Barry O'Reilly - How to Keep the Humanity in Artificial Organizations

These frontier lab companies have billions of dollars to spend on marketing. They want you to feel fear you're behind. You're going to lose your job. Everyone else is doing it. You're not doing it. Combine that with influencers who are again, optimized to sort of create wow, fear selling of look, all the amazing things I can do. Can you do this? They're paying to do it. And they're incentivized to do it. The, the feed is not a reflection of the reality. You're not behind, but you need to start where you are. You cannot freeze. That's the worst thing to do. Hello and welcome to one night in product, the show where I chat to some of the brightest minds in and around product from across the globe to help you see product management in a whole new light. If that sounds up your street, don't forget to dive into the back catalog on your favorite podcast app or on YouTube. And of course, follow, share, or drop me a comment or review. It all helps keep the lights on. On this episode, I'm speaking to Barry O'Reilly. Barry's an entrepreneur, executive advisor, and author who works with senior leaders to redesign how the organizations perform, hopefully for the better, Barry has a long storied career, including leading transformation efforts for up and coming companies like British airways, baptism, the economist sort of almost working with Elon Musk back in the day, a lucky escape there, some might say, and also the bestselling author of lean enterprise and unlearn. Now Barry's got the AI bargain is back with a new book, artificial organizations that says the AI isn't replacing leaders. It's exposing them. Well, let's hope it's at least got the decency to put some little black bars over their sensitive parts. Barry, thanks for coming. And welcome to the show. Listen, I have been dying to do this show for a long time. So I am very happy to be here. Well, it's good to have you here. We're going to get through this together. We're going to uncover everything about AI. We're going to learn and unlearn and all these other things that we do along the way, and we're going to come out better people and better leaders. I'm sure. But let's talk about you to start with. It's been a bit since unlearn came out a few years back, obviously lean enterprise as well. You're out there in Asia now doing all of the things and just kind of curious, you know, for people that maybe don't know you or aren't up to date with what you're working on. What are you working on these days and kind of what's keeping you busy? Yeah. Thanks. Um, so I think, uh, a little bit around after unlearn came out in 2021, I started an early stage AI incubator called nobody studios with our goal was to try and build a hundred companies over the next five years. So I've been literally been spending my time, uh, figuring out, you know, how to use these new technologies to build companies cheaper, faster, better, and really, I guess, artificial organizations is sort of the lessons learned from that. You know, when we first started the studio, I think some of these tools really like they were nowhere near what they are today, I think the, um, you know, the, the chat GBT moment that most people experienced in 23 really even shifted how we pivoted the whole studio. Like simple things like even our financial models, we were expecting our startup teams to have anywhere between six or 10 people as they were scaling. And, uh, we were investing a quarter of a million dollars over 12 months to sort of incubate these companies and get them going, but today, like our teams are a fraction of the size. You're we, we model around four to six people, someone who can sell someone who can build someone who can support customers and go to markets. And then you just, you load around where you have opportunity to go faster. Um, so fundamentally, so many things that I was even thinking about four or five years ago have shifted, but the most important ones is probably how I work. And a lot of that has been inspired from leveraging these tools, not, not to do my job, but to support me in how I work. And that's really what the book is sort of inspiration for it is about. But would you say that you're now like a hundred X Barry O'Reilly, or you sort of somewhere in between zero and a hundred L one and a hundred X at the moment, a hundred X is a, you know, everyone's talking about how they were a hundred X in everything. I just wondered how many Xs you've got to so far. You've obviously thrown yourself into it. You've, uh, you've obviously, you know, presumably made a few mistakes along the way as you've been kind of learning some of this stuff, and then you've kind of come back and sort of told us or written a book to tell us all about where you're at now and some of the things you've learned. But I just wondered, cause I'm being slightly cheeky with the hundred X thing, but like at the same time, is there, could you even put a number on like, like a percentage number, an X number on what you think, like the, the impact on what you've been doing, like you talked about how you work, but how many Xs do you think you've gone up in that with the stuff? Yeah, no, it's a great question. Um, so the way I think about it, um, is I used to sort of have a ratio of what percentage of my time was spent on doing like necessary administrative work, you know, like filling out the JIRA tickets and following up on the, you know, it, did it get done or not, right. Versus how much of my time was creative problem solving on the really like, you know, the naughty difficult problems. And when, when I asked most people that they always say they've been, they've an 80 20 split, you know, they've about 20% of their time is on the problem solving and 80% is admin. And especially as you're an exec, it's even worse. You're just, you feel like you're just going from meeting to meeting, to admin, to admin, this stack of stuff filling up behind you. So, but how I tend to think about it now is I have managed to reduce that admin work like massively. I would say maybe two orders of magnitude. So I sort of feel like I'm sitting now in this sort of 60% creative problem solving 40% necessary admin, which is like, to your point, it's probably a. It's 200% increase in that capacity of problem solving. But I think the thing that's really, really important that, that your, your, your influencers that are building 7,000 agents on the weekend and making $10,000 a month with affiliate marketing deals don't talk about is that that capacity is not necessarily activity. It's actually time where I'm thinking. I go for a walk and deeply considering a problem. It's it's time where I'm like creating things and prototyping them and testing them, um, which I just didn't have before. Right. I was on, I was on the treadmill like everybody else. And I think that has really surprised me where I'm like, actually, I've got time now to think, and that, which I believe is helping me make better decisions. I'm showing up better. Um, and we'll talk a little bit more about how, like how presence I think is so important now in leadership, but, um, that's, that's how I think about it. I'm not, I know you're, you're, you're tongue in cheek with your a hundred X, but I just feel, I feel more present as a leader and, and that actually. I'm proud to present both at work and present at home. And that that's a gift in my world anyway. No, absolutely. And yeah, we'll absolutely talk about some of those topics as well. But, you know, those topics, uh, be kind of enunciated in the book that you've kind of already alluded to. We talked about the introduction or, uh, artificial organizations. So you kind of said already that that was almost kind of like that almost was the, the output of all the things that you'd learned along the way. And you felt, I guess, the need to get out. You obviously written books before, you know, how much of an undertaking it can be to write a book, but you wanted to write another one anyway. Was that something that kind of almost