productivity and contributions I want to make over the next 10 years as Silicon Valley is as a tough game.
It's an ageist place, place, right? Uh, we discriminate against, uh, people over the age of 40 amongst others, not the only. So anyway, I just felt like it was a chance for me to add a superpower. So
[00:04:49] Jeremy Utley: what did you see? That made you feel testosterone for my brain. What was it? Do you remember the moment where you go, Oh,
[00:04:58] Greg Shove: it was two things.
It was the lack of friction to get an answer and my point of view. And this is one of the, this will be the, one of the lasting impacts, which the generative AI, or this chat interface, which was, will interface friction will not be tolerated going forward, right? We're going to expect, and we're going to have these sort of magical experiences where we get the answer.
That we are looking for, right. And in a way that just has less keystrokes, less cotton of load, less effort, less hassle. Right. So I think that, so the one, the moment was playing with GPT and where it felt like, okay, that was equivalent of four or five searches done in one. Right. And the second was quickly thinking about it as a thought partner.
So I went, I was able to quickly realize that it's not search. It's brain power, right? Or, and specifically for me, thought partnership and this idea of approaching something from a different angle. But by my age, you have a lot of bias. You have a lot of experience, but you have a lot of bias. You have a lot of set beliefs.
You have points of view and I just find AI so refreshing. Convigorating it in terms of allowing me to come out of a problem or an idea just from a different angle, right? Which is just harder to do as you get older, right? Our brains are less plastic.
[00:06:11] Jeremy Utley: I know we, we hate to admit it. Okay. So I see all that now, what I'd love for you to talk about.
And I know a little bit of the answer because of my experience with you, what was, did the organization see it immediately? Does everybody, is it as apparent as it was to you? We need to make a radical investment and exploration. Or did that require some leadership? And if it did, what did that leadership entail?
[00:06:38] Greg Shove: Well, it's the classic, it's the classic CEO. I've seen the future kind of moment. And everybody else is what? No, you haven't. You're an idiot. You're the guy that did three layoffs. Right. Like really you're the genius in the room. So absolutely had one of those moments, probably more than one. Right. And then the reality of this is everybody's got day jobs.
Everybody's busy. The team is lean, right? The capital's as less available. And so the team is smaller and working really hard. And this, this is more work. I frankly, the media doesn't help, even if you're in Silicon Valley. But if you're not in ai, you, you're just, anxiety has really been the primary emotion associated with ai.
I think for most of
[00:07:23] Henrik Werdelin: us, for the whole year, I guess when A CEO says, Hey, we should do ai, it seems that a lot of people on teams hear you say, yeah, we should do ai 'cause they're not gonna fire a bunch of you. And obviously that could be an outcome, but it could also be an outcome that you can give people an Ironman suit and you can make their.
The boring kind of part of their job, less boring, and you can allow them to do more of the fun stuff. You know, Jeremy, I was talking about, like, you can see the efficiency that AI can give you as both helping you with the top line. If you give people the ability to make a better product or the bottom line.
Yeah, that's exactly the way
[00:07:57] Greg Shove: I think that's the right way to think about it. We think about it in, and one of three sort of modes or approaches, which is optimize, accelerate, and transform. And so when I started to play with it. And I did the, Hey, look at this at all hands meeting, or I was slacking people.
I check this out, or I was forwarding newsletters and I was cutting pasting links to, Hey, check this out. And people I'm sure were like setting up a little folder or whatever, a little, Hey, all this stuff from Greg about AI. And I'll look at it maybe on the weekend, but I probably won't. So that went on for two or three months.
And that, so then I realized I need to do something else. And so I need to make this kind of both real and, and strategic at the same time. These are smart people. The work at section in any of our organizations, right? They want to know like, why are we doing this and where is this taking us? So I thought about as exactly the same way you do.
How do we make ourselves more efficient internally? How do we optimize? Can we run the business better? Allowing us to do, you know, more of the good stuff and, and less of the drone work. And that does not mean laying off people, obviously, in most cases, there will be job, there will be job loss, significant job loss in some areas, right?
But you know, right now, and certainly not at section cause everybody's working too hard. But the thought we thought about was optimized. Then I thought about as well, how do I make the business go better? More revenue, expand margin, improve the product, right? In measurable ways. And that's the kind of second bucket.
And most of our attention went to those two buckets. Transform is okay. I'm at such existential risk. Or I see such incredible opportunity. I want to move to that kind of mode, right? I might take a chunk of money and a bunch of people and actually go try to do something that's more transformative. So I'd say I got people on his stand.
Listen, I'm not trying to lay anyone off. I'm trying to make us operate more efficiently and we're in the content business. Oh, hey, this is called generative AI, right? It is content. It generates stuff. Content, right? So we had to get, I had to get people there and it took me too long. I should have got people there faster.
