The Story of Wicked Problems

Wade Erickson (00:12):

Welcome all to another episode of Tech Leaders Unplugged. Today we're getting unplugged with Marcus Kirsch of the Wicked Company, founder of The Wicked Company. We're going to be talking about the story of Wicked problems and, and the basis of that is things are getting, the world has always been complex, and I think with our interconnectedness, we're finding things are even getting more and more complex that we have to solve. And I think that's kind of the nature of what we're going to talk about today. Marcus is a specialist in this area. And yeah, go ahead Marcus. Thanks for, for sharing your knowledge with us today and introduce yourself a little bit, some of your background and the Wicked Company, and then we'll jump into the topic.

Marcus Kirsch (00:58):

Hey, Wade. Thanks. Thanks for having me. Yeah let me start by giving you my initial context and 5 cents, I guess, and let's see how long you, let me ramble on until you stop me there and ask more questions. Yeah. So Marcus Kirsch, The Wicked