inevitably had to come out of the learning journey that you'd gone on? Or was there like another kind of almost, uh, kind of starting point or a tipping point that, that made you think that that was a good idea to get that book out there? So, so the, um, most people don't know this, but I'm dyslexic. I have a, I've a solid history of D minuses in English literature. If my teacher knew that I'd written three books, they wouldn't believe you, believe you, you know, and, um, and actually unlearn funnily enough was one of the breakthrough moments for me when I first started to understand how I could use technology to support how I work. So I, I had this view, right. As writers that they're like, you know, sitting by a roaring fire with a purple jacket on drinking wine, just like, you know, chugging it down and tearing pages off and so, you know, I sat by fires, I drank a lot of wine, but like I wasn't writing very much, you know, but, um, but the sort of aha for me was this is sort of like the archetype, right? Like that archetype was what I thought a writer did or how you made a book. Yeah. But the reframe I really had was, well, hang on a sec. How, how do I do my best work? Like typing is difficult for me. Like I I'm trying to type a word and then I figure out how do you spell thought or through or how is it? Like I get stuck. So my natural trait for doing a lot of innovative work is actually talking. I like talking out ideas. Like I love podcasts, like back and forth, debating things. It's, it's a really energizing way for me to, to ideate. And then the task I like of writing a book, it's, it's not typing, it's creating content and there's so many ways to create content. So as soon as I was like, all right, talking is my natural trait. The task is creating content. So if I just have a tool that can help me, I capture. And if you transcribe me talking, then I could be way more efficient. So I ended up hiring a journalist and the journalist would interview me. We'd bullet point out the chapters and they would interview me and we would talk for like 40 minutes. And I would get like a 10,000 words and they would take the recording and send it to an AI transcription service and get it back in like a few minutes and then they would copy edit the chapter and almost send me in like an MVP chapter three within an hour and a half. So I would go from creation to sort of iteration in about two hours. And I'd be like, oh, I forgot that story. And this actually should, I wouldn't say it like this. And so I was moving so quickly. It almost felt like I was cheating. Um, and it was, this was the whole idea of where I sort of had the aha moment. It's like, actually we've got this wrong. Like I've, I've spent so much of my time trying to shoehorn myself into a way that I thought work should be done. But if I redesign this approach and leverage my natural traits, my natural abilities and understand the task I'm focused on and have a tool there to support me, like that iteration, just it, I was just accelerating so fast. And to the point earlier, the admin work started going away. All of that work was like creative problem solving, right? Thinking of the ideas, iterating and tweaking the chapters, right. That the admin of typing it all up or getting the idea, like that was just being reduced. So that's sort of, you know, how I first sort of had this aha moment was like, right, well, what else can I use this for? And that was my launch point. Yeah. It's interesting because I actually was going to make a cheeky point about the fact that the very first page of the book had like EM dashes in, which is obviously what people start to talk about. Oh, yeah. That's been written by AI in the first place. It would feel almost bullying to sort of go down that line now, but it is an interesting point, this idea of like the mechanical stuff, the mechanical aspects of writing and drafting and redrafting and spell checking and editing and all of that stuff, like it's all important. It's something that people have been doing for years when, you know, for time in memorials, you know, since I've been making books and it does feel then on the one hand, you can sit there and say from a purist perspective, well, that's part of the craft, right? Like you need to do that stuff. If you don't do that stuff, like in the age old fashion, then somehow you're not doing the job. But it does open up a whole new fascinating idea that who cares? Like who cares how that bit was done as long as it was done in some way. And as long as the output is good. Because then, and I know we want to talk a little bit about AI slop later, but there's this kind of almost debate on, you know, with like social media and marketing copy and such around like, well, yeah, you can tell it's AI and you can tell that they've just like kind of crapped it out and obviously that's not what you're talking about, but there's this almost, almost a pushback against if it looks a bit too AI or if it looks like it's too assisted. But again, first of all, with dyslexia, assistance is a good thing, right? But also at the same time, typing was never the job, right? So I guess then that almost naturally leads into this idea of with the book about that is also true about leadership and probably a lot about other jobs. So it kind of feels like that, that journey almost then set the scene for the book and maybe some of the stuff that you're doing these days. Is that fair enough? Absolutely. Right. Because for me, I always see the tools as a support mechanism to help me do my best work. And if I can recognize how I do my best work, then I can really focus on that. And then the tools that be there to support me. So to your point, you know, the logical progression for me after using a transcription service, like when I was trying to write the book, the next step was, well, where, where else are the moments where I create the most amount of value? And for me, again, it was meetings, right? I was often in meetings with founders in the studio, meetings with execs where I'm coaching. And like anyone I'd be in a meeting and they'd be talking to me and I'm scribbling down notes and I'm thinking about the meeting from the last one. And I'm thinking about what I got to have for lunch. And I'm thinking all this stuff in my head. Right. So again, um, I started using a meeting co-pilot in literally 2016. And everywhere I went in meetings, that, that meeting co-pilot was with me. So I started capturing every conversation and started turning it into a data asset. Every coaching call, every person I spoke to and the way it showed up is I would show up in those meetings actually with an empty head. I wouldn't be worried about what was the last meeting? What were the actions? What were the, because I knew I had an audit log of that behind me. So when I came to meet the next person, I could be again, present for them. And I had, I didn't have this cognitive tax that was in my head all the time. So I could show up. And again, this is especially for product leaders being in a, in a calm state when you're dealing with complexity, uncertainty, high stakes decisions, that's the state you want to be in when you have to make tough choices, not hamster wheeled running from one thing to the next 50 things in your head. So again, like, but people notice that because after I had meetings with them, I would literally like take my transcription, synthesize it in an LLM and send out the tanks for the track. Jason, here's the key actions. We talked about the themes we're meeting here. This is what you got. This is what I got. And people were, were sort of shocked. They were like, how did you, how did you do that? Cause I felt so listened to in the meeting, you know? And, and then even before I would meet them like 24 hours before I'd send them the nudge going, right, here's the actions. Here's all I need to make this decision. Another thing like meeting agendas. A fair play to you. When you run your podcast, you, you set up an agenda. 