It probably took me 90 days because I was doing that kind of CEO thing. Hey, read this, check this out. What about this? Why don't we try that? And I think it would have been more effective to do that for a month and then call time out. I just, it took me a while to really figure out this framework or figure out this approach and then get people in a room and say, Hey, let's start talking about it a little more intentionally versus cool demos.
[00:10:16] Henrik Werdelin: So was it like a, like a real, there's just old hands, like we're doing now. We've, we've heard other CEOs that kind of send out like a manifesto. What was the tactical kind of
[00:10:25] Greg Shove: approach? Yeah, no, no, no manifesto yet. We don't have AI, we don't have AI principles or policies yet, but we will soon. No, it was more really running a series of brainstorming sessions.
Using this idea of optimize, accelerate, and transform. And I, we took transform off the table. I'm not sure we should have, and we're bringing it back on the table now. And I'll talk about that in a moment. We basically use those two kind of operating modes, optimize and accelerate. Okay. Let's talk about AI, right?
So optimize is easy. They're both pretty easy to figure out. I think, workflows. Ask people to do an honest audit of their internal workflows. It's not that hard, right? Look at your calendar. Look at your Asana boards, whatever it might be and map out how you spend your day, how you spend your week. Right.
And look at these moments where you're doing tasks that we think AI could do at least as well, maybe even better. Right. So that was,
[00:11:15] Jeremy Utley: so with that caveat, how do you get people to honestly look at the workflows? Because I can imagine a scenario where Greg's saying, we want to see what AI can do. And I look at my calendar and I go, there's a lot of it.
Do I, how do you keep people from wanting to hide that stuff? Cause you can imagine a scenario where people go. I don't want Greg to know that AI can do a lot of my job. Like, how did you provide that assurance that optimize is not about getting rid of you. It's about supercharging you. Yeah. Listen,
[00:11:43] Greg Shove: that's all
[00:11:43] Jeremy Utley: about trust.
[00:11:45] Greg Shove: They may not have thought, they may not have thought I'd seen the future. Like I was that smart, but going through the last three years that we'd been through together as a team, they, they at least at some level, trust me, right. Meaning every time we did the layoff, we were transparent about when we were doing it, why we're doing it and who's going to be in pain.
You got to earn that, right? Just no other way. I think it's harder in bigger companies. And I think frankly, there is a lot of cynicism, a lot of mistrust that the, uh, the relationship in is so frayed in so many ways, I think between knowledge, kind of knowledge workers, right. And there are employers, right.
That's why people have two jobs at the same time, but yeah, listen, I, in that respect, we're fortunate or I I'm fortunate. I think there was enough trust to say, listen, let's look at this and see if we can get some gains out of it, but it's a great question. I think in large organizations, it's tougher.
You're going to have to, you're going to have to somehow. You're going to have to, you're going to have to diagnose where you're at in that trust scale or trust meter, because otherwise that, that will be the behavior you'll get. You'll get people, or we see it now in the other way, right? That Salesforce study that just came out from this week, I think it was 14, 000 employees, right?
That that's 64 percent were not, or passing off AI work as their own work and makes sense, right? In the, in this context of lack of trust, one of the things we did around the same time, and I think it. Helped, which was, we started acknowledging when we are using AI and we even did something as goofy as AI shout outs at all hands, when I started and people were like, what, you're going to do like an AI shout out and we do like human shout outs, right.
Every, every week. And, but it was just really an attempt to say to people, we're all going to be using AI, it's going to be okay. We're going to celebrate the wins. We're going to talk about the losses so we can learn from them. And yeah, we're going to move forward together. What's a few examples of something that fell
[00:13:32] Henrik Werdelin: into the optimized bucket?
[00:13:34] Greg Shove: Oh, easy stuff, right? Low hanging fruit would be trans transcriptions and translations of content. Obviously preparing scripts for video shoots. A lot of the marketing tasks that you I'm sure you know about email templates and building drafts of marketing email campaigns and cadences or sequences. Yeah.
Stuff like that, basically what I'd consider V1 work most of Gen AI today, I think is the way to think about it is get you off the blank page and get a good V1 right faster. And so I would
[00:14:05] Henrik Werdelin: even, I would imagine even that have already yielded like efficiency. I think that's one of the interesting thing with the tools that are available right now, you don't have to do a lot.
Before it becomes something that's really useful, you don't, it
[00:14:17] Greg Shove: doesn't cost a lot. People tend to think, Oh, this is going to be expensive, or it's going to be like the prototype and then apply it and all that stuff. And I got it. It's 20 bucks a month. It's 20 bucks to attend some training, right? You got to help people basically how to get better at prompting.
It's the gains are so obvious, right? Uh, at that, right. Your
[00:14:36] Henrik Werdelin: age question, or your age comment earlier, do you feel. That because prompting is as easy for everybody, like you don't have to understand Python. Do you think this is one of the things that could be easily adapted by everybody or is it, is this, is prompting AI also a young person's sport?
