Episode 078
The Future of AI: Simplifying Complexities with Conor Grennan
In this engaging episode of the Karma School of Business, host Sean Mooney welcomes Conor Grennan, a New York Times bestselling author, Chief AI Architect at NYU Stern School of Business, and CEO and Founder of AI Mindset. Conor shares his journey into the realm of AI, offering insights that make the subject approachable and relatable to everyone. From his initial exploration sparked by ChatGPT to developing an educational framework for MBA students at NYU, Conor's approach to AI emphasizes the human aspect and practical understanding. This conversation is essential for anyone looking to grasp the current influence and future potential of AI in business and everyday life.
Episode Highlights:
00:00 - Introduction to Conor Grennan and the transformative impact of AI.
02:30 - Conor's unique path to becoming an AI influencer.
09:43 - Effective strategies for utilizing AI in business and personal development.
12:44 - The significance of shifting our mindset to unlock AI's capabilities.
21:59 - Strategies for adapting careers in the fast-evolving AI landscape.
34:09 - Insights into the next five years of AI and its business implications.
41:17 - Accessing Conor's AI training materials and newsletter.
For more insights from Conor Grennan and to explore his AI training materials, visit ConorGrennan.com.
Conor is also active on LinkedIn, where he shares regular updates and thought leadership in AI. Follow him here: https://www.linkedin.com/in/conorgrennan.
Episode Highlights:
00:00 - Introduction to Conor Grennan and the transformative impact of AI.
02:30 - Conor's unique path to becoming an AI influencer.
09:43 - Effective strategies for utilizing AI in business and personal development.
12:44 - The significance of shifting our mindset to unlock AI's capabilities.
21:59 - Strategies for adapting careers in the fast-evolving AI landscape.
34:09 - Insights into the next five years of AI and its business implications.
41:17 - Accessing Conor's AI training materials and newsletter.
For more insights from Conor Grennan and to explore his AI training materials, visit ConorGrennan.com.
Conor is also active on LinkedIn, where he shares regular updates and thought leadership in AI. Follow him here: https://www.linkedin.com/in/conorgrennan.
EPISODE TRANSCRIPT
00:00:00] Sean Mooney: Welcome to the Karma School of Business, a podcast about the private equity industry, business best practices, and real time trends. I'm Sean Mooney, BluWave's founder and CEO. In this episode, we have a fantastic conversation on the current and future of AI with industry thought leader, Conor Grennan.
Conor is also a New York times bestselling author. He's the chief AI architect at the NYU Stern school of business, and it's the CEO and founder of AI mindset. Enjoy.
So I am very excited to be here today with Conor Grennan. Conor, thanks for joining.
[00:00:48] Conor Grennan: Thank you. Yeah, it's great to be here.
[00:00:50] Sean Mooney: I've been looking for this a long time and maybe as a little bit more. Backstory here. I came to really know of Conor when I was. attending a CEO conference that was in Nashville.
Usually a lot of those things, there's a lot of people on their emails. There's a lot of like content is thrown at you. And then they brought in Conor as a keynote and talking about AI. And this was really last year at the height of buzzword AI and the beginning of AI, maybe fatigue because people didn't really understand it.
And Conor comes out and he has this very unique approach. For those who've seen him, you'll know, and those who haven't. You gotta look him up on LinkedIn and his other areas that we'll get into. He made it so tangible, so understandable for mere mortals. Most of the audience were people kind of with the pigmentation of my hair, which is decidedly gray.
But what was really unique in his content was, as soon as he started getting into it, you saw all these kind of overwhelmed, over sensory, jaded, sometimes CEOs, all start pausing and leaning in and taking notes. I looked around, I was like, what is going on here? Because it was so good and natural. And so now with kind of like the flattery, overwhelmingly aside for Conor, you know, after that, I reached out to him, got in touch.
I read his AI mindset newsletter. He's got great content on LinkedIn. And so we've kept in touch and I asked Conor to be so nice to come and share a perspective into something that I think is going to be one of the biggest trends, certainly of the modern. eras of commercial history here. So Conor, thank you so much for joining.
[00:02:30] Conor Grennan: Yeah, no, this is gonna be cool. Thank you for that very warm and overly kind introduction. I always see people on email. I don't mind, but thank you for saying that. No, absolutely.
[00:02:41] Sean Mooney: Before we jump in too much, Conor, I shared a little bit of the preamble on how we came to know each other. I think it'd be really helpful if you could share kind of the quick story of you and how you kind of got into being really someone who's adding a lot of value in the topic of AI.
[00:02:56] Conor Grennan: Yeah, it's sort of a strange story, right? I don't have a background in AI or machine learning or even tech. Interestingly enough, I'm at NYU Stern School of Business. I'm chief AI architect there. And the way I sort of started was very strange, right? I got my MBA from Stern and then came back a few years later and I became dean of students For the MBA program for the next decade or so.
But when Chachabity came out, I like everybody else was like, Oh, what's this thing? And I tried it out and I tend to just be somebody who just loves to dig and dig and dig. And so I sat down at first, I didn't even know what this thing was. And I was like, well, how do you even interact with it? And my wife, who is more savvy than me, she was like, you know, just ask it stuff, you know?
So I was like, I don't know how that works. So it took me a while to even figure out like what to ask it. But once I did, I went down this crazy rabbit hole for the next two or three or four hours. And I realized right away, like, holy cow, this is going to change everything. And the funny thing is that my first thought was, okay, we have to build some kind of framework to teach our MBA students at NYU.
But the second thing was, well, I better start taking some like machine learning classes and things like that to understand it better. But the funny thing about that was that all those online classes I was taking or NYU classes I was taking. None of it was helping me use generative AI. It's not that it wasn't interesting.
It just, that it didn't have anything to do with it any more than you need to learn about coding to use your iPhone. It was just a very, very different experience. And so that was surprising to me. And it took me down another rabbit hole of, well, let's see how far I can push this and how do we teach this and all that kind of stuff, and it kind of just took off from there.
And I think it's actually helpful that I don't have a tech background because I'm coming at it from everybody who doesn't have a tech background. Not trying to explain what it is, just sort of saying, Hey, this is what this is. It's really unusual. It's really unique. It's all about how we think and everything like that.
The thing that I discovered and kind of stumbled onto was around the fact that this is really about us and our brains. It can do almost anything. But it's not like learning in the past. It's not like there's a learning curve. You have to learn a lot. You just have to know that it's there and available and be able to talk to it like a human, which sort of like weight loss is very simple in concept, but sort of hard in theory.
So I've spent the last 18 months researching that and going out and training companies on that.
[00:05:21] Sean Mooney: I think that's been one of your superpowers because you don't come from the tech side. Before getting BluWave going, I was in private equity for, Nearly 20 years, and the most dreaded conversation I would always have was the CTO conversation, where you go in and they say, well, I don't like dot net, so we got to put it in something else totally.
And then acronyms would start flying at me, and dollars. You would have like heart palpitations, because you're like, I don't know what that means, and you're purposely kind of obfuscating, obscuring it. Whereas when I heard you speak, it was just so. human. It was so conversational. And that's where I think you kind of captured everyone.
And that's why I enjoy reading your newsletter and your content so much. You come from an educator background. You're stern. A lot of your alum are clients of ours. And so I think all of that made it really, really helpful and tangible, particularly someone like myself, who's not a technology person. And so maybe before we go into kind of some of the nuts and bolts about how you make this a more powerful part of your lives and your business world, one of the things I'd love to ask just before you jump into this is.
What are some of the things we'd know you better if we knew this about you? So if there's one thing that you'd share that's maybe not on your LinkedIn profile or otherwise What's something that we know you better if we knew?
[00:06:41] Conor Grennan: I mean, I would probably say just that I lived abroad most of my life after college I graduated from the University of Virginia When I was 21 and I just moved abroad just for the heck of it and I end up working in public policy and Conflict resolution all that kind of stuff peace and reconciliation And the Balkan country.
So I lived in Prague for the next seven years. And I lived in Brussels for another couple of years after that. And then I traveled around the world for a year and then I moved to Nepal. I lived in Nepal for a couple of years and started a nonprofit out there and rescuing traffic kids and things like that.
My entire 20s was spent abroad until I was in my early 30s, I guess. And then I met my wife out in Nepal, who was American, fell in love with her. And that's why I moved back. But yeah, most of my sort of formative years were spent just living and working abroad.
[00:07:28] Sean Mooney: What an amazing adventure. I was one of those kids where I didn't do any of the gap year.
I didn't do any of the adventure. I jumped right in. Other than I made one smart choice. When I was doing the study abroad period, I had the choice of going to London School of Economics or the University of New South Wales and living on a beach. And I think that point in time, I've made the right decision to live on a beach.
And so not nearly as, uh, is kind of amazing and kind of do sack Eastman ish that you've done in terms of adventuring the world, but I'm certainly jealous of that experience. What would be one of the countries, if you could say, all right, you're going to go on one trip this year and you can get there. The whole family and do it tomorrow.
It's all paid, no kind of restrictions. Where would that be?
[00:08:14] Conor Grennan: Man, well, we're going to Thailand kind of at the end of the year. And that's something I'd wanted to do for a long time. I spent a bunch of time in Thailand and just loved it. It's just spectacular and exotic and so far away from my normal life that I can't wait for the family to see that.
[00:08:30] Sean Mooney: What is it about Thailand that kind of jumps off the map?