90% of people don't do that for meetings. They don't do it for shows. They don't do it for anything. And again, it sets an expectation when you're meeting with someone and they're like, here's the decisions I want to make. Here's the supporting information to make those decisions. So when you meet, it's not rebuilding context to go. What did we talk about last week? I forgot. What's the, where has anyone got Jira open? What's the ticket number? It's literally like high velocity decision-making. And I like working like that. And I think a lot of people like that feeling of making decisions of time well spent. You know, so that's again, how this all started compounding to me. And, and now here we are 10 years later, and I have this amazing database of every conversation I've ever had with execs that I've been coaching with teams that I've been working with. So I can, I can actually give myself feedback on how I run those meetings and how I show up on, on, on patterns and how they evolve over time. Cause I'm just mining all these conversations that I've had. And that feeds everything I do from social media posts to blog posts to books to, you know, it's a living context. And, um, that for me, I suppose is, is the fun part of all of this and how it supports me because I still have to do the creative acts, but, but the information is there to support my instinct. I was going to say this idea of like having a, an eternal database of all your conversations almost starts to sound like it could be like a compromise or, uh, you know, materials that you could go back and, uh, bully people with afterwards, but I'm sure that you're far too ethical to do that kind of thing. But all right, we've talked, we kind of gone around the, the, the edge fair bit now about like what this book's about, but you know, you've got to get your best salesman pitch voice on right now. And just maybe talk a little bit about the core premise value proposition of the book, uh, and ultimately who should be buying that book, who should be picking that book up and what are they going to learn from it? Yeah. So the, the core premise is that this book has nothing to do with tools. Um, and AI tools are the absolute worst place to start any sort of journey. Um, this book is all about better judgment, decision-making and how you operate as a leader. The tools are the periphery to that. So even in the examples we shared, everything I start with is around you understanding yourself about how you do your best work and how you make decisions, because for me, the, the most important thing and a capability that we can very easily lose is our ability to make decisions. If we lean too heavily on technology, the moment you start deferring agency and using these machines to tell you answers rather than to pressure test your thinking, you're already on a road to perdition, I would say. So for me, again, the, the, the last thing that is uniquely human is is our ability as product leaders, as any leader to look at the information and make a decision. Machines suck at that, but machines are great at capturing information, at synthesizing information, at actually allowing you to sort of play with the information, a huge volumes that you, you, as a human, you just can't comprehend. That you, you, as a human, you just can't comprehend, but you need to hold onto the judgment and the decision-making. And for me, that's really the core tenant of this book. So the joke of AI isn't replacing leaders, it's exposing them. Really what I'm saying is it's exposing your leadership systems, your decision-making systems. And if you don't have any, you're going to struggle. But if you can build that competency, you can really refine it and get better and really outperform most people in the market in ways you're probably going to surprise yourself. And for me, that's, that's the personal growth aspect for all of this. So when you say leader, I mean, obviously you could sit there and think of a CEO. You could sit there and think like a company founder, you've mentioned already product leaders as well. Are we talking basically about anyone that leads organizations or people that lead teams or all of the above, additional to the above, like how are you defining a leader in this context? Yeah. Some people, for example, say for example, that any product manager is a leader. I don't think that's always a hundred percent true in all organizations, but like, yeah, how, how is leader being defined in this context? Yeah. For me, I would think about it, anybody who's responsible for making any decisions of any consequence. And then obviously the magnitude of those decisions are higher order, right? As a CEO versus a, an IC on their first day. And they're, they're, you know, they're, they're building a, a better landing page for a new product, right? Like there's different magnitudes there. But at the end of the day, the crux of everyone's job and what we're generally paid for is to make decisions or to make recommendations about what a decision should be, even if you're an IC. So for me, that's really the place I begin from and then asking people to start recognizing how they do their best work, where are the places that they create value and then identifying potentially tools that can help them accelerate that process or improve it. And for me, that's, as you say, it's, it's anyone who's making decisions. So a leader can be at any level. Uh, but again, the book is packed primarily because I work with execs, primarily fortune 500 execs. It's packed with examples from, uh, Stephen Franchetti, who's the CIO of Slack, uh, Andrew Phillips, the CTO of Skyscanner. Uh, we have, you know, execs from HSBC, Progeny, the world's largest provider of fertility benefits. All of these are people I've been working and coaching with over the last number of years to help them improve how they run these, you know, multimillion dollar, billion dollar companies. And it's fascinating to see how these folks dive into this to improve because they're interested in personal growth, right. They're interested in making better decisions and running better businesses. And, um, yeah, lots of fun examples I can share of all, and even building our studio of all the crazy mistakes we made along the way that, uh, you know, it's always interesting to help people avoid them. Well, that's the thing, you know, you kind of come back with all the arrows sticking out your back and, you know, telling people where to dodge the arrows. Right. So it's always, uh, that kind of, uh, school of hard knocks type of thing going on as well. But leadership in itself is an interesting concept, right? Because if you look at some of the AI commentary out there these days, there's this whole thing around like, you know, leadership is dead. We don't need leadership anymore. Like everyone can just be a super individual contributor and et cetera. And people should be building their own stuff again. On the other hand, you can sit there and say, you know, to your point just now that, you know, there's a, you know, leadership is almost defined by the consequentiality of the decisions that, that people make and the kind of the impact that they can have. So how are you seeing, you know, whether it's using AI or not, how are you seeing the role or the importance of good leadership these days, because not everyone seems to believe in it anymore. I still do. I wonder where you were on the kind of the idea that like leadership is like a dying art somehow or should be dying versus actually it just needs to get really better. Yeah, I think, um, the best leaders I've worked with certainly over the last number of years, if anything, have more humanity to them than ever before. Um, you know, a good example again is Pete Avenesky, who's the CEO of Progeny. Now, Progeny, as I said, are the largest provider of fertility benefits in the US. They're a NASDAQ listed company. Prior to starting Progeny, Pete was the CFO of WebMD, which is like, um, you know, he was there for 14 years, built up that company. He's super meticulous. He's data driven, more like absolutely down into the minutiae of everything, you