[00:14:55] Greg Shove: I don't think it's a young person sport, but I think it's not easy in terms of good prompting, right? So the complex, contextually relevant and directed prompts, people are now calling them structured prompts, right? They're, I don't think they're natural for us necessarily. The conversational approach is more natural, but the bottom line is I think prompting still is harder than it should be.
And we obviously need to move to some version of an agent or some, the GPTs, November 6th to me was a kind of watershed moment for AI, I think probably for the board of AI too, but I'm blown away by, I'm blown away by GPTs and really showing a path forward that can unhook AI from prompting. Basically and bring a real kind of value at a very kind of task or in a task level.
So at a very sort of micro level in terms of people in their daily workflow, but yeah, I don't, I think that I think prompting is just hard for all of us to really do it well. And so I'm looking forward to prompting less in 2024.
[00:15:53] Jeremy Utley: Yeah, you can imagine that being something that open AI, actually it's maybe the answer is for AI to understand what we're trying to say, right?
Where prompting just gets built in the chat, GPT gets GPT one thing. I want to go back to the
[00:16:07] Greg Shove: head. Oh, sorry. I want to go back to Henry's question that we did one thing early. But I think it was a light bulb moment for all of us. And I wouldn't, I think it's a good idea for others to try is we took something that was very high value and infrequent, but high value and applied AI to it to see what would happen.
And so let me give you the example. And it's, it's the AI as thought partner and AI as a board member. We don't record our board meetings, but we take good notes. So we had a board meeting in the summer where we, I asked the team to make faithful notes better than usual. Around all the input and ideas we got from the board.
And so we use that and then we use the board deck that we had sent the board as a pre read and then we basically ran the board deck through four models, right? Claude, GPT, three and a half, four, I guess, five part of being and compared the output from the AI after a bunch of prompts, not just one, but we started with the obvious prompt, right?
Pretend you're a board member. I'm the CEO. I sent you this pre read. And it was, it was mind blowing really on how good, particularly Claude was. In fact, GPT 4 performed poorly in that moment, I think primarily because of a, a crazy hallucination, but Claude nailed it. And we actually rated Claude as 91 percent overlap to the feedback, including quite nuanced feedback about the stage of our company, our cap table and preference.
The kind of growth we'd have to create or margins we'd have to create sort of growth versus profitability kind of discussion. So we were, and I, so I, I shared that with everybody. I shared it with the team internally. And they're like, what with that kind of simple prompt, right? And the conversation afterwards with one pre read AI could do that.
I shared it with the board, say, Hey guys, it's time for you to bring your a game because you're about to get replaced. I mean, you know, you're sitting at setting up a board meeting takes two hours, at least a scheduling effort. And then the thing's 90 minutes and then it's 30 minutes afterwards. And then there's some email follow up.
Claude got 91 percent of what you said. And I got a great board. I got, I got the former CEO of Time Warner. I got board members who are on the board of Moderna and Akamai. Like I've got a great board. Right. And so guys. Were they, are they concerned at all
[00:18:15] Jeremy Utley: about AI taking their jobs? Is that? Yeah.
[00:18:17] Greg Shove: That was one of the, one of the responses was, Hey, we loved AI until you showed us this because now it's like, Oh, it's coming for us.
Like it's coming for all of them.
[00:18:25] Jeremy Utley: What I love about that example, Greg, is that. If you bring that back to your team, you're showing the team, this is how it's relevant for me. Right. It's, and it's not, I think sometimes you use that word V1 work. I think what that can, the way that can be interpreted is it's about low level tasks.
It's about the junior employees and what you do with that example, as you say, the board deck, you, it just in the org structure, you can see that it is the highest level task and you say. Even there, I'm using it, it helps me a lot, I haven't been fired and nor has the board, but it actually, it's just this amazingly elegant example to show people, it's not about you not having a job, it's about you doing a better job.
[00:19:08] Greg Shove: Yep, I think that's right, and I think, and it's, it is providing that context as well, listen, why am I doing this? I'm doing this because. And by the way, I'm doing it, meaning I'm now giving my board decks to Claude and GPT 4 prior to my board meetings so I can raise my game. And what I'm trying to get people to understand is that meeting will now be more productive, right?
If everybody has not just read the pre read, but now used AI. With the pre read, right, they're going to be able to come in and hopefully move the conversation forward faster and hopefully obviously bring the benefit of human experience and the years on the planet that we all have to these conversations, right?
And so that's, I think people at that moment, okay, I get it. We're not trying to, we're not trying to do away with me or the meeting. We're trying to make the meeting better, right? Trying to get better answers, better decisions, things like that. So that's why I like thinking about these high value. Moments or meetings or discussions or decisions or conversations that we have and bringing AI into them as a test case or use case as by the way, sometimes it doesn't work and that's part of, obviously part of the conversation.