[00:08:33] Conor Grennan: It's so insanely beautiful and there's so much to see there. I did a lot of rock climbing down to the beaches there and there's just these cliffs overhanging the ocean. So I ended up spending, I don't know, five or six weeks when I was 29 or something like that, just down there, just rock climbing and writing every day because I'm a writer as well.
And I just want them to sort of see and experience what that side of the world looks like.
[00:08:57] Sean Mooney: That'll be amazing. And you get to bring the whole crew and great food, amazing beaches, wonderful people. We'll have to get that on our list with our kids. And so, Conor, maybe if we jump into some of the meat of the conversation here, one of the things that I really appreciated when I saw you speak at the conference was, This practical approach to using some of these technologies are out, particularly large language models, generative A.
I. And so if you were to kind of say here, three of the top approaches that everyone can and should start doing to get more out of these models to get more of the full potential and the additive utility and kind of productivity that comes with them. What would be some of the things you'd recommend?
[00:09:43] Conor Grennan: It's a really good question. Cause it kind of goes to the heart of what these things are and how we interact with them. And I think that maybe just by example, I work a lot with private equity. I work a lot of healthcare kind of across organizations and industries. And the question is always around, well, what tools are the best or what prompts should we use or what are the use cases?
And I used to do that more. I used to kind of give them that, but then I started to realize that And that's because their brain was craving, how do I use this empty box that says, ask anything because the brain doesn't like that, right? The brain likes templates. If you can kind of imagine two ninth grade classes and one teacher says, write a one page paper on anything.
And the other one says, write a one page paper on the last weekend and three people you talked to. The second one is actually easier than the first one, right? Which it shouldn't be. The first one should be easier. It should be easier to write about anything you want, but the brain really likes templates.
And this doesn't give you templates. And so I would say that the first thing that people need to understand is that it's deceptively complicated. Again, in the same way that weight loss is deceptively complicated. There's nothing to learn with something like getting on a treadmill. There's nothing to learn.
But our brain forces us off the treadmill because our brain prioritizes different things. Our brain prioritizes conserving energy and our brain prioritizes quick rewards and things like that. It's a little bit the same with chat GPT. Your brain is not sure what to do with it. There's no template there.
So it's kind of lost in the wilderness a little bit. And I think people are often looking for what's the secret, what am I doing wrong or how am I not using this well, or what is this? And so we were just talking offline, but I've just launched this course My own course for the first time that encapsulate everything that I do with organizations.
And the idea behind it is we need a framework. We need an education around this. It's not enough to know what it is because we also know what a treadmill and a gym is and all that kind of stuff, but it doesn't help me get in shape. And instead it's, how do we change our behavior? And so I have this, as you kind of referenced this AI mindset framework that says, listen, we're really looking at this all wrong.
We're really looking at it. Like, A tool that we have to figure out how to do like French or calculus or Excel or something like that that we have to learn. But the problem isn't the learning. With those things, the problem is the learning. There's a learning curve and then to practice. Once you know French, speaking French is easy.
The hard part is the learning it. This is the opposite. The learning it is the easy part. There's nothing to learn. You just talk to it as if it was a human. But the actual practice, that's the hard part. And so what I sort of like talk to folks about is, listen, we can't just say, just go out and practice.
Just use it because that's just saying, just eat less and exercise. It doesn't work. What we have to say Hey, you're looking at it this way, but your brain is looking at it this way. So here's how you think about it and here's how you interact with it and everything like that. So that's how I kind of built out a framework and built out this course that I have available now, but that's kind of the big thing.
I think it's starting more with like us rather than the tool.
[00:12:44] Sean Mooney: So if you think about that framework and the practice as a human, what are just some of the basics? I think we've talked about this. Like you talked to it like a human. What does that mean at a high level?
[00:12:57] Conor Grennan: It's funny, right? Because you hear it all the time you hear, Oh, talk to it like a human or treat it like you're an intern or something like that.
Because in theory, again, that should be simple. And it would be simple if it was an actual intern. You know what I mean? Or if it was an actual human, you wouldn't have to think twice. But your brain doesn't let you. So to give an example of that, your brain has these things called neural pathways and your brain automates things.
So if you see a baby, for example, You don't accidentally talk to it like a college professor or something like that, right? You just know to talk to it like a baby. And that's because your brain has automated that. You don't think about things. It's your brain has automated a lot of what you do to kind of free up her prefrontal cortex.
So what's the problem here? Well, the problem here is that in the same way, You wouldn't accidentally talk to a baby like something else when your brain sees something like chat GPT or some other large language model, your brain sees essentially Google. It kind of looks like Google, right? It's a search bar.
And so your brain is saying, I know what this is. It's Google. And somebody could say to you all you want, talk to it like a human. But it's Google. That's hard. In the same way, if you tried to talk to a baby like a college professor, you could do it for a few sentences, but you'd slip back into talking to it like a baby because it's just how it goes, right?
I mean, like, that's why walking and talking backwards and all that kind of stuff is very difficult. You have to really, really focus, whereas going through life normally at normal speed is very normal. In other words, when you see Chachapiti, your brain is telling you it's Google, and it doesn't help that it kind of acts like Google.
If the interface of Chachapiti and other large language models looked instead of like Google, if it looked like, imagine C 3PO from Star Wars, or Data from Star Trek, or Jarvis from Iron Man, or, you know what I mean, like something like that, like, imagine a fictional, all knowing, artificial intelligent robot.
You wouldn't talk to it like Google. You know what I mean? Like, in the same way, like, If you want to ask it about your trip to Costa Rica, if you were doing this with Google, you'd say, give me the top 10 things to do in Costa Rica with my family. And it would give you a great blog post with a lot of great things to do.
But if you were to go into an office and talk to the head of the Costa Rican tourism board, you'd speak much differently. It would be a conversation. You'd be sharing about who you are and what they like and what your kids like, and they like this. They don't like this. Well, Chachapiti is actually acting like the head of the Costa Rican tourism board, but it looks like Google and our brain has a very, very hard time with it.
So it's all about kind of training your brain, which sounds complicated, but it's actually fairly straightforward. If we get into this framework, that's how you have to do it. You actually have to train your brain to think about it differently. That's the complexity around it.
[00:15:33] Sean Mooney: There's just a lot of little tricks.
And one of the things that I picked up from you is to start the conversation with one of these models with the word high. And it's something that completely changed the way that I thought about this. And as I've kind of gone through just other, Kind of deep dives it's high and thank you in the thing you reference the thing that we teach our team members here is like, talk to it like it's a 22 year old or an intern.
Where it's going to be really good at this stage of doing a lot of the kind of basics, but you can't just ask it one thing and think it'll magically happen. It's a dialogue. You can ask it, Hey, what questions do you need to know? And okay, well, this was right now, do these three other things, right? And so where I found a lot of people in our organization, otherwise get frustrated because it's not say one thing and then magic happens just like with a human.
And maybe it's because we get a snatch because we connect all these consultants for projects where. Magic doesn't happen on projects either. Like you got to manage the outcome. And so the content that you have that I've seen in your newsletters have been tremendously helpful and impactful for me. So, and we'll talk about the end about where you can get kind of the course, but I, I fully recommend it knowing that our company has benefited from it as well.
[00:16:52] Conor Grennan: Yeah. Thanks. I think you're right about, I have this kind of very simple model, which is like just HTG, which is high, thanks. Great. And I have it simple because it's easy to remember, but really, It's almost my prompting model and it's just very simple and stupidly simple in a way, but it's say hi to it, say thanks to it and say great to it.
What that really does is it doesn't change the output. of Chachi Petit. It changes us. It changes how we interact with it. And so by saying hi, you're sort of putting your brain in the mode of, Oh, I'm talking to not exactly a person, but something that acts like a person. Saying thanks is actually really interesting too, because what it does is it's sort of this linguistic matching thing that happens in your brain where you actually start really respecting the answer that it gives you.
And yours continues to keep you in that mode of talking to it like a human. And the great part is just. When it gives you an answer, tell it whether you like that answer or not. So you're like, Hey, that was great, or, oh, I didn't really, that wasn't that great. Like number two and three on your list wasn't that great.
But number one was really great because you're right, it's not a magic button. In the same way, if Jeff Bezos walked in right now and I said, Hey, I'm trying to market a shoe company, gimme five things to say, and he could spit five things out and then I'd be like, okay, thanks Jeff. Get outta here, . He's like, well, tell me more about your company.
You know what I mean? Like he would need more information. And so. That's the thing. It's an iterative conversation as if you had Jeff Bezos sitting next to you and talking marketing with Jeff Bezos But we're so used to this Google command response because it looks like Google that we have a hard time with that And so again, this framework is really taking us this framework I have is this learn execute strategize framework and it takes us through like all those things Like how do you like get stuff done?
How do you strategize but to your point? It's really all about how do you just start a conversation? How would you start a conversation with your new colleague that was saying, Hey, I'm new here. How do I do this? What instructions would you give that colleague? You'd do some really practical things. You'd be patient.
You'd say, Hey, here's some examples of what a good thing looks like. I'm going to be clear in my instructions, but good answer would kind of look like this. So you're going to want to do that. And then when that new colleague said, well, how do you like this? You know, how about this? What would you do? You wouldn't say.
Okay. No, that's not right. You're fired. You'd say, okay, well, that's good. But really what you want to do is more like this. You give your colleague additional context and you'd say, okay, tell me how you're thinking about this. Tell me your logic behind how you came up with this answer, all that kind of stuff.