know, and, um, for years, the way he had managed all of his work was on a Word doc. He literally just had a Word document of like meeting with Jason, meeting with Barry, this is what we talked about. Like that's how he managed these massive companies. So, um, the thought of using these tools or changing the way he worked, you know, most people were scared because he's a CFO background that he just wanted to see, show me the measurable ROI. That person isn't contributing, let's, let's eradicate them. But he did some very unique things that I think really showed leadership for me. The first thing he did is he talked about this idea in the company that they're going to use these tools to elevate, not eliminate people, but they're going to use them as a way to sort of help them do the best work of their lives. The first person to start sharing in the open about what they were trying to do, what worked, what didn't work was him. He put his hand up to say, I'm going to start using these tools on a daily basis. And I'm going to share with you every week, what I tried, what I liked, what I found difficult. And this is imagine this is a person for their whole life. They've just had a word doc to manage their whole business. So as we started running experiments together, getting him having co-pilots in meetings, getting him use them to generate his notes, generate strategy documents, look at different scenarios, get hold of data that he would have ideas around potential sales opportunities and playing around in an LLM to run multiple scenario plans and variables. Like this guy was in heaven. And what he was doing was showing his team every week. I tried this. It didn't work. I tried this. Here's how I'm going to do it differently next week. So it wasn't just a statement of we all need to suddenly be amazing at this. And I just bought you licenses for the product. If you're not amazing, you're fired. It, you know, he, he really was talked about it and then he walked the walk about it. And for me, that's where then you have this explosion of experimentation in the companies because people say, right. If the, if the leaders are doing this, I should need to do this. I'm going to, I'm going to mimic their behavior. Right. And progeny had just an amazing exec team, like their, their chief HR officer, you're going to love this. So she, she was adamant. She wanted to build this sort of HR product where it would onboard new people into the company. And so when people came in, they would have a chat GBT ask interface that they could just have dialogues. Like what are the public holidays? How many days off do I get? You know, what, what options do I have for healthcare services? So what was really fascinating about building that is that instantly she started to learn the questions people had about HR. She had like an objective reference of these are the policy questions people are asking about. So what she could do is like self-serve the really low level, simple, when's the next public holiday question, but she could set boundaries around if there was questions that were any way unclear or had some sort of real personal impact that would go straight to her team. So the ticket queue on her response times went down from literally three days to less than 16 hours. They had a learning mechanism about the questions people kept asking. They use that to adapt their healthcare policies inside the company and change their whole benefits offering internally in the company. So she had built this whole product that was basically a living, breathing HR system, adapting to customer requests and needs. So to me, that's where you get people who, and then an intern built this, by the way, this wasn't like a big 10 million, you know, get me a software squad that I need, um, 25 people to build this thing. This is like an intern doing it over a summer. And, and one of the best things is we were doing one of the calls and this new lady had just joined the company. And she's like, yeah, the last three days I've just been talking to the HR boss and I never have felt better on boarded in my life of in a company. I know who to talk to, who makes decisions, what meetings I need to attend. And to me, like that was a powerful example of a leader, like from the CEO, right down with the exec teams, like demonstrating the leadership in this space and for me, that's, that's how these companies are going to be successful. You can't outsource it. It's not like digital transformation where you just put everything in the cloud and you tick box it and you're done, you know, you, you, you have to change the behavior and you've got to role model it. Well, I mean, that's an interesting point with regards to, for example, the, the, the intern doing it. And obviously people kind of throwing their weight behind it and experimenting and seeing what works and what doesn't work, because one of the things you talked about in your book was that you did like a survey with your mailing list of CEOs and leaders around all of your subscriber base. And I think it showed something like a 61% of senior leaders still consider themselves somewhat beginners when it comes to using AI in the first place. But then when I look on social media and LinkedIn and even God forbid X these days, it seems like everyone's at it. And everyone's doing all of this stuff already. So based on your experience, do you think that kind of AI adoption in the real world amongst real leaders is actually quite a lot earlier than the kind of the social media narrative would say, or like, Oh yeah, we kind of just in a bubble of some sorts because the two stories don't seem to join up. They don't. Right. And to me, it's a by-product of two things. One, these frontier lab companies have billions of dollars to spend on marketing. So they, they, they want you to feel fear. That's how they're selling. They're selling through fear. You're behind, you're going to lose your job. Everyone else is doing it. You're not doing it. And then also you combine that with influencers who are again, optimized to sort of create wow. You know, again, fear selling of look, all the amazing things I can do. Can you do this right? And then you have, so, so that is just, and they, they are the, the two bodies or entities that control most of your marketing, social media feeds, right? Like that they're paying to do it and they're incentivized to do it. But when you actually talk to the people on the ground, if you talk to a C, uh, so I keynoted Gartner CFO conference in Washington three months ago, and every single one of the CFOs in there was sitting there going, I have no idea. The return on investment for the spend I'm making. I have a line that shows my spend on licenses for Microsoft co-pilot going like this. And I have a usage line that is less than 1% relative to that spend what's going on, right? So, and, and so companies are still very scared to turn this technology on because you have to remember like a Microsoft license for some of these engineers is like a thousand dollars a month, you know, like, and if you're a, any, a medium sized company of a thousand people, like that's a million dollar line item you have a month that you haven't even thought about adding to your, your, your capacity. Right? So these are decisions that companies have to take their time on. And it's rightly so. So I, I, I do would say that the feed is, is not a reflection of the reality. And you're not behind, but you need to start where you are. You, you cannot, you cannot freeze at that's the worst thing to do. You have to start taking small steps, like what's a decision you could maybe experiment with. What's a workflow you could try and automate it sitting on the sidelines is not an option here. Because the people who are experimenting are again, learning at a higher velocity and they will just accelerate. So you, you have to start, um, but you're not as far behind as your social media feed wants to tell you you are. It's interesting though, because whilst I agree that people should start and start working out