And I think that also helps people to, uh, the anxiety can, it will drop a little bit, right? Hey, it's not a AGI and they're all, but don't worry about all that. These are like, they're kind of dumb. They're getting smarter. And they often don't work. So, you know, we're not going to use it for that. And you're going to have to go back to the old way.
And so should have really highlighting where AI has failed internally, where we've stopped using it for tasks has been, I think, really good as well. What's an example of a test that you stopped using? Well, you know, I used to do one that's relevant to me. We used to do scripting, video scripting. We don't think AI is, is the speed doesn't, doesn't make up for the lack of quality.
So we're still, we're now back to writing scripts. Fully manually, if you will, human, that's one example that's out of the education team for me, I used to use AI over the summer and into just a couple months ago, I was using either to write my monthly email to the board because I, we do a great weekly email summary of the business.
We call it three Ps or progress, priorities and problems. So Ps from my direct reports, feeding it into cloud and saying, write me the first draft of my monthly board update. And it seemed to work well enough, or maybe I was just looking confirmation bias. I was just thinking it was doing that well enough, right?
Cause I was trying to show examples of how AI can help. But the reality is by September, October, Haley, my assistant was like, this is just not worth it. It's, we're not getting back a good enough V1. Let's just go back to the old way of cut and paste and edit. So now that's back on my to do list as an hour to do, you know, once a month, versus I thought I could get it down to 15 minutes.
And AI do the rest and it's just not working right now for whatever reason and we'll try again in Q1 and see if we can see if we can get it to work. Maybe we build a GPT for it. That's one of the reasons I'm so excited about GPTs, right? Because with GPTs you can give really specific instructions. You can constrain the training data is a way to think about GPTs, right?
And make it very task oriented. So that'd be a great test to build and see if I can then get back that hour of time, which is, I think how we should be thinking about it, right? If I can get back these hours of time over the course of a week, they'll add up to be meaningful.
[00:22:21] Henrik Werdelin: I was curious on a super nerdy question.
I've also experienced that for some things I just go straight to Claude for some things I go to. TBT and for just normal chatting, I would use PI or whatever, like you kind of increasingly kind of like a little bit like on your team have the go to LLM. It sounds like you have the same. Could you explain that and maybe try to help create some vocabulary on how should you think about how to use what service for what?
[00:22:50] Greg Shove: Yeah. Yeah. I think, um, well, let's start with the, well, here's what I think about framework wise is daily, weekly, occasional. And then in testing mode so i've got this portfolio right and so daily for me and for us mostly at section it is gpt for the most muscular model right with the most range if you will.
And then and clod and for some reason and i don't know why clod seems to be better at thought partner work. It seems to be better at business. It just seems to have more, more, yeah, business oriented thoughtfulness. I don't know, I just, we think Claude's a better thought partner for people, for executives, for people who work in business.
I don't know why. And now Perplexity, I'd say, has been added to that list in the last couple months. Really, our go to for more research oriented, clearly when we want to see the sources. Now GPT 4 is revealing the sources as well, but I think Perplexity really, I think, owns that at this moment in time. And then, of course, Fathom for note taking, I use Fathom.
That's probably the go to daily and then weekly for me, I never got my head around mid journey and I'm not a creative and so Dolly for me, it's just so much easier and good enough, right? Although Jeremy's wagging,
[00:23:57] Jeremy Utley: sorry, sorry, I can't let that comment stand. That's my other life, Greg. I can't abide because people know me.
And even though this podcast isn't about creativity, I can't let the comment. I'm not a creative go just like my dad's a lawyer and you have to mark a, an objection. I'm just marking an objection. We can keep going, but I just want to make sure I could reflect. I objected to your comment that you're not a creative, but please continue.
[00:24:21] Greg Shove: Okay. Well, but can you tell me why you're objecting or was it just like,
[00:24:27] Jeremy Utley: I fundamentally disagree with you. You're not at all. You're all
[00:24:30] Greg Shove: creative. We're all great.
[00:24:31] Jeremy Utley: A hundred percent. A hundred and ten percent. And by the way, if you, if, if we share this conversation with a hundred people and ask a simple question, is Greg a creative person?
One a hundred people will say, absolutely. He's doing stuff I never imagined. So not, I'm mostly just teasing. I get it. I'm making it up. Maybe to refund
[00:24:52] Henrik Werdelin: that, I think one of the cool things for that AI is allowing people to do is to reduce the, the space between people with an insight or an understanding of a customer and the ability to produce an output.
And I think historically the reason why people would define themselves as not creative was because they were not able to produce the final output that was seen as being something that was a visual or music or whatever it was. And obviously now where somebody like you Greg can take all the wisdom and insight you have.
And package it in and you can get mid journey or Dahlia or whatever to render that graph or image or whatever it is. I think that actually changed quite a bit. Yeah, no, I agree. I think
[00:25:37] Greg Shove: about that. That's one angle to think about. The other is someone who's. Got the, has done the mental math or the napkin math, but can't get it into that sort of CFO ready presentation.