The funny thing is all that works brilliantly with large language models. Why? Because it behaves like a human. That's why it works so well. It really literally means not just talking to it like a human, but talking to it as giving instructions as you would sort of a new colleague or something.
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[00:19:57] Sean Mooney: Yeah. I remember when these things were all kind of this time last year and it was all craze and it's about the same time I saw your presentation and before it was everything was like prompt engineer is going to be the new big thing. And there wasn't enough frameworks in the world to like, figure out that you can have a prompt engineering.
And when I kind of started using your approach, where it talks like a human being and make it a dialogue, not a monologue, it changed everything in terms of the outcomes and the output and the productivity and the usefulness. So I really appreciate that kind of mindset, no pun intended with your newsletter, but it really helped kind of unlock the power of that without having to be a technical person.
And we'll talk a little bit about in a moment, but as I think about where we are today, it feels a lot like 1996, maybe 97 Netscape comes out in 1995. And suddenly the internet, which used to be the bastion of those who could code was their own secret world was unlocked and unleashed to the entire world through a GUI interface that really anyone could figure out.
And just like maybe right before 2023, AI and ML was the bastion of. Those who knew how to code and use SQL and Python. Today, it's opening up this world to everyone, and that's going to have profound impact on our ability to synthesize information, productivity, et cetera, it's still got a ways to go in terms of people figuring out.
And we'll talk about how it's being applied. If you were to think about the things that are going to come from these tools, the productivity. The insights, the ability to synthesize, the ability to learn faster. How do you think about future proofing your career and maybe to put a stencil around it, Conor is like, let's talk about it from the vantage of a middle level professional, kind of a junior level in the queue, but not brand new and then someone who's going to be starting next year.
[00:21:59] Conor Grennan: Yeah, you're right. There are kind of different roles, right? I mean, I would say that working our way down kind of thing from the senior level. You really want to want to rethink hiring almost completely, right? I mean, you're gonna want to rethink about who you bring in. You don't really need to bring in people with strong administrative skills anymore because people are going to be coming in, being able to do that stuff really very quickly now.
I think you can really think about hiring for critical thinking. So if you're at the junior level, what you're really gonna want is to Make sure that you're really fluent on generative AI and showing how you can really expand beyond just what the role they hired you for is, because you can do a lot more than just that one little role.
And I would say that in order to do that, you really want to come up with, not just a framework for yourself, but a framework for how you can bring value to the entire organization in a brand new way that usually entry level type of people are not. able to, I would say then kind of working our way back up with the middle management, it's also really different, right?
I mean, if you can think about how entrepreneurs or solopreneurs would work, you used to have to have. You had your idea, but then you needed a marketer and you needed a coder and you needed to, et cetera. This can really help you create a lot of different elements of your minimum viable product, just yourself, because it fills in a lot of the gaps.
I don't know anything about marketing and I'm never going to be a perfect marketer with Chachapiti. A great marketer will be a much better marketer using Chachapiti than I will be. It doesn't level everybody up to the same level, but it sort of like rises the tide for all your, not weaknesses, but the things you don't know that much.
About. And with that, if you can put that into the corporate setting, essentially, you're going to be in middle management, really being able to communicate with all these different types of departments. So if you're in marketing, you can now connect with the people who know data and everything, because this essentially serves as almost like a translator.
It's like, Hey, this is my idea. What would they need to know? What would they need to see? Like, how are they taking all this? It helps you communicate and converse and negotiate and everything else from that position, which I think is really huge. And then at the senior level, in theory, what this should be doing is it should be taking away a lot of almost any of the busy work that you should be really doing.
And at the senior level, this should become a serious brainstorming. So you are now going to be able to really focus on strategy. And when you focus on strategies in this framework that I kind of teach, it's really going deeper and deeper and having a really deep iterative conversation around deep strategy.
It's not just about getting tasks done anymore at the senior level. It's really about, Hey, now I have this incredible thought partner that I can just keep dumping all my context into, and it'll just keep on feeding and be like, that doesn't really work. What about this? What about this? And it's just an incredible partner that.
Bounces back ideas instantly or at two o'clock in the morning or in any format you want or anything like that. So depending on your level, people are going to be doing sort of the same things, but really like an AI powered work day at all these levels just looks very, very different.
[00:25:00] Sean Mooney: That's very well said.
And think about it. Even I put myself in the lens of kind of that senior level person. Administratively. It's great. I can kind of whip through things really quickly. I don't have like a virtual assistant capability quite yet, but I imagine I'll figure that out eventually. The thing that really resonates as well is this whole kind of like thought partner deal.
Because a lot of times as a, either a business unit leader or a CEO, you're trying to figure things out before you have that conversation and you want to have it thought through. And what I've found these tools to your point, really helpful is like, Hey, what are the pros and cons of doing this? Or what should I think about?
Where am I wrong? Where am I right? How do I have this conversation? And it's amazing at that stuff, in terms of just thinking around a challenge and opportunity and going into a conversation more informed and more prepared in ways that I've ever been able to do so.
[00:25:58] Conor Grennan: Yeah, a hundred percent. You have to start thinking of it as a thought partner, something that you really trust.
And I would even say somebody that you really trust because you're treating it again, it's not a real person, but you're treating it like as you would a colleague or something like that. But as a thought partner and even then going deeper, it's like, well, what do you mean by that? What do you mean by that?
Map that out for me. What would that look like? Okay. Let's play that out. Okay. So now let's test that out. Like create a focus group and like, let's ask them what they think of that. There's just so much you can do. It's almost like having magical powers, as long as. Your imagination allows you to sort of see how far you can push this thing.
[00:26:34] Sean Mooney: I'd love to dig a little deeper as well on the junior professionals, people entering the workforce. And as a quick aside is really an experiment over the last year. We heavily curtailed entry level hiring and we gave everyone an LLM that we had kind of API'd and built purposely for our business and made it available to the And we did things like gamifying it.
in league tables so people would use it more. But we said, we're going to hire less at the entry level. We're going to give everyone an entry level person, but it's an LLM, really to compel people to know how to use these things. And the hypothesis was, this is going to be about as good as an intern or someone right out of college.
And by and large, that's essentially what it was. We saw pretty profound gains in productivity in that entry level. Oh yeah, can you do this? But actually do it this way. And the, you know, the things that you would have someone write out of college so that by the time we hired someone, they were maybe more experienced.
We were saying, well, why don't we just hire a couple of years out now? Because we don't need that 22 year old kind of skillset. And so let's get them more fully formed. And my sense is that people will continue to take them from 22 to 24 and we can let them do the training. And so the thing that as a father, that makes me very concerned is now my kids getting older and one getting ready to go to college, how do they enter the workforce?
Where they're not hiring for that 22 year old capability more and they want to jump to 24. And yet, you still have to have it if you want a job. So, how do you think about that for these newly emergent or future grads where they need to almost like leapfrog an apprenticeship period that likely won't exist?
[00:28:17] Conor Grennan: I think we are going to land there. We're not there yet because I just find adoption is so slow that I'm not sure exactly when this is going to happen. So we're not there yet for sure. And I think you've seen that too, but I will say that I think that this needs to become second nature to the generation that's coming out of college now, kind of starting to enter the workforce now.
But what I definitely would not underestimate is the power that they can bring to an organization by being able to train others on it. And not trained, just like show them what it is. Cause as we talked about, it's not the learning, that's the hard part. It's the execution. That's the hard part. And so I think that if you can be a kind of person in your organization where you say, Hey, I'm really going to get fluent on this and then I'm going to teach everybody else and our team is going to become an AI powered team and our leadership is going to be AI powered leadership companies are absolutely craving that right now.
It's almost more important that you teach sort of everybody to fish, so to speak, rather than. You creating work product and giving it to them, because if you can help get your marketer fluent on generative AI, their work products will be way better than whatever you could produce as a non marketer. So a lot of the value add will actually be there.
It'll be in this moment of, Hey, I'm going to show you all how to do this. We're going to do this together and let me show you what this can look like for our team. And you become an evangelist and a champion in your organization. And that can be done at any level, but certainly I think it's almost required that people.
coming out into the workforce should really understand how to get creative with these tools. That's not supposed to be intimidating. You can get educated out there. If you haven't sort of like figured it out yet, trust me, it is not your fault. It's your brain's fault. And this is how we do it. We sort of look at a framework and we follow this kind of framework and that's what gets us there.
It seems intimidating. It's not, it's just a matter of sort of sitting down with it.
[00:30:10] Sean Mooney: I think that's exactly right, Conor. And you think about generation Z, they're the most digitally native generation yet. And so if anyone should be able to make that leap, it should be them. And maybe this is a deeper conversation, but one of the things that I think that has to happen really quickly is the academic institutions need to run towards this versus away from it.
And know that this is the superpower tool that if these kids come out being skilled with, then they naturally jump 22 to 24, a period that existed before the generative AI era commenced. It should be much more natural to them, certainly to me. And I think if they can embrace that and the institutions embrace it, then the whole world just jumps past that to your apprenticeship of here's how you write an email.
[00:31:02] Conor Grennan: And again, it's, they should know it. The key is, can they pass that information on to their colleagues who don't really get it? That's the big thing. Like you need a framework, you need a way to teach people because if you just come and say like, Hey, everybody just use it. It's like going to people who are out of shape, like me and everything.