what's in it for them and what they can do, this narrative of like, well, you know, either you're behind or you're not behind and you should start, or you got to catch up or you'd be left too far behind in the future, et cetera, I kind of understand where that comes from. And obviously at least some of it comes from people trying to sell courses and tools and stuff. But in theory, and this is an ill, an ill formed kind of birthing thought that I'm just coming up with as I say it, but just this idea of like, are they behind because surely what's going to happen is that people and tool makers and AI aficionados and such. They're going to make a bunch of mistakes. I'm going to come up with something that works that you can then just use. Now I want to talk a little bit in a minute about some of the ways that you make this stuff yours versus just generic, but on a kind of purely tooling perspective, it kind of feels like being an early adopter in such a fast moving space could actually, yeah, it's just gonna be fun, but like whether actually kind of some people are going to be just fine whenever they come on, you know, whenever they come on board. Yeah, I, I think it's a really good point and I can even bring that to life for people and even in the last month. So we're, we're recording this at the beginning of August, right? Um, three or four weeks ago, if you were using a tool like chat TV T and you wanted to try and integrate it into various different components of your work, plug in your Gmail, plug in your calendar, plug in your work management tool, whatever you had to use a codex, which is one of their packages. And it was also really difficult to make that work, right? It was a pain. It was basically a pain. You sort of, you almost had to be at the level of like some engineering capability or willing to learn it. So again, roll, roll back three weeks ago and they make, um, GBT work available. Where suddenly you can have a dialogue, like a human dialogue with your machine and say, plug in my chat, um, plug in my Gmail, my, and then start looking through that, and this is what I was do every morning, look over my, the last 36 hours of my work and bring up all the actions potentially have to do from my email, my Slack, my calendar, my, right. And I get that every morning when I wake up. Like to do that, even six months ago would require some level of programming capability. Today, I just wake up and I say it to the machine and now it can do it. Right. So I can get this, as you say, like really like rich experience out of the box now that I couldn't get. So if my day one of playing with these tools was last week, I'm literally like, this is Pandora's box now, right? You're literally like going, Oh my God, this thing's amazing. Right. So, um, the principle of what you're saying is true. I think though, the moment has to be the start where you are, right? Like, again, there's a risk of, um, opportunity costs, if you want to call it that, of, of not taking action, because the only way you can learn this stuff is you cannot learn it in a book. You cannot learn it in a, in a course. Aidan McCullen, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, MPH, you just read a book about it. I don't worry. I'm, I'm happy to tell people that you only can do it by actually using it. Right. Because again, it's quite, it's such a personal thing. Again, this is why I go back to the human side of this. Like the way I use these tools is going to be fundamentally different about how you use them. Because we've different styles, probably of ways of working with different tasks that create value for us. So again, it's to me, it's just like, you now have this again, like if you, I call like almost AI, like a thinking partner to work with you, right? So for me, it's a joy because I come up with ideas and then I tell these machines to like, tell me everything that's wrong with it, tell me all the assumptions I'm making, tell me the blind spots, give me four different scenarios for this idea that if the price of oil goes from a hundred dollars a barrel to $200 a barrel, what would that mean? Or, you know, that's amazing in airline industry where you're like razor thin and you're like, you're, so I can do like quantitative modeling now on, on hunches. Where, when I then go to talk to partners or peers or people I'm working with, I don't come to them with these sort of one-on-one questions like, Hey, why does the price of oil matter in the airline industry? I can go to them and I'm like saying, okay, I've been looking at these, I had this hunch, here's all the information I looked at, here's the scenarios I ran. These are some of the assumptions I'm making and the three options that were there, I'm going with this option too, because I think it's the right one for these reasons, you're an expert in that field, but what, what am I missing here? Like, what a great conversation, you know? Like that's, that's, that's how I dream people would use my time if it was in the other side. Right. And so I think if you think of it like this, um, that it's not there to take away, to give you the answers that it's there to pressure test, to raise the bar, to allow you to do more of the hard work yourself, you can get so much out of this experience right now. Yeah. It's interesting because obviously some of the stuff that you talk about in a book is around what you might kind of call classic LLM use cases, right? You know, you've mentioned it earlier, bring something to the meeting and it can kind of transcribe your meeting. It can summarize your meeting, give your actions off your meeting. You can get a summary for next time off your meeting. Now, yeah, that's not necessarily the most controversial use case for this stuff. Like a lot of people are using it for that. I know obviously there are entire apps built around it and any meeting you go on is going to have 15 different note takers on it these days as well. Plus everyone's like private granolas that you can't see, but it's the kind of thing that you imagine quite a lot of people are doing, but you talk in a book, you just talked about it just then and something that I'm. talked about it just then and something that I'm, I wouldn't necessarily say I'm passionate about it, but it's definitely like a use case that I'm very keen to push with people is this exactly as you say, kind of almost as a thought partner. So the way I've kind of tried to experiment with stuff is almost as like a virtual stakeholders that I can kind of go and take my things to, or not necessarily my things, but like people that I'm working with, get them to take their things to it, because as you say, they're going to miss a bunch of potentially obvious things. And it's almost like there's this credibility that they can get because they can sit there and not have to ask the dumb questions in the room, but they can already have asked the dumb questions and got some basic, don't want to make an expert in that area, but at least they're not going to kind of make the person that they're speaking to kind of low key angry that they're having to answer these dumb questions in a meeting when you want to talk about some other stuff instead. And then it reminds me of past experiences where you've had people going into meetings, you know, maybe they're doing that big presentation and the meeting goes completely off the rails because, you know, on slide two, there's an assumption that wasn't right, or kind of a point that they made that didn't really answer the question that was obviously going to be asked by the person that was in the room. So yeah, then rather than spending a productive hour actually doing something and coming to a proper decision, you're just spending an hour arguing the toss over something that probably could have been answered in a couple of minutes. Do you think this is kind of the most high powered sort of use case of all of this stuff? Is there something that's better than that? Cause for me, that's, that really is part of the magic, especially for product managers, as they're