And they're not viewed as that person that builds robust business cases, but now they can, right? Or they're going to get much closer now, right? With AI. So that's obviously the, to me, the magic of gen of AI or these models really is that they, they just move across domains. They remove, they move across industries.
They move across functions. They move across skills. With such which is such ease and we don't as humans and so we're in our silos both skill based and industry based and AI doesn't live in a silo so it's just so powerful in that respect other so that's how I think about it so my daily tools or weekly, um, less frequent something like synthesia we're playing with synthetic video and voice.
A little bit, we'll see, uh, where we go with that. And then testing for me, what I'm testing right now is Lex just started with Lex dot AI to see if I can find a good writing partner or again, get off the blank page. And then of course, beginning to play with the AI features that are appearing in the tools we use every day, like Notion or superhuman.
[00:26:51] Jeremy Utley: One, um, one, one thing that I just want to contribute to the. Comment about Claude being a better business kind of thought partner. I have, I agree, but the challenge is for me, there's so little time where I'm sitting at my desk. And GPT by, with Whisper and Voice to me is my go to thought partner. Not necessarily because it's better, the best thought partner is the one who's always available.
And I kid you not, like practical use case. I had a sales call last week with a client and I know I've got 40 minutes to do a workout. And it's, and if I don't leave now, I know that email is going to suck up my life for the next 40 minutes. So I get up and I go and, but I know I've got to send a recap.
The fact that I can open up chat GPT. All via voice while I'm stretching. Mm-hmm . Hey, I just talked to Dan and so we talked about this and this, and I wanna send him a follow up. Would you mind to take a first pass at a memo that I could send him, letting him know that I'm excited that I heard these three things and that duh.
Right. Oh yeah. And don't forget this. Now I'm done stretching. And the one thing that I probably would've forgotten to do I did with the thought partner, who may not be the best mm-hmm . But is the one who's available for that moment.
[00:27:58] Greg Shove: Ab, absolutely. Yeah. Listen, I think the, my takeaway from that is. You got to give OpenAI a lot of credit, a lot of props the last 12 months, the rate, the pace of their product, product advancements or releases just been incredible.
As we all know, Google's slipped Gemini to Q1, and I'm sure at Google, they're sitting around thinking, shit, we get to Q1 and we're going to be behind again, because OpenAI will have pushed, uh, further ahead now that they decided who the CEO should be again. But yeah, really impressive, right? What they're doing and hard for others to, to catch up.
So yeah, I absolutely, we need a mobile app from Anthropic soon. No,
[00:28:34] Jeremy Utley: I can't believe it isn't there yet. So folks, Anthropic, if you're listening to this, please want to shift gears, just last topic that I've got on my mind, Hendrick may have others, but I'd love to hear about success stories and I'd love for you to brag on yourself and get practical.
What's, what would you say? What is the success in applying? Generative AI to, to the business section that you feel like, wow, this is a great example of the kind of impact you can have. And then also I know because of the course, there's loads of examples. You want, if you want to refer to anything outside of section as well, we'd love to hear that too.
But for folks who are going, what kind of really, what kind of impact can this have on our operations? Are there one or two? Key studies that you could share to just highlight the practical, real economic value of integrating generative AI.
[00:29:26] Greg Shove: Yeah, I don't, I want to come at the answer a little differently. I think success at this moment, talking about this moment, right?
Cause we're talking about 20 bucks a month. Let's be clear, right? So we're not talking about building. We're not talking in this conversation about spending a million dollars or more, millions of dollars to build a, uh, an AI app or AI product. We're not talking about that at this moment. We're talking about knowledge workers.
Every day using AI and it's, it costs 20 bucks a month. So pay for it yourself or get your employer to pay for it. And if your employer is clueless and won't pay for it, then pay for it for yourself. And so I think the success metric is different. It's about how, what percentage of your team is AI ready or AI comfortable, AI competent, I call it the AI class.
I think the workforce is splitting and into two, right at the AI class and everybody else, the knowledge workforce is about to split and we need. Ourselves to be in the AI class, and the more of us inside of an organization that are in the AI class, that means the organization will be in the AI class, right?
That's clearly to me the challenge of the next 12, 12, 24 months. And in that, if we make that happen, we'll get the successes and we'll get the business cases and we'll get the ROIs. But we're not looking for a lot of ROI because we're not, it's only costing us 20 bucks a month. I think that's one part of the answer.
Second part of the answer is that there are hundreds of use cases and they are specific, meaning the application of that use case to your workflow, right? Or your company's kind of workflows are so specific that my examples probably don't matter. And by the way, what I'm looking for, I'm looking for one use case that saves half an hour.
Less, right? If you can't come up with one use case. It's going to give you back half an hour in a week or an hour in a week. Here's how I think about it, a hundred bucks an hour for a knowledge worker, and that's probably at the low end, at least in Silicon Valley, but use that number as just, it's a nice round number for what we pay a knowledge worker.