And they're saying like, come on, all we have to do just go out and start running. It doesn't work. Like there's ways of changing habits. There's ways of changing all that kind of stuff. But what doesn't work is just to say, just do it. Just try it. It doesn't work. We've been down that road. People are not picking it up because of, I believe in the way that I train anyway at NYU and everywhere else is that because our brain is fighting it.
And so you need a new way of training. It's important to know it yourself, but it's really also important to sort of think, how do I share this information?
[00:31:47] Sean Mooney: And I love that concept of like, you got to change in your mindset, this idea of you're going to move from being a refugee to a missionary, or you're going to come in and embrace it, but then spread the word, if you will.
Hey, as a quick interlude, this is Sean here. I wanted to address one quick question that we regularly get. We often get people who show up at our website, call our account executives and say, Hey, I'm not private equity. Can I still use BluWave to get connected with resources? And the short answer is yes.
Even though we're mostly and largely used by Hundreds of private equity firms, thousands of their portfolio company leaders. Every day we get calls from every day top proactive business leaders at public companies, independent companies, family companies. So absolutely you can use this as well. If you want to use the exact same resources that are trusted and being deployed and perfectly calibrated for your business needs, give us a call.
Visit our website at BluWave. net. Thanks. Back to the episode.
Let's talk a little bit, Conor, like maybe turn the lens forward a little bit. Right now, I think everyone is marveled by generative AI. It's doing some pretty amazing things, but just like in, like, 1996, it's that initial euphoria in my mind where there's a lot of, like, base levels that people are getting, but everyone's trying to figure out, like, what's the next Amazon in this thing?
Or what's the next killer app? At least thus far, I think we've gone through this period of euphoria where the LLMs were strategies in themselves. And don't worry, it's just generative AI. And then naturally, like any of these big crazes and booms and seismic shifts in capability and commerce, they start getting very application specific.
Other than we're not going to cure cancer, we're going to start with patient satisfaction. And then we're going to do this one type of cancer versus everything all at once. And so As you look, given your vantage here into the next five years, what do you think this leads to acknowledging there's brackets in this because who knows?
But where do you see it kind of five years from now going so that business leaders who listen to this can similarly think about, okay, I'm going to think five and 10 years beyond that.
[00:34:09] Conor Grennan: Truthfully, it's pretty hard because it's moving so fast. I would say that it's bound to get more personal. It's bound to start mapping to everybody.
And I think that we're going to start getting into the agent's world sooner or later, which will start very simple. But that just means that you'll have not exactly a large language model, but something like the generative AI tool that will carry out things for you. So instead of just saying, Hey, help me find these flights, you'll just say, Hey, I really need to get from here to Denver tomorrow and we'll go in and we'll find the exact thing that you want.
It'll book it all. I don't think we're that far from that to be totally honest, which is pretty awesome. So that's. What they call like a gentive AI, these things that do it by yourself. I think the other next thing is the companies that will win will really win with user interface. If you can get this, that's easy for people to use.
I think that's absolutely huge. I think the biggest problem with chat GPT is the interface. I'm not sure there's an easy solution for it. I don't have one, but I think that as we start to look out, I think that the real changes will be the sort of the human changes. It's how you restructure your organization.
Now that you know that people can do. A lot more in that you probably need fewer people. If you have 10 copywriters or something like that, you probably don't need 10 copywriters is the truth. And also thinking about it in terms of not so much like where the tech is going, cause that's very hard to predict, but more like what jobs are uniquely human.
Where do you start leaning into? Like, where will people. One, have that very human experience. What does this not replace? And also just as you restructure, this thing takes tasks. It doesn't really take jobs. So how can you take your people and take the tasks off them that are, it's almost like the barnacles off them that have the non value add thing that weighs them down and allow them to be the person that you hire them for and really think, okay, so let's get ready to expand here.
It's not about cost cutting. It's really about let's expand and grow. Using the people that we hired because it's their brains that you really need. And if you can take off the non value add tasks off their shoulders, they can be free to do a lot more. And that to me is really exciting for the future.
[00:36:16] Sean Mooney: That's well said. And I think it's an important mindset that people have to have as well, in terms of, you think about every big kind of tectonic shift in our lives, right? You had first, it was probably the personal computer where you had a computer that showed up at your house as antiquated as that was, Then there was like cell phones and cars, and I remember my parents got like a cell phone in their car.
I
[00:36:39] Conor Grennan: remember that. The car phone. Yeah, I remember that. Yeah.
[00:36:41] Sean Mooney: Then the internet, and then the iPhone, and now generative AI. Each one of those, everyone during each of those times said, you know what, we're going to be like, everyone's going to be displaced, and or you're going to be eating bonbons and caviar on the beach and you have nothing to do.
And in each shift, what's happened is we just did more in the same hours.
[00:37:01] Conor Grennan: Right, exactly.
[00:37:02] Sean Mooney: And so the speed of business. We'll just continue to accelerate. But for some reason, I don't think I'm going to be like drinking martinis or margaritas on the side.
[00:37:14] Conor Grennan: I agree. I know that there's this theory that people need to work less.
They won't really, I just don't see it. I don't see it happening. I don't think that that's how we're built. So we'll find out how it goes.
[00:37:24] Sean Mooney: What you're talking about is really understand it, get up to speed on it, use the tools, And run towards it. I've listed this book on this podcast so many times. I don't know if you all use it at Stern, but Who Moved My Cheese?
[00:37:39] Conor Grennan: Oh yeah, yeah.
[00:37:40] Sean Mooney: It's such a great just foundational book about embracing change and running towards it versus like recoiling in the face of it.
[00:37:47] Conor Grennan: Yeah, no, this is about adoption and I know everything is about adoption, but this for sure. And again, you need some kind of framework or something to get you there because it's not just going to be enough to be like, Let's implement Salesforce and now everybody's on it and let's get rid of the old technology.
It's not like it doesn't act like a digital transformation. That's what I think is so hard.
[00:38:08] Sean Mooney: It's something different, but beautiful and amazing. So one of the things as we kind of bring the altitude back up here, Conor is I love to get people's thoughts on just ways to make things a little easier, a little better.
And like Conor, I have kind of a newsletter I send out once a month that is much less widely read. So Um, in places it is, and one of the things that I just got so infatuated with in my current life and prior life is like just little things to make my life easier. And so I've risen to probably having a problem with my Amazon spend at this point that is enabled by a newsletter I have to send out once a month.
And so that's a different conversation about little brown boxes showing up too often, something my wife will weigh in on later. As she should, justifiably. I'm curious, Conor, given your vantage in figuring all this stuff out, what's maybe a life hack that you've discerned over time that just makes things maybe a little easier, a little better?
[00:39:11] Conor Grennan: Yeah, I think for me, it's the understanding how to change habits when there's things I really want to get done, right? So like, I love books about habits, I hate how to change by Katie Milkman and atomic habits and all these things. And I think for me, it's the understanding that there's actually a formula to it.
And so for me, I like to use like visual cues for my brain to keep my brain on target. So for example, for me, my world is chat, GBT and generative AI. And so I literally would have like a post it note a lot of times on my laptop. If I'm traveling, just saying, don't forget to use chat, GBT, because even I forget to use it all the time.
So for me. It's understanding that there is a pattern to habit formation. There's something you actually have to do. You can't just kind of cross your fingers and hope. And so for me, the latest one that I've been using is this idea of a visual cue, like a posting note saying. This will probably go a lot better if you use ChatGPT or if you, if you go, why don't, why don't you ask the opinion of ChatGPT or something like that.
So for me, it's kind of like those visual nudges for me.
[00:40:10] Sean Mooney: I love that, Q, because it's just personalized. It's so amazing. You have this amazing power at your fingertips. I've got two of the apps on my phone. I've got it on my desktop. And the number of times I just forget to use it and I'll go back to old school Google and then going through 50 web pages.
And then it's just, I suddenly remember. And it's not that it's good or bad, it's just, to your point, it was like the way our brains work. We just get caught in the noise and the fog. And so just by doing something as simple as a sticky note and sticking in front of you, you just can change a behavior and reinforce it over time and then feed it with positive outcomes.
It's a great little trick that I've never thought about. All right, well, this has been really helpful. I'm going to go to our mailroom. We still have a mailroom. It's mostly empty. But I do think there are some sticky notes in there. Yes. I'm gonna go get them right after this because it's a very common sense solution to a problem I have.
[00:41:07] Conor Grennan: Yes, totally.
[00:41:08] Sean Mooney: So, Conor, how can people learn more about your training materials, your newsletter, get in contact with you, etc.?
[00:41:17] Conor Grennan: Thanks for asking. So conorgrenning. com is kind of an easy way to do it. You can find me on LinkedIn and places like that. And I have been trying to get this course together for a long time.
I know I go out to a lot of keynotes and train a lot of big companies, but I wanted to put something out that everybody could actually access. So now I have a course out generative AI for professionals. And you can just find that over on ConorGrenin. com and it's all digital self paced. It's super easy and super fun, but that's the best way to find me.
[00:41:46] Sean Mooney: That's great. I love it. So we'll include that in the episode note and the links therein. So check it out. I'm going to also get it and probably have my kids take it, which will probably be a debate within my household. So, yes. Right. You're welcome. So Conor, this has been amazing. I really appreciate you taking time to pull back the curtain, share insights and all sorts of things.