trying to up themselves, product leaders, as they're trying to advocate for themselves at the top table, this, this to me sounds like the, the, the big unlock. Yeah. And like you say, it's a progression for many people to get there, right? Like the, the table stakes, as you described it, it's just understanding this, every conversation can be captured as data and you can use that data to show up better, to prepare better. Right. And that's, that's for me, that's like, you know, that's the entree, the main courses you're describing. Wait, wait, wait. Is this the American entree or the European entree? Cause I'm still, I'm still salty about that, to be honest. That's okay. Where it's, it's your show. So we'll say it's the, it's the first meal served, but then, you know, but then as you say, like where it gets, starts to get interesting, as you're describing is this idea of like pressure testing. Right. You're so one of the things we built, as I said, one-on-ones with Pete Evanese, the CEO of Progeny, right? Like super detail oriented guy, always in the numbers, ex CFO, like, and he's time poor, right? So his exec team, but if they're lucky, they 45 minutes a week to do their one-on-one to get a decision on a couple of things and update them. And the example that you described there is something that very, what could happen in those meetings. So what we did, and this wasn't to make fun of Pete, but what we did is we programmed an executive GBT that people could sort of prepare to go and meet him. That would exit like questions he would ask, like, but like disconfirming questions, checking assumptions. So people would show up better. It's as simple as that. And, and, and everyone has a better experience of those, you know, time poor high stakes moments, whether it's a presentation where it's a one-on-one with the CEO, whether it's. So the quality of that moment is higher. It's better for everybody and people feel more confident showing up and they get a better outcome at the end. And then again, like you say, the last piece for me, which is a dessert, which I think we can all agree is fine. The last bit, but before the cheese, maybe exactly. Yeah. But is this idea of presence is because when, when you're feel prepared, when you feel like you've done the work where you've, you, you can, you show up in a different way, you show up confident, ready to be listening to look for gaps in your thinking, and again, that's what a great place to be, you know, and that's where you make your best decisions. Plus at the end of the day, you can close your laptop and you can go home. You can sit down for dinner with your family and you're not thinking about five emails that you have to send. You're you're present in those moments too, as well. And for me, that's how this starts to give us a whole better work experience and life experience overall, is that if you have this, these support mechanisms around you to help you do your best work, to be the best person you can in these high stakes moments, you're just, it, it permeates your life. And for me, that's been the biggest gift of all of this stuff is that I'm happier as a person, I'm less stressed. I've got systems now that support me, but I don't have to remember every conversation that I've had, every detail, every action, when it needs to be done. I've all this support mechanism around me. I've got a high stakes podcast that I'm doing with you. I can pressure test my questions and like, you know, Aidan McCullen-Nessey, Ph.D.: don't worry. This is, this is the lowest stakes one that you can worry about. It's not, it's not a problem. But Danielle Pletka, Ph.D.: you know, you're smiling because you, you know this, right. And, and you're doing it and you're, you're reaping the benefits and you're coaching people how to do it, you know, and, and that for me makes work better for all of us. And, and so I, that's what makes me most excited about it. Aidan McCullen-Nessey, Ph.D.: No, absolutely. And, you know, again, I mean, I think we probably both have the same sorts of stories about how it's helped us to show up as, you know, we both work with multiple organizations or people at the same time, right? Like we'll, we're kind of bouncing between contexts a reasonable amount. We are also trying to, as we discussed earlier, trying to find new work whilst doing the best existing work as well. And there's a lot to do. So it obviously is a massive unlock and I already can't really imagine not having some of the stuff now that I, that I have now, but there is also a dark side potentially to all this stuff as well. And it's not having to spend time with the kids, obviously, but there's this, this dark side that could be considered, which is like, it's kind of a two parter really, that first of all, that people use it, not necessarily as a thought partner to pressure test and kind of, you know, armor plate their ideas, but it's just a shortcut. Like it kind of just comes up with something that looks kind of good. Probably no one can really tell, and it'll probably be good enough. And you can just bypass judgment and just get it straight out the door because you just, you know, you either like think that that's good enough, or you didn't really care enough about the decision in the first place. And then the second part, which frankly might be part of the first part is just this general kind of concept of AI slot, which we kind of touched on a bit earlier, the idea that people can just do the bare minimum, you know, marketing copy, or, you know, basic research that may or may not be true. They don't even have the tools to work out whether or not it is true because they're just moving on too quickly. And there is a risk, right? Because people are being kind of encouraged to 10x, 100x themselves, do everything faster. These tools are amazing. AGI is here already, et cetera. So how do you recommend that leaders keep themselves, I guess, honest and make sure that they're not just sloppifying their company decision-making and that they're actually still actually amplifying what they should be doing? Yeah, no, it's a, it's a really important question. And it's, it's probably, I would say with executives, the number one question that I'm getting at the moment. And I'll explain why. I remember when we started Nobody Studios in 2021, right? We had like a series of documents that entrepreneurs had to submit, you know, customer profile, go-to-market, business model, kind of, you know, share a set of documents to sort of, you know, describe your idea and, you know, people did it well and people did it not so well, but I can literally tell you today in 2023, we went from people sending us like, you know, a couple of post-it notes on the back of a deck to sending us full blown out data rooms of an idea that they had literally, you know, and again, when you saw this for the first time, you were like, Oh my God, this, this is a dream. We found this dream entrepreneur that really knows how to get everything they need at the right time. And you'd jump on a call with them and you'd ask them like two or three questions about their idea and it would have no rigor to it straight away. You could tell that they had literally, I decided we're doing Uber for cats. And that was the idea and I've all this documentation, but none of the thinking, none of the work had been done to understand how it all fits together. Right. That became very obvious very quickly. Um, and we were very specific with people. If, if people submitted that and showed up like that, they were sort of stricken from potentially working with us in the future. Now, last week I was sitting on a call with a CEO of a well-known company in the UK. And he's like, I'm overwhelmed. I have more output coming at me now than ever before. People send me 12, 14, 18 page documents to review and ask for feedback on them. I get 10 or 20 of those a day. And the challenge is because it's so easy to produce now that people are moving the processing work onto other people. So that is like the biggest tax in poorly run or poorly supported