Our token costs this week for GPT 4 are around 2 cents, 500 words, right? Do the math. That's a lot of queries to the AI,
which means to me, it's several things. My employees should be able to get enough value for 20 bucks a month. That's number one. Number two, I'll add a lot of value to someone who I'm paying a hundred bucks an hour or two or more, right? Cause they're going to be able to do a lot of queries and get some value from the AI.
Just it.
[00:32:01] Henrik Werdelin: The math works, you clearly been down, you clear, like, I think for many organizations, like on the advanced side, a lot of some pitfalls to avoid. Have you had anything where you were like, if I could give myself the advice not to chase that rabbit, I would. I think
[00:32:18] Greg Shove: the pitfalls are the ones that people talk about it.
I think the biggest pitfall is misinformation and unrealistic expectations. The misinformation is coming from media. It's stealing our data. It's going to take our jobs. We can't trust big tech. That might be true. I'm not naive. Listen, big tech's not trying to save the world. Big tech's not really trying to make educational health care more accessible.
They just want to make more money. They want us addicted to AI because they want to charge us 20 bucks a month for it. That's the reality of the situation. It's our job to find the use cases and frankly avoid some of these pitfalls. But some of this is misinformation. Some of this is just the missed expectations, right?
We it's being oversold to us. And so I think the first thing I'd say to any leader is don't oversell it. Be optimistic, but pragmatic. Acknowledge that it's not for the, it's not for the anxious. If you have an, if you're culturally anxious, if your team or you as a leader are anxious. A. I. is not going to help, right?
It's going to hurt. It is in this moment. You, and so that means you might want to wait. So my advice to some is wait. If you're anxious If everything has to pencil out, if everything has to work, if you're a no mistake culture, if you've got, if this is not going to land well, then don't do it. You can sit, uh, on the sidelines at least for a while, depending on where you are in the crosshairs of AI.
So if that's the first thing every leader should do, every leader should have an honest conversation with themselves or someone that they, a thought partner that they, they trust or more than one to really assess how soon do I think I end up in the crosshairs. And I think on that thing,
[00:33:51] Henrik Werdelin: and I'll say this as a statement, but I ask the question to your point about the future and using AI to make big transformative changes in your organization, it does also seem that things are moving so fast right now that if you were to like even try to spec what is like the future that I can build with AI and I start the billion dollar project tomorrow, You're very likely to build something that's going to be wrong.
Is that a fair statement?
[00:34:18] Greg Shove: I think that's a fair statement. I wouldn't do that. I would have obviously a product vision or a product strategy or some idea of what I think I want or where I think I might be going with this, but we have to think about this as a thousand experiments. Inside of a single roadmap, because otherwise I think the risks are too great, particularly if you're an incumbent, right?
And even for startups, and we're seeing that every week now in Silicon Valley in terms of AI startups, right? Talk about pivots, they're having to pivot every week based on what OpenAI is doing in terms of changing the model, changing the capabilities, changing the economics of the model, and so on. But back to your pitfall question.
It's all about leadership at this moment. Then it just having realistic conversations with people around. This is what I think is possibly here and what these tools can do. And here are the first three or five or 10 steps we're going to take. And we're just going to experiment, experiment our way into this, both in terms of spend.
Uh, capital and time, and I get it. If you're the CEO of a 20, 000 person organization, 20 bucks a month adds up. It's going to be four, 4 million, right? Of incremental tech spend. It's not in the budget currently. And so your CIO is saying, oh, okay, I got to pay that. I got to pay that for everybody. What do you want to take out of the roadmap?
Cause it's 4 million bucks. Or you got to grab that money from some other, obviously some other source. So it's real money when you scale that up, I get that. Even if you do the discounts and stuff like that, start in a meaningful, but small way is my opinion and grow into it or experiment into it, but be very, to your point, it's changing so fast.
You could end up in the crosshairs quickly.
[00:35:43] Jeremy Utley: Yeah, that's right. One thing I really liked Greg about your, uh, your class is you encourage students to reevaluate every three months. I think that's great. It's not just that you run a framework one time and then you take your marching orders. It's every three, this now needs to be a part of your regular rhythm of review is where are we on in the crosshairs?
Where are we in our organizational development? Where are we with the latest advances that have occurred? How do they affect our business model? And if you're not regularly reviewing, you're going to be operating off of an outdated model very quickly. Absolutely.
[00:36:20] Greg Shove: Yeah. And I think that's right in terms of.
It's limitations, so it's capabilities and limitations. Oh, it's too biased. It's less biased now, and it's getting less biased, right? It hallucinates. It hallucinates less now, right? And it's going to hallucinate less in Q1. So you check back in to capabilities, limitations, business model costs, the costs of queries, for example, or API costs coming down dramatically on November 6th, right?