I wish I knew before. And so for that, I'm extremely, extremely thankful. Thank you so much.
[00:42:16] Conor Grennan: Thank you. Thanks for having me. I really appreciate it.
[00:42:28] Sean Mooney: That's all we have for today. Special thanks to Conor for joining. If you'd like to learn more about Conor, including his new training materials and his AI mindset newsletter. Please see the episode notes for links. Please continue to look for the Karma School of Business podcast anywhere you find your favorite podcasts.
We truly appreciate your support. If you like what you hear, please follow, five star rate, review and share. This is a free way to support the show and it really helps us when you do this. So thank you in advance. In the meantime, if you want to be connected with the world's best in class, private equity grade, professional service providers, independent consultants, interim executives that are deployed and trusted by the best business builders in the world, and you can do the same, give us a call or visit our website at BluWave.net. That's B L U W A V E and we'll support your success. Onward.
Conor is also a New York times bestselling author. He's the chief AI architect at the NYU Stern school of business, and it's the CEO and founder of AI mindset. Enjoy.
So I am very excited to be here today with Conor Grennan. Conor, thanks for joining.
[00:00:48] Conor Grennan: Thank you. Yeah, it's great to be here.
[00:00:50] Sean Mooney: I've been looking for this a long time and maybe as a little bit more. Backstory here. I came to really know of Conor when I was. attending a CEO conference that was in Nashville.
Usually a lot of those things, there's a lot of people on their emails. There's a lot of like content is thrown at you. And then they brought in Conor as a keynote and talking about AI. And this was really last year at the height of buzzword AI and the beginning of AI, maybe fatigue because people didn't really understand it.
And Conor comes out and he has this very unique approach. For those who've seen him, you'll know, and those who haven't. You gotta look him up on LinkedIn and his other areas that we'll get into. He made it so tangible, so understandable for mere mortals. Most of the audience were people kind of with the pigmentation of my hair, which is decidedly gray.
But what was really unique in his content was, as soon as he started getting into it, you saw all these kind of overwhelmed, over sensory, jaded, sometimes CEOs, all start pausing and leaning in and taking notes. I looked around, I was like, what is going on here? Because it was so good and natural. And so now with kind of like the flattery, overwhelmingly aside for Conor, you know, after that, I reached out to him, got in touch.
I read his AI mindset newsletter. He's got great content on LinkedIn. And so we've kept in touch and I asked Conor to be so nice to come and share a perspective into something that I think is going to be one of the biggest trends, certainly of the modern. eras of commercial history here. So Conor, thank you so much for joining.
[00:02:30] Conor Grennan: Yeah, no, this is gonna be cool. Thank you for that very warm and overly kind introduction. I always see people on email. I don't mind, but thank you for saying that. No, absolutely.
[00:02:41] Sean Mooney: Before we jump in too much, Conor, I shared a little bit of the preamble on how we came to know each other. I think it'd be really helpful if you could share kind of the quick story of you and how you kind of got into being really someone who's adding a lot of value in the topic of AI.
[00:02:56] Conor Grennan: Yeah, it's sort of a strange story, right? I don't have a background in AI or machine learning or even tech. Interestingly enough, I'm at NYU Stern School of Business. I'm chief AI architect there. And the way I sort of started was very strange, right? I got my MBA from Stern and then came back a few years later and I became dean of students For the MBA program for the next decade or so.
But when Chachabity came out, I like everybody else was like, Oh, what's this thing? And I tried it out and I tend to just be somebody who just loves to dig and dig and dig. And so I sat down at first, I didn't even know what this thing was. And I was like, well, how do you even interact with it? And my wife, who is more savvy than me, she was like, you know, just ask it stuff, you know?
So I was like, I don't know how that works. So it took me a while to even figure out like what to ask it. But once I did, I went down this crazy rabbit hole for the next two or three or four hours. And I realized right away, like, holy cow, this is going to change everything. And the funny thing is that my first thought was, okay, we have to build some kind of framework to teach our MBA students at NYU.
But the second thing was, well, I better start taking some like machine learning classes and things like that to understand it better. But the funny thing about that was that all those online classes I was taking or NYU classes I was taking. None of it was helping me use generative AI. It's not that it wasn't interesting.
It just, that it didn't have anything to do with it any more than you need to learn about coding to use your iPhone. It was just a very, very different experience. And so that was surprising to me. And it took me down another rabbit hole of, well, let's see how far I can push this and how do we teach this and all that kind of stuff, and it kind of just took off from there.
And I think it's actually helpful that I don't have a tech background because I'm coming at it from everybody who doesn't have a tech background. Not trying to explain what it is, just sort of saying, Hey, this is what this is. It's really unusual. It's really unique. It's all about how we think and everything like that.
The thing that I discovered and kind of stumbled onto was around the fact that this is really about us and our brains. It can do almost anything. But it's not like learning in the past. It's not like there's a learning curve. You have to learn a lot. You just have to know that it's there and available and be able to talk to it like a human, which sort of like weight loss is very simple in concept, but sort of hard in theory.
So I've spent the last 18 months researching that and going out and training companies on that.
[00:05:21] Sean Mooney: I think that's been one of your superpowers because you don't come from the tech side. Before getting BluWave going, I was in private equity for, Nearly 20 years, and the most dreaded conversation I would always have was the CTO conversation, where you go in and they say, well, I don't like dot net, so we got to put it in something else totally.
And then acronyms would start flying at me, and dollars. You would have like heart palpitations, because you're like, I don't know what that means, and you're purposely kind of obfuscating, obscuring it. Whereas when I heard you speak, it was just so. human. It was so conversational. And that's where I think you kind of captured everyone.
And that's why I enjoy reading your newsletter and your content so much. You come from an educator background. You're stern. A lot of your alum are clients of ours. And so I think all of that made it really, really helpful and tangible, particularly someone like myself, who's not a technology person. And so maybe before we go into kind of some of the nuts and bolts about how you make this a more powerful part of your lives and your business world, one of the things I'd love to ask just before you jump into this is.
What are some of the things we'd know you better if we knew this about you? So if there's one thing that you'd share that's maybe not on your LinkedIn profile or otherwise What's something that we know you better if we knew?
[00:06:41] Conor Grennan: I mean, I would probably say just that I lived abroad most of my life after college I graduated from the University of Virginia When I was 21 and I just moved abroad just for the heck of it and I end up working in public policy and Conflict resolution all that kind of stuff peace and reconciliation And the Balkan country.
So I lived in Prague for the next seven years. And I lived in Brussels for another couple of years after that. And then I traveled around the world for a year and then I moved to Nepal. I lived in Nepal for a couple of years and started a nonprofit out there and rescuing traffic kids and things like that.
My entire 20s was spent abroad until I was in my early 30s, I guess. And then I met my wife out in Nepal, who was American, fell in love with her. And that's why I moved back. But yeah, most of my sort of formative years were spent just living and working abroad.
[00:07:28] Sean Mooney: What an amazing adventure. I was one of those kids where I didn't do any of the gap year.
I didn't do any of the adventure. I jumped right in. Other than I made one smart choice. When I was doing the study abroad period, I had the choice of going to London School of Economics or the University of New South Wales and living on a beach. And I think that point in time, I've made the right decision to live on a beach.
And so not nearly as, uh, is kind of amazing and kind of do sack Eastman ish that you've done in terms of adventuring the world, but I'm certainly jealous of that experience. What would be one of the countries, if you could say, all right, you're going to go on one trip this year and you can get there. The whole family and do it tomorrow.
It's all paid, no kind of restrictions. Where would that be?
[00:08:14] Conor Grennan: Man, well, we're going to Thailand kind of at the end of the year. And that's something I'd wanted to do for a long time. I spent a bunch of time in Thailand and just loved it. It's just spectacular and exotic and so far away from my normal life that I can't wait for the family to see that.
[00:08:30] Sean Mooney: What is it about Thailand that kind of jumps off the map?
[00:08:33] Conor Grennan: It's so insanely beautiful and there's so much to see there. I did a lot of rock climbing down to the beaches there and there's just these cliffs overhanging the ocean. So I ended up spending, I don't know, five or six weeks when I was 29 or something like that, just down there, just rock climbing and writing every day because I'm a writer as well.
And I just want them to sort of see and experience what that side of the world looks like.
[00:08:57] Sean Mooney: That'll be amazing. And you get to bring the whole crew and great food, amazing beaches, wonderful people. We'll have to get that on our list with our kids. And so, Conor, maybe if we jump into some of the meat of the conversation here, one of the things that I really appreciated when I saw you speak at the conference was, This practical approach to using some of these technologies are out, particularly large language models, generative A.
I. And so if you were to kind of say here, three of the top approaches that everyone can and should start doing to get more out of these models to get more of the full potential and the additive utility and kind of productivity that comes with them. What would be some of the things you'd recommend?
[00:09:43] Conor Grennan: It's a really good question. Cause it kind of goes to the heart of what these things are and how we interact with them. And I think that maybe just by example, I work a lot with private equity. I work a lot of healthcare kind of across organizations and industries. And the question is always around, well, what tools are the best or what prompts should we use or what are the use cases?
And I used to do that more. I used to kind of give them that, but then I started to realize that And that's because their brain was craving, how do I use this empty box that says, ask anything because the brain doesn't like that, right? The brain likes templates. If you can kind of imagine two ninth grade classes and one teacher says, write a one page paper on anything.