companies right now is that they are moving the feedback. They're moving the work, the processing work to somebody else. And most of it keeps filtering up to the executive team who are already the people with the least capacity to do processing work, you know? So for me, um, one of the things I've actually encouraged a lot of execs and CEOs to do is to have a slop policy. I don't, I don't, I'm not a big, I'm not into mandates, but the one thing I am into is them saying something to the effect of in our company, a respectful way to work with people is for you to do the work and call on their capacity to improve your work in meaningful ways. That means not generating massive documents and moving the process, like the production tax from you onto the processing tax to them. And if people do that to people in this company, we will see that almost like as a sign of disrespect of your coworker, of their time, of their capacity and energy. So there's an expectation that you don't show up with more work for someone else. You show up in some of the ways we described where here's the work I've done. I've looked at 25 scenarios. I've looked at different options. Here's the pros. Here's the cons. I want to choose B. Here's why. What do you think, Jason? That's the way you need to show up, you know, and that is a cultural behavior. That you, you need, you need to have almost a policy on certainly a position. And for me, that's one of the things I'm certainly encouraging because we did it in the studio because we were just getting overwhelmed with all these business ideas that had no merit or rigor in them. And execs are feeling that right now in companies where they're getting these strategy documents that are 20 pages long and say nothing, you know, and that is, um, that is a disrespect in my, in my world to your peers to show up like that or to expect that of them. So that's sort of how I'm going at it. No, absolutely. And that makes a lot of sense, you know, kind of actually trying to apply some standards to this stuff and calling people out when, when, when they don't hit those standards, but another interesting point around, uh, you know, we kind of touched on a little bit earlier, this idea of like, well, how do you make this stuff yours as well? And how do you make it not generic? Cause you know, if we talk about AI slop, a lot of AI slop comes from the fact that, you know, what you're, what's pumping out is effectively just the average of, of what went in there and what got trained into the model in the first place, right? So you sit there and say, Hey, write me a strategy document about going into a new market, but you don't give it any context at all, and it just kind of just cranks something up because it's always going to answer whatever happens. It's always going to answer. And the answer is going to look kind of okay, but actually if it's just generic, then that's probably not going to help you at all. And you talk in the book and it's something I'm very keen and again, somewhat passionate about this idea that these things only work if you give them enough context. You talked about your own data points that you, you know, conversations that you're putting in there, but there's also a bunch of other context out there as well around your company, your strategy, your market, your customers, your offering. How much do you feel it's important to maintain and keep up to date and manage the context that both you as an individual, maybe as a leader individually putting in, but potentially across your organization as well. So that you have that kind of grounding in some kind of truth versus just getting some kind of generic slop kind of average of these things. Yeah. Again, for me, the companies that are powering ahead are the companies that maintain healthy, fresh context. You know, one of the companies that I'm on the board of is a company called dot work. Actually, John Cutler, who some of the listeners might listen to is head of product there. I'm sure he sends you lots of very long emails. Yeah, he does. Yeah. He writes a lot. He writes a good email, John. Um, but you know, one of the things that's amazing about that, a whole business idea, right? These guys, you know, they've been doing this for many years. They built agile craft, which was bought by Atlassian to become the portfolio management tool. And, you know, one of the things they realized is that information is everywhere in a company, but nobody ever has, and maybe they never will have this single source of truth. But there's context floating around the company in all of these tools. And we've never really been able to bring it to a place where maybe you're making a decision and somebody else in the company has made a similar decision before, or is in the process of making one, or there's a company directive from the executive team to increase retention by 10%, but most people can never ladder their work up to that, or, so these, these ideas now of tools that are sort of ambiently listening in the background about the work and looking at the work that's being done, the, the tasks people are focusing on, the documents they're, they're creating. These machines are amazing at creating knowledge graphs of your company to understand how it's actually working, how information is moving, and can you get it in the hands of the right person at the right time? Like that's the problem to solve in these moments. So to me, it's almost like our, you know, opening example of me just capturing transcripts and uploading them into my database because that's my context, right? Um, but if you scale that thinking out to a whole corporation where all the information moving in it, like what moves fast, what moves slow, what changes frequently, what doesn't that's invisible to most people, but to these machines, they can build knowledge graphs. They can, they can join relationships that maybe, you know, I can't see because I'm a individual contributor working in Brazil, but you're working on a similar project in London and, you know, we didn't even know each other existed. Right. And like that to me is sort of the opportunity of this stuff where we've never really had that ability before it, that would have been a three-year integration project with Salesforce. And, you know, you'd have a couple of SAP consultants showing up and it would just be a nightmare, you know? And so again, I, I tend to get, cause I'm an optimist on this. You probably recognize, uh, you know, like I, I come at it from how it can help us improve and get better. And you're right. And I do appreciate your, your calling out that they're just like the old Superman or is it Spider-Man? Is it with great power comes great responsibility. Yeah, exactly. You know, like they're, they're. So you'd have known that if you'd have been keeping a track of all the films you'd watched. I don't get to watch these films anymore. Uh, but you know, like that's, that's how I, I tend to think about these things. And, um, and for me, that's exciting, right? Because I, I want us to be working on things that matter, right? Interesting, like hard problems with interesting people. That that's how I live my life. And that's where I want to be focusing. Yeah. And it does kind of feel that there's that kind of reinforcing loop as well, because many of the times, if I go and work with a company, I maybe, you know, you talked about it yourself, like maybe there's no shared context or people don't know where's what, and frankly is part of the reason people sometimes bring me in is to try and help them work that out and start to understand like where the opportunities are, but also what the status quo is. And it's funny because if I look at, for example, some of the, you know, there's like a bunch of different personal operating system, company operating system, kind of LLM courses and stuff out there that people can take. And I'm not going to name any because I've never taken any of them, but I've looked at some of them just to see kind of, you know, what they like. And so many of them have almost