So, yeah, I think that's right. I think this idea of a one year AI strategy, it makes no sense. I think you should have a head of AI, by the way. I think it should be a business person, not a tech person. And that's the person responsible for doing this every three months.
[00:36:53] Henrik Werdelin: It can't, you know, it, it is seemed to be a golden opportunity for a lot of IT team to suddenly get back into glory days.
It'll be interesting to see how many of those IT teams actually going to grab that one and saying, instead of seeing as this necessary evil comparable to let's not give everybody in the office internet, as some of us might remember in the nineties. Or banning Facebook, remember banning
[00:37:14] Greg Shove: Facebook?
Remember that, right? Like, yeah, listen, this is, this will, but it'll happen faster. This reminds me of what, how IT reacted to SaaS, right? Which is. You know, wait a minute, not invented here. I didn't choose that kind of thing. Right. And then eventually they lost that battle, so to speak. Right. And, but it took it probably a decade really.
Right. I think similar, right? The route is, this is going to shadow AI. It's already everywhere. Just like shadow IT, SAS generated shadow IT, shadow AI is everywhere already. And it's the high school kids first, and then the college kids, and now it's the younger employees. And they're like, and they know that their work is mind numbingly repetitive.
[00:37:56] Jeremy Utley: You know, it is by the way. So, sorry, this is actually non trivial Henrik and I have mutual friend Bracken Darrell, who I understand made major inroads when he was at Logitech because in part, because of his kids gaming habits informed some of his big strategy, Greg, you have. Sons, or you have kids, I think, how have you got three kids?
[00:38:15] Greg Shove: Yeah.
[00:38:16] Jeremy Utley: Yeah. How have your kids affected your understanding of this and your mindset towards it?
[00:38:24] Greg Shove: They haven't helped to be honest. And I think they started to ignore my texts by June or July because the two of them are working. Two older kids working in tech and one younger just graduated from college and now working actually in sales in New York and he and I are now have a more active dialogue as he's using AI more in his day to day flows as he should.
But for my other two, I think just got sick of me, but
[00:38:51] Jeremy Utley: they unsubscribed from the family to
[00:38:53] Greg Shove: grab from the family text because it was dad, like posting and they just seriously, dad, stop talking about Sam Altman and they just started shit posting back about AI. I
[00:39:01] Henrik Werdelin: have one question that I'm curious about because obviously you're such an expert in education.
It does seem very obvious that both like the texting format, like the going back and forth, but also being able to completely personalize the education for that specific individuals, it has the potential to change education quite a bit, maybe as we're like finishing up and you're looking into the future, could you give us a tooth, a few cents on what's your thought on what this will mean for education?
[00:39:31] Greg Shove: Yeah, for sure. First of all, having been someone who's tried to disrupt business schools. It's, it's harder than it looks, right? We, and I always reminded of the conversation I had with an associate dean at a top, uh, 10 us business school who said, Greg, I, your product's great because we've had people on my team take your courses and your price is too cheap, so I hope you go out of business or run out of capital.
These guys have strong brands. And it just culturally, and we instill so much value in that brand, right? Whether it be undergrad or business school. So it's harder to disrupt education than you realize, I think. And most ed tech entrepreneurs, I think would agree that it's a tougher sell or it can be, I would say, and back to how we talked about what section doing with AI, we're moving faster now than November 6 dev day at open AI for me and the lowering of the token costs, the release of the GPTs.
And the kind of the robustness of the model, the improvements, the model to me really were a signal that we need to accelerate, meaning I do think that particularly if you're sitting on what are what I call dumb video libraries of training and we're not that because we're a live learning platform, but we're not, we're next, right?
Meaning, but if you're certainly an asynchronous learning platform today, I just, I have to believe. That someone's going to create a much better experience, right? That is it because it's personalized and relevant, because it's the number one question we get from our students, which is what about my industry?
What about my country? What about my job in terms of I'm learning this, but how do you make it contextually relevant? And clearly AI can do that. So I'm optimistic in that respect, and we're going to have to move quickly. I think we will do to build it. I'm also thinking about a little bit differently, which is a lot of people don't want to learn.
Let's be honest. We burn people out on education by, I think, probably set by selling them with 40, 000 a debt, at least in the U. S. And, you know, most of us are not lifelong learners. If you do any kind of segmentation analysis of U. S. customers, U. S. consumers, rather, you'll get a like a 5 to 10%. Oh, they're the lifelong learning.
Segment of the market, everybody else has day jobs and then they want to go home and watch Netflix and look after the kids. And so I'm thinking about this more as can I reinvent what we are, uh, uh, building basically, not as a course, but as a co pilot essentially.
[00:41:52] Jeremy Utley: Right. So as an example, I think I heard you say this the other day, Greg, just for listeners to make it very pragmatic.
Some people want to learn how to make a product strategy. Most people just want a product strategy, and you can run a course to teach the people. But as you said, maybe 10 to 15 percent who actually want to learn how to create a product strategy for the other 85 percent who just want a product strategy.