And the other one says, write a one page paper on the last weekend and three people you talked to. The second one is actually easier than the first one, right? Which it shouldn't be. The first one should be easier. It should be easier to write about anything you want, but the brain really likes templates.
And this doesn't give you templates. And so I would say that the first thing that people need to understand is that it's deceptively complicated. Again, in the same way that weight loss is deceptively complicated. There's nothing to learn with something like getting on a treadmill. There's nothing to learn.
But our brain forces us off the treadmill because our brain prioritizes different things. Our brain prioritizes conserving energy and our brain prioritizes quick rewards and things like that. It's a little bit the same with chat GPT. Your brain is not sure what to do with it. There's no template there.
So it's kind of lost in the wilderness a little bit. And I think people are often looking for what's the secret, what am I doing wrong or how am I not using this well, or what is this? And so we were just talking offline, but I've just launched this course My own course for the first time that encapsulate everything that I do with organizations.
And the idea behind it is we need a framework. We need an education around this. It's not enough to know what it is because we also know what a treadmill and a gym is and all that kind of stuff, but it doesn't help me get in shape. And instead it's, how do we change our behavior? And so I have this, as you kind of referenced this AI mindset framework that says, listen, we're really looking at this all wrong.
We're really looking at it. Like, A tool that we have to figure out how to do like French or calculus or Excel or something like that that we have to learn. But the problem isn't the learning. With those things, the problem is the learning. There's a learning curve and then to practice. Once you know French, speaking French is easy.
The hard part is the learning it. This is the opposite. The learning it is the easy part. There's nothing to learn. You just talk to it as if it was a human. But the actual practice, that's the hard part. And so what I sort of like talk to folks about is, listen, we can't just say, just go out and practice.
Just use it because that's just saying, just eat less and exercise. It doesn't work. What we have to say Hey, you're looking at it this way, but your brain is looking at it this way. So here's how you think about it and here's how you interact with it and everything like that. So that's how I kind of built out a framework and built out this course that I have available now, but that's kind of the big thing.
I think it's starting more with like us rather than the tool.
[00:12:44] Sean Mooney: So if you think about that framework and the practice as a human, what are just some of the basics? I think we've talked about this. Like you talked to it like a human. What does that mean at a high level?
[00:12:57] Conor Grennan: It's funny, right? Because you hear it all the time you hear, Oh, talk to it like a human or treat it like you're an intern or something like that.
Because in theory, again, that should be simple. And it would be simple if it was an actual intern. You know what I mean? Or if it was an actual human, you wouldn't have to think twice. But your brain doesn't let you. So to give an example of that, your brain has these things called neural pathways and your brain automates things.
So if you see a baby, for example, You don't accidentally talk to it like a college professor or something like that, right? You just know to talk to it like a baby. And that's because your brain has automated that. You don't think about things. It's your brain has automated a lot of what you do to kind of free up her prefrontal cortex.
So what's the problem here? Well, the problem here is that in the same way, You wouldn't accidentally talk to a baby like something else when your brain sees something like chat GPT or some other large language model, your brain sees essentially Google. It kind of looks like Google, right? It's a search bar.
And so your brain is saying, I know what this is. It's Google. And somebody could say to you all you want, talk to it like a human. But it's Google. That's hard. In the same way, if you tried to talk to a baby like a college professor, you could do it for a few sentences, but you'd slip back into talking to it like a baby because it's just how it goes, right?
I mean, like, that's why walking and talking backwards and all that kind of stuff is very difficult. You have to really, really focus, whereas going through life normally at normal speed is very normal. In other words, when you see Chachapiti, your brain is telling you it's Google, and it doesn't help that it kind of acts like Google.
If the interface of Chachapiti and other large language models looked instead of like Google, if it looked like, imagine C 3PO from Star Wars, or Data from Star Trek, or Jarvis from Iron Man, or, you know what I mean, like something like that, like, imagine a fictional, all knowing, artificial intelligent robot.
You wouldn't talk to it like Google. You know what I mean? Like, in the same way, like, If you want to ask it about your trip to Costa Rica, if you were doing this with Google, you'd say, give me the top 10 things to do in Costa Rica with my family. And it would give you a great blog post with a lot of great things to do.
But if you were to go into an office and talk to the head of the Costa Rican tourism board, you'd speak much differently. It would be a conversation. You'd be sharing about who you are and what they like and what your kids like, and they like this. They don't like this. Well, Chachapiti is actually acting like the head of the Costa Rican tourism board, but it looks like Google and our brain has a very, very hard time with it.
So it's all about kind of training your brain, which sounds complicated, but it's actually fairly straightforward. If we get into this framework, that's how you have to do it. You actually have to train your brain to think about it differently. That's the complexity around it.
[00:15:33] Sean Mooney: There's just a lot of little tricks.
And one of the things that I picked up from you is to start the conversation with one of these models with the word high. And it's something that completely changed the way that I thought about this. And as I've kind of gone through just other, Kind of deep dives it's high and thank you in the thing you reference the thing that we teach our team members here is like, talk to it like it's a 22 year old or an intern.
Where it's going to be really good at this stage of doing a lot of the kind of basics, but you can't just ask it one thing and think it'll magically happen. It's a dialogue. You can ask it, Hey, what questions do you need to know? And okay, well, this was right now, do these three other things, right? And so where I found a lot of people in our organization, otherwise get frustrated because it's not say one thing and then magic happens just like with a human.
And maybe it's because we get a snatch because we connect all these consultants for projects where. Magic doesn't happen on projects either. Like you got to manage the outcome. And so the content that you have that I've seen in your newsletters have been tremendously helpful and impactful for me. So, and we'll talk about the end about where you can get kind of the course, but I, I fully recommend it knowing that our company has benefited from it as well.
[00:16:52] Conor Grennan: Yeah. Thanks. I think you're right about, I have this kind of very simple model, which is like just HTG, which is high, thanks. Great. And I have it simple because it's easy to remember, but really, It's almost my prompting model and it's just very simple and stupidly simple in a way, but it's say hi to it, say thanks to it and say great to it.
What that really does is it doesn't change the output. of Chachi Petit. It changes us. It changes how we interact with it. And so by saying hi, you're sort of putting your brain in the mode of, Oh, I'm talking to not exactly a person, but something that acts like a person. Saying thanks is actually really interesting too, because what it does is it's sort of this linguistic matching thing that happens in your brain where you actually start really respecting the answer that it gives you.
And yours continues to keep you in that mode of talking to it like a human. And the great part is just. When it gives you an answer, tell it whether you like that answer or not. So you're like, Hey, that was great, or, oh, I didn't really, that wasn't that great. Like number two and three on your list wasn't that great.
But number one was really great because you're right, it's not a magic button. In the same way, if Jeff Bezos walked in right now and I said, Hey, I'm trying to market a shoe company, gimme five things to say, and he could spit five things out and then I'd be like, okay, thanks Jeff. Get outta here, . He's like, well, tell me more about your company.
You know what I mean? Like he would need more information. And so. That's the thing. It's an iterative conversation as if you had Jeff Bezos sitting next to you and talking marketing with Jeff Bezos But we're so used to this Google command response because it looks like Google that we have a hard time with that And so again, this framework is really taking us this framework I have is this learn execute strategize framework and it takes us through like all those things Like how do you like get stuff done?
How do you strategize but to your point? It's really all about how do you just start a conversation? How would you start a conversation with your new colleague that was saying, Hey, I'm new here. How do I do this? What instructions would you give that colleague? You'd do some really practical things. You'd be patient.
You'd say, Hey, here's some examples of what a good thing looks like. I'm going to be clear in my instructions, but good answer would kind of look like this. So you're going to want to do that. And then when that new colleague said, well, how do you like this? You know, how about this? What would you do? You wouldn't say.
Okay. No, that's not right. You're fired. You'd say, okay, well, that's good. But really what you want to do is more like this. You give your colleague additional context and you'd say, okay, tell me how you're thinking about this. Tell me your logic behind how you came up with this answer, all that kind of stuff.
The funny thing is all that works brilliantly with large language models. Why? Because it behaves like a human. That's why it works so well. It really literally means not just talking to it like a human, but talking to it as giving instructions as you would sort of a new colleague or something.
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[00:19:57] Sean Mooney: Yeah. I remember when these things were all kind of this time last year and it was all craze and it's about the same time I saw your presentation and before it was everything was like prompt engineer is going to be the new big thing. And there wasn't enough frameworks in the world to like, figure out that you can have a prompt engineering.
And when I kind of started using your approach, where it talks like a human being and make it a dialogue, not a monologue, it changed everything in terms of the outcomes and the output and the productivity and the usefulness. So I really appreciate that kind of mindset, no pun intended with your newsletter, but it really helped kind of unlock the power of that without having to be a technical person.
And we'll talk a little bit about in a moment, but as I think about where we are today, it feels a lot like 1996, maybe 97 Netscape comes out in 1995. And suddenly the internet, which used to be the bastion of those who could code was their own secret world was unlocked and unleashed to the entire world through a GUI interface that really anyone could figure out.
And just like maybe right before 2023, AI and ML was the bastion of. Those who knew how to code and use SQL and Python. Today, it's opening up this world to everyone, and that's going to have profound impact on our ability to synthesize information, productivity, et cetera, it's still got a ways to go in terms of people figuring out.