like a bunch of like, whatever, Mark down files with like strategic context and vision and market context and stakeholder maps and everything else. And it's like, yeah, this all looks fantastic, but I don't know a single company that I've ever worked with that could fill all of those in like just on day one, because again, as you say, it's all over the place as companies get more complicated and there's also not just the explicit context, but there's also implied context as well, right? You sit there and say, well, actually, you know, Dave hates Susan and therefore they don't work, you know, all that sort of stuff that goes on within the organization as well, because organizations are complicated organisms. But trying to kind of at least start with what you have, get the AI to tell you what you don't have and what you may be going to need to find out. And then iterating over time kind of feels like that can just sort of reinforce itself over time, right? But that, that is the method, you know, like there is no, there is no method to suddenly magically just go off and have all this stuff, like you're describing, you know, like, again, that, that's the world of these bloody influencers on, you know, who are just like, yeah, welcome. Oh, you're an influencer too Barry, come on. Copy my skills.md file and you're going to, you're going to have $10,000 a month in from Instagram, right? So, um, but one, one other person I really want to recommend to your, even to yourself as well, to have her on the show is Melanie Steinbach. And she was the chief HR officer for McDonald's Cameo Masterclass. And, you know, one of the things, um, she talks a lot about is this idea of a work charter, which again, is this very human artifact to pair with a company. an artifact to pair with a company because it, it, it describes the invisible, just like you did a moment ago, it's like, I can look at the artifact of the organizational chart and that's nice, but like, how do I know that when I meet Barry, that if he's drinking a coffee and you know, his right leg is twitching, that means he's probably not in a good sort of head space, so don't tell him something that's going to frustrate him, right. Or I'm meeting Anne and she's sort of in a certain mode, like how she likes information, she's really visual. And I show up with a slide with, you know, six point font and I stick it up on the. You know, like those things are so important for people to be successful that aren't in bits and bytes, you know? And so I, again, I always try to say it's human and machine. It's, it's, you have to not give up on the instincts, the gut, but you've got to pair it with the machine intelligence too, as well, and insights because that's the best of both worlds. No, absolutely. Well, if someone is now listening to this and thinking, well, that sounds awesome, never done any of this stuff before, maybe they're part of that 60% that we talked about earlier and they want to just get started, obviously one of the things they could do is buy your book, but before they even do that, what would you recommend being kind of, there you go, there's the book on screen. I'll make sure to get that graphic up on, yeah, didn't send me one, by the way. I had to go bloody go and buy it, but there you go. Which I'm so grateful for, that got me up, it almost paid for one sandwich. Yeah, you can have your, whatever, three, three pound cut or whatever, you know, cost of living inflation these days and everything, but, but if they did want to start with some kind of workflow or some kind of task or step or anything else, I mean, obviously I know that you in the book talk about like not starting with tools, you know, you start talking about traits and tasks and then tools, so kind of examining yourself and then the things that you need to do and then the tools that you need to do them, which is fine, but like, if we were just going to be super specific kind of like one little nugget that people could take away and just experiment with, and then maybe buy your book afterwards, what would that nugget be? Yeah, no, it is though the idea of one, I would start with like one decision that you have coming up in a right in front of you at the moment, and then think about how you're going to make that decision. And even before you do anything like write it down, get a bit of paper and say, because the thing is, most people have never really thought about how they make decisions. They have this internal algorithm that they just sort of execute against. And what's really fun about some of these tools now is that you can like write out, how do I make a decision, right? What information do I look for? What counter arguments matter to me? What data points could be important here? Like you can write all of that out and then you can codify that really in, in, in a system now, so you could sort of take your, your human algorithm, if you write it out and then stick it into one of these tools and then sort of fill in the blank on the decision that you're going to make, or even better before you fill in the blanks, you could ask this LLM, how could I make my decision making process better? What am I missing? Is there something you would recommend that would make this more robust? And you'll start getting into that experience, if you will, of using this like a thinking partner, it giving you feedback and going, oh yeah, yeah, you should look for four assumptions that you've missed here, or you have a blind spot in this area or, so you'll instantly experience how this tool can make you better. And then you can fill in the blanks with that next iteration. And then if you just get into that habit, like you won't recognize yourself in a week's time about how you go about doing your work. And that's what I try to get people started with. And then I can buy the book. Yeah. Yeah. If they, if they have time, you know, it's also the audio book just came out yesterday. So after they've listened to you and me, uh, you know, they're probably thinking I need to listen to more of these two guys. Jason's not on the audio book, but you know, you can listen to me for three hours. I'll do the Spanish version or something. So that'd be fine. But if people do want to come and check out the book, catch up with you, I know you book calls, for example, as well, let you do your Tuesday calls and stuff. Where can people come and find you and, uh, you know, find out more, maybe have a chat. Yeah. And firstly, like, thank you for having me on the show and asking these questions. Like it makes such a difference when people do the work and they also, you know, you're also sharing your expertise and you're humble enough to ask me mine. So thank you for that. Expertise in air quotes for me. Exactly. But, um, yeah, look, my website, barryoreilly.com, the book, artificialorganization.com. Um, I, I, I tend to live more on LinkedIn than any other social platforms. I know, you know, you can follow me there. Um, yeah, but again, if you do read the book, the only thing I ask is do please like write a review or let me know and get in touch in what you think about it. Because, um, that's half the fun of doing these things. So, yeah, thank you very much again for having me. Well, you know, it's always a pleasure and hopefully the book will still, you know, go on to, to future success before it gets kind of consumed by LLMs. And then people just ask the LLM about the book instead, but you know, you've probably got a couple of months till the next training run, right? But, uh, yeah, I'll make sure I put those links into the show notes. Uh, hopefully you'll have a gaggle of people heading in your direction to find out more, but Barry, it's been great to chat, obviously about leadership, AI, leadership and AI, um, obviously the ways that we can all try and be present and, and do things, uh, ethically and not sloppify the leadership in our organizations, uh, obviously we're sure the best and continued success of the book, but as for now, thanks for taking the time. Thanks man for a great show. Appreciate it.