That's a fascinating to me evolution of the brand and evolution of the business to say, why don't we just deliver a better product strategy for them?
[00:42:23] Greg Shove: Yeah, that's right. I think that's how I'm starting to think about it. And there's hundreds of tasks like that. Some as small as how do I do a good one on one or how do I do a performance review and some as infrequent, but more strategic, like how do I build a product roadmap or product strategy?
How do I do business strategy? How do I do, how do I do competitive analysis? And I think that we can teach people or we can actually sit alongside them. And, and get the output. Now, the question will still be then if ever, if all of us are getting good V1s out of AI, then what? So that's the question we're going to have to answer next.
[00:42:55] Henrik Werdelin: It definitely seemed very interesting when you look at like the graph of like where AI can take you, there's going to be people that's going to be under that either can be redundant or can be lifted. Yeah. And there's people gonna be above, but like one point, the graph is gonna change quite a bit. Yeah, absolutely.
Absolutely.
[00:43:10] Greg Shove: Yeah. And so, you know, we, we, we, we, we might all be looking at okay v ones of product strategies in a couple years where no one's really we, we need to, we need some of those to be V two to be better and differentiated to actually invest in them.
[00:43:24] Henrik Werdelin: This has been so inspiring, not only because you're inspiring, but like what you guys have done already, I'm sure a lot of people are listening to going to be able to take a lot from very much appreciated you taking the time to talk to us today.
[00:43:36] Greg Shove: Likewise. Thank you for inviting me. I've enjoyed it. It's a great conversation.
[00:43:39] Jeremy Utley: Tell folks how they can find you, follow you, engage with you.
[00:43:43] Greg Shove: Yeah, sure. So, uh, follow me on LinkedIn and I'm starting to post more frequently. I've been unimpressed with the growth in my followers, but impressed with the engagement.
That I'm getting on LinkedIn. So I'm enjoying it. Uh, you can find section at section school. com, but yeah, find us on section school. com and we'll make it easy to check us out and experience a live learning course. It's nothing like LinkedIn learning. It's nothing like LinkedIn
[00:44:06] Jeremy Utley: learning, Greg. Thank you. As always.
I look forward to continuing the conversation. I appreciate it. Thank you. Best of luck
[00:44:13] Henrik Werdelin: with everything.
[00:44:13] Jeremy Utley: Thanks guys. Yep. Take care.
[00:44:15] Henrik Werdelin: Okay. Jeremy, give me your first like impression after we had this conversation. What was the thing that you remember?
[00:44:22] Jeremy Utley: First thing that comes to my mind when I reflect on Greg conversation is the rhythm of acknowledging explicitly with the team when they used AI, I thought that's great.
Doing AI shout outs, just like you'd shout out a human being shout out when someone uses AI, I think it's a great kind of mechanism to normalize. And then the other, he described it as an early light bulb moment, finding an infrequent, but high value use of AI, like reviewing the board deck, I think is a magical way, not only of demonstrating value high up the food chain, but also for the CEO to be open about the way that AI can affect anybody's job and the way it can amplify anybody's job.
A couple of things. What about you, Henrik? What'd you take away?
[00:45:06] Henrik Werdelin: Two things. Obviously. Had not to fall in love with, can be testosterone for your brain, which is like just a funny thing for the middle aged man, but, but I do think that this idea of seeing it as not something that's replacing you or something that you are necessarily tasking, but something that is becoming an iron man suit or becoming something that you can use to make yourself better, I thought was interesting.
The second thing, which I think we've heard before, but it's just. I think important is that most of the people that seem to be knowing how to use this and are using it a lot, they keep talking about it as a thought partner, not necessarily as like a somebody you send tasks to. And so. I remember you said the other day, like when you come out for a meeting, you have a great idea, you basically ramble into the chat to BT app, and then it basically structured the thinking back to you.
I have exactly the same thing. I like to use a lot of words. So I tend to be a little bit of philosophical in the way that I compute and say things. And so being able to just get the bullet points back from something that you just vomit vomited into your phone has been very useful. And I think he seemed very much to be of that kind of.
A school of thought also see that something that you're having a conversation with when the paper is empty.
[00:46:20] Jeremy Utley: Yeah. Yeah. And then the last thing probably is the regularity of review. Don't assume that an AI strategy is set for long, but actually have. One of the things that I've done because of Greg's influence is I've put calendar alerts on my calendar, three months out, six months out, nine months out to revisit my own AI strategy.
And I think it's a really good practical thing is recognize the world is changing so fast. What you think about it should probably be regularly updated deliberately. That's all for this episode of Beyond the Prompt, but hey, before you go, would you do us a quick favor? Would you hit subscribe? We've got a bunch of amazing advice coming your way and we don't want you to miss any of it.
We'd be grateful if you'd like and share this episode with someone you know who's also curious about how to add AI to their life and their organization. Until next time, take care.