And we'll talk about how it's being applied. If you were to think about the things that are going to come from these tools, the productivity. The insights, the ability to synthesize, the ability to learn faster. How do you think about future proofing your career and maybe to put a stencil around it, Conor is like, let's talk about it from the vantage of a middle level professional, kind of a junior level in the queue, but not brand new and then someone who's going to be starting next year.
[00:21:59] Conor Grennan: Yeah, you're right. There are kind of different roles, right? I mean, I would say that working our way down kind of thing from the senior level. You really want to want to rethink hiring almost completely, right? I mean, you're gonna want to rethink about who you bring in. You don't really need to bring in people with strong administrative skills anymore because people are going to be coming in, being able to do that stuff really very quickly now.
I think you can really think about hiring for critical thinking. So if you're at the junior level, what you're really gonna want is to Make sure that you're really fluent on generative AI and showing how you can really expand beyond just what the role they hired you for is, because you can do a lot more than just that one little role.
And I would say that in order to do that, you really want to come up with, not just a framework for yourself, but a framework for how you can bring value to the entire organization in a brand new way that usually entry level type of people are not. able to, I would say then kind of working our way back up with the middle management, it's also really different, right?
I mean, if you can think about how entrepreneurs or solopreneurs would work, you used to have to have. You had your idea, but then you needed a marketer and you needed a coder and you needed to, et cetera. This can really help you create a lot of different elements of your minimum viable product, just yourself, because it fills in a lot of the gaps.
I don't know anything about marketing and I'm never going to be a perfect marketer with Chachapiti. A great marketer will be a much better marketer using Chachapiti than I will be. It doesn't level everybody up to the same level, but it sort of like rises the tide for all your, not weaknesses, but the things you don't know that much.
About. And with that, if you can put that into the corporate setting, essentially, you're going to be in middle management, really being able to communicate with all these different types of departments. So if you're in marketing, you can now connect with the people who know data and everything, because this essentially serves as almost like a translator.
It's like, Hey, this is my idea. What would they need to know? What would they need to see? Like, how are they taking all this? It helps you communicate and converse and negotiate and everything else from that position, which I think is really huge. And then at the senior level, in theory, what this should be doing is it should be taking away a lot of almost any of the busy work that you should be really doing.
And at the senior level, this should become a serious brainstorming. So you are now going to be able to really focus on strategy. And when you focus on strategies in this framework that I kind of teach, it's really going deeper and deeper and having a really deep iterative conversation around deep strategy.
It's not just about getting tasks done anymore at the senior level. It's really about, Hey, now I have this incredible thought partner that I can just keep dumping all my context into, and it'll just keep on feeding and be like, that doesn't really work. What about this? What about this? And it's just an incredible partner that.
Bounces back ideas instantly or at two o'clock in the morning or in any format you want or anything like that. So depending on your level, people are going to be doing sort of the same things, but really like an AI powered work day at all these levels just looks very, very different.
[00:25:00] Sean Mooney: That's very well said.
And think about it. Even I put myself in the lens of kind of that senior level person. Administratively. It's great. I can kind of whip through things really quickly. I don't have like a virtual assistant capability quite yet, but I imagine I'll figure that out eventually. The thing that really resonates as well is this whole kind of like thought partner deal.
Because a lot of times as a, either a business unit leader or a CEO, you're trying to figure things out before you have that conversation and you want to have it thought through. And what I've found these tools to your point, really helpful is like, Hey, what are the pros and cons of doing this? Or what should I think about?
Where am I wrong? Where am I right? How do I have this conversation? And it's amazing at that stuff, in terms of just thinking around a challenge and opportunity and going into a conversation more informed and more prepared in ways that I've ever been able to do so.
[00:25:58] Conor Grennan: Yeah, a hundred percent. You have to start thinking of it as a thought partner, something that you really trust.
And I would even say somebody that you really trust because you're treating it again, it's not a real person, but you're treating it like as you would a colleague or something like that. But as a thought partner and even then going deeper, it's like, well, what do you mean by that? What do you mean by that?
Map that out for me. What would that look like? Okay. Let's play that out. Okay. So now let's test that out. Like create a focus group and like, let's ask them what they think of that. There's just so much you can do. It's almost like having magical powers, as long as. Your imagination allows you to sort of see how far you can push this thing.
[00:26:34] Sean Mooney: I'd love to dig a little deeper as well on the junior professionals, people entering the workforce. And as a quick aside is really an experiment over the last year. We heavily curtailed entry level hiring and we gave everyone an LLM that we had kind of API'd and built purposely for our business and made it available to the And we did things like gamifying it.
in league tables so people would use it more. But we said, we're going to hire less at the entry level. We're going to give everyone an entry level person, but it's an LLM, really to compel people to know how to use these things. And the hypothesis was, this is going to be about as good as an intern or someone right out of college.
And by and large, that's essentially what it was. We saw pretty profound gains in productivity in that entry level. Oh yeah, can you do this? But actually do it this way. And the, you know, the things that you would have someone write out of college so that by the time we hired someone, they were maybe more experienced.
We were saying, well, why don't we just hire a couple of years out now? Because we don't need that 22 year old kind of skillset. And so let's get them more fully formed. And my sense is that people will continue to take them from 22 to 24 and we can let them do the training. And so the thing that as a father, that makes me very concerned is now my kids getting older and one getting ready to go to college, how do they enter the workforce?
Where they're not hiring for that 22 year old capability more and they want to jump to 24. And yet, you still have to have it if you want a job. So, how do you think about that for these newly emergent or future grads where they need to almost like leapfrog an apprenticeship period that likely won't exist?
[00:28:17] Conor Grennan: I think we are going to land there. We're not there yet because I just find adoption is so slow that I'm not sure exactly when this is going to happen. So we're not there yet for sure. And I think you've seen that too, but I will say that I think that this needs to become second nature to the generation that's coming out of college now, kind of starting to enter the workforce now.
But what I definitely would not underestimate is the power that they can bring to an organization by being able to train others on it. And not trained, just like show them what it is. Cause as we talked about, it's not the learning, that's the hard part. It's the execution. That's the hard part. And so I think that if you can be a kind of person in your organization where you say, Hey, I'm really going to get fluent on this and then I'm going to teach everybody else and our team is going to become an AI powered team and our leadership is going to be AI powered leadership companies are absolutely craving that right now.
It's almost more important that you teach sort of everybody to fish, so to speak, rather than. You creating work product and giving it to them, because if you can help get your marketer fluent on generative AI, their work products will be way better than whatever you could produce as a non marketer. So a lot of the value add will actually be there.
It'll be in this moment of, Hey, I'm going to show you all how to do this. We're going to do this together and let me show you what this can look like for our team. And you become an evangelist and a champion in your organization. And that can be done at any level, but certainly I think it's almost required that people.
coming out into the workforce should really understand how to get creative with these tools. That's not supposed to be intimidating. You can get educated out there. If you haven't sort of like figured it out yet, trust me, it is not your fault. It's your brain's fault. And this is how we do it. We sort of look at a framework and we follow this kind of framework and that's what gets us there.
It seems intimidating. It's not, it's just a matter of sort of sitting down with it.
[00:30:10] Sean Mooney: I think that's exactly right, Conor. And you think about generation Z, they're the most digitally native generation yet. And so if anyone should be able to make that leap, it should be them. And maybe this is a deeper conversation, but one of the things that I think that has to happen really quickly is the academic institutions need to run towards this versus away from it.
And know that this is the superpower tool that if these kids come out being skilled with, then they naturally jump 22 to 24, a period that existed before the generative AI era commenced. It should be much more natural to them, certainly to me. And I think if they can embrace that and the institutions embrace it, then the whole world just jumps past that to your apprenticeship of here's how you write an email.
[00:31:02] Conor Grennan: And again, it's, they should know it. The key is, can they pass that information on to their colleagues who don't really get it? That's the big thing. Like you need a framework, you need a way to teach people because if you just come and say like, Hey, everybody just use it. It's like going to people who are out of shape, like me and everything.
And they're saying like, come on, all we have to do just go out and start running. It doesn't work. Like there's ways of changing habits. There's ways of changing all that kind of stuff. But what doesn't work is just to say, just do it. Just try it. It doesn't work. We've been down that road. People are not picking it up because of, I believe in the way that I train anyway at NYU and everywhere else is that because our brain is fighting it.
And so you need a new way of training. It's important to know it yourself, but it's really also important to sort of think, how do I share this information?
[00:31:47] Sean Mooney: And I love that concept of like, you got to change in your mindset, this idea of you're going to move from being a refugee to a missionary, or you're going to come in and embrace it, but then spread the word, if you will.
Hey, as a quick interlude, this is Sean here. I wanted to address one quick question that we regularly get. We often get people who show up at our website, call our account executives and say, Hey, I'm not private equity. Can I still use BluWave to get connected with resources? And the short answer is yes.
Even though we're mostly and largely used by Hundreds of private equity firms, thousands of their portfolio company leaders. Every day we get calls from every day top proactive business leaders at public companies, independent companies, family companies. So absolutely you can use this as well. If you want to use the exact same resources that are trusted and being deployed and perfectly calibrated for your business needs, give us a call.
Visit our website at BluWave. net. Thanks. Back to the episode.
Let's talk a little bit, Conor, like maybe turn the lens forward a little bit. Right now, I think everyone is marveled by generative AI. It's doing some pretty amazing things, but just like in, like, 1996, it's that initial euphoria in my mind where there's a lot of, like, base levels that people are getting, but everyone's trying to figure out, like, what's the next Amazon in this thing?
Or what's the next killer app? At least thus far, I think we've gone through this period of euphoria where the LLMs were strategies in themselves. And don't worry, it's just generative AI. And then naturally, like any of these big crazes and booms and seismic shifts in capability and commerce, they start getting very application specific.
Other than we're not going to cure cancer, we're going to start with patient satisfaction. And then we're going to do this one type of cancer versus everything all at once. And so As you look, given your vantage here into the next five years, what do you think this leads to acknowledging there's brackets in this because who knows?
But where do you see it kind of five years from now going so that business leaders who listen to this can similarly think about, okay, I'm going to think five and 10 years beyond that.
[00:34:09] Conor Grennan: Truthfully, it's pretty hard because it's moving so fast. I would say that it's bound to get more personal. It's bound to start mapping to everybody.
And I think that we're going to start getting into the agent's world sooner or later, which will start very simple. But that just means that you'll have not exactly a large language model, but something like the generative AI tool that will carry out things for you. So instead of just saying, Hey, help me find these flights, you'll just say, Hey, I really need to get from here to Denver tomorrow and we'll go in and we'll find the exact thing that you want.
It'll book it all. I don't think we're that far from that to be totally honest, which is pretty awesome. So that's. What they call like a gentive AI, these things that do it by yourself. I think the other next thing is the companies that will win will really win with user interface. If you can get this, that's easy for people to use.
I think that's absolutely huge. I think the biggest problem with chat GPT is the interface. I'm not sure there's an easy solution for it. I don't have one, but I think that as we start to look out, I think that the real changes will be the sort of the human changes. It's how you restructure your organization.
Now that you know that people can do. A lot more in that you probably need fewer people. If you have 10 copywriters or something like that, you probably don't need 10 copywriters is the truth. And also thinking about it in terms of not so much like where the tech is going, cause that's very hard to predict, but more like what jobs are uniquely human.
Where do you start leaning into? Like, where will people. One, have that very human experience. What does this not replace? And also just as you restructure, this thing takes tasks. It doesn't really take jobs. So how can you take your people and take the tasks off them that are, it's almost like the barnacles off them that have the non value add thing that weighs them down and allow them to be the person that you hire them for and really think, okay, so let's get ready to expand here.
It's not about cost cutting. It's really about let's expand and grow. Using the people that we hired because it's their brains that you really need. And if you can take off the non value add tasks off their shoulders, they can be free to do a lot more. And that to me is really exciting for the future.
[00:36:16] Sean Mooney: That's well said. And I think it's an important mindset that people have to have as well, in terms of, you think about every big kind of tectonic shift in our lives, right? You had first, it was probably the personal computer where you had a computer that showed up at your house as antiquated as that was, Then there was like cell phones and cars, and I remember my parents got like a cell phone in their car.
I
[00:36:39] Conor Grennan: remember that. The car phone. Yeah, I remember that. Yeah.
[00:36:41] Sean Mooney: Then the internet, and then the iPhone, and now generative AI. Each one of those, everyone during each of those times said, you know what, we're going to be like, everyone's going to be displaced, and or you're going to be eating bonbons and caviar on the beach and you have nothing to do.
And in each shift, what's happened is we just did more in the same hours.
[00:37:01] Conor Grennan: Right, exactly.
[00:37:02] Sean Mooney: And so the speed of business. We'll just continue to accelerate. But for some reason, I don't think I'm going to be like drinking martinis or margaritas on the side.
[00:37:14] Conor Grennan: I agree. I know that there's this theory that people need to work less.
They won't really, I just don't see it. I don't see it happening. I don't think that that's how we're built. So we'll find out how it goes.
[00:37:24] Sean Mooney: What you're talking about is really understand it, get up to speed on it, use the tools, And run towards it. I've listed this book on this podcast so many times. I don't know if you all use it at Stern, but Who Moved My Cheese?
[00:37:39] Conor Grennan: Oh yeah, yeah.
[00:37:40] Sean Mooney: It's such a great just foundational book about embracing change and running towards it versus like recoiling in the face of it.
[00:37:47] Conor Grennan: Yeah, no, this is about adoption and I know everything is about adoption, but this for sure. And again, you need some kind of framework or something to get you there because it's not just going to be enough to be like, Let's implement Salesforce and now everybody's on it and let's get rid of the old technology.
It's not like it doesn't act like a digital transformation. That's what I think is so hard.
[00:38:08] Sean Mooney: It's something different, but beautiful and amazing. So one of the things as we kind of bring the altitude back up here, Conor is I love to get people's thoughts on just ways to make things a little easier, a little better.
And like Conor, I have kind of a newsletter I send out once a month that is much less widely read. So Um, in places it is, and one of the things that I just got so infatuated with in my current life and prior life is like just little things to make my life easier. And so I've risen to probably having a problem with my Amazon spend at this point that is enabled by a newsletter I have to send out once a month.
And so that's a different conversation about little brown boxes showing up too often, something my wife will weigh in on later. As she should, justifiably. I'm curious, Conor, given your vantage in figuring all this stuff out, what's maybe a life hack that you've discerned over time that just makes things maybe a little easier, a little better?
[00:39:11] Conor Grennan: Yeah, I think for me, it's the understanding how to change habits when there's things I really want to get done, right? So like, I love books about habits, I hate how to change by Katie Milkman and atomic habits and all these things. And I think for me, it's the understanding that there's actually a formula to it.
And so for me, I like to use like visual cues for my brain to keep my brain on target. So for example, for me, my world is chat, GBT and generative AI. And so I literally would have like a post it note a lot of times on my laptop. If I'm traveling, just saying, don't forget to use chat, GBT, because even I forget to use it all the time.
So for me. It's understanding that there is a pattern to habit formation. There's something you actually have to do. You can't just kind of cross your fingers and hope. And so for me, the latest one that I've been using is this idea of a visual cue, like a posting note saying. This will probably go a lot better if you use ChatGPT or if you, if you go, why don't, why don't you ask the opinion of ChatGPT or something like that.
So for me, it's kind of like those visual nudges for me.
[00:40:10] Sean Mooney: I love that, Q, because it's just personalized. It's so amazing. You have this amazing power at your fingertips. I've got two of the apps on my phone. I've got it on my desktop. And the number of times I just forget to use it and I'll go back to old school Google and then going through 50 web pages.
And then it's just, I suddenly remember. And it's not that it's good or bad, it's just, to your point, it was like the way our brains work. We just get caught in the noise and the fog. And so just by doing something as simple as a sticky note and sticking in front of you, you just can change a behavior and reinforce it over time and then feed it with positive outcomes.
It's a great little trick that I've never thought about. All right, well, this has been really helpful. I'm going to go to our mailroom. We still have a mailroom. It's mostly empty. But I do think there are some sticky notes in there. Yes. I'm gonna go get them right after this because it's a very common sense solution to a problem I have.
[00:41:07] Conor Grennan: Yes, totally.
[00:41:08] Sean Mooney: So, Conor, how can people learn more about your training materials, your newsletter, get in contact with you, etc.?
[00:41:17] Conor Grennan: Thanks for asking. So conorgrenning. com is kind of an easy way to do it. You can find me on LinkedIn and places like that. And I have been trying to get this course together for a long time.
I know I go out to a lot of keynotes and train a lot of big companies, but I wanted to put something out that everybody could actually access. So now I have a course out generative AI for professionals. And you can just find that over on ConorGrenin. com and it's all digital self paced. It's super easy and super fun, but that's the best way to find me.
[00:41:46] Sean Mooney: That's great. I love it. So we'll include that in the episode note and the links therein. So check it out. I'm going to also get it and probably have my kids take it, which will probably be a debate within my household. So, yes. Right. You're welcome. So Conor, this has been amazing. I really appreciate you taking time to pull back the curtain, share insights and all sorts of things.
I wish I knew before. And so for that, I'm extremely, extremely thankful. Thank you so much.
[00:42:16] Conor Grennan: Thank you. Thanks for having me. I really appreciate it.
[00:42:28] Sean Mooney: That's all we have for today. Special thanks to Conor for joining. If you'd like to learn more about Conor, including his new training materials and his AI mindset newsletter. Please see the episode notes for links. Please continue to look for the Karma School of Business podcast anywhere you find your favorite podcasts.
We truly appreciate your support. If you like what you hear, please follow, five star rate, review and share. This is a free way to support the show and it really helps us when you do this. So thank you in advance. In the meantime, if you want to be connected with the world's best in class, private equity grade, professional service providers, independent consultants, interim executives that are deployed and trusted by the best business builders in the world, and you can do the same, give us a call or visit our website at BluWave.net. That's B L U W A V E and we'll support your success. Onward.
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Private equity insights for and with top business builders, including investors, operators, executives and industry thought leaders. The Karma School of Business Podcast goes behind the scenes of PE, talking about business best practices and real-time industry trends. You'll learn from leading professionals and visionary business executives who will help you take action and enhance your life, whether you’re at a PE firm, a portco or a private or public company.
BluWave Founder & CEO Sean Mooney hosts the Private Equity Karma School of Business Podcast. BluWave is the business builders’ network for private equity grade due diligence and value creation needs.
BluWave Founder & CEO Sean Mooney hosts the Private Equity Karma School of Business Podcast. BluWave is the business builders’ network for private equity grade due diligence and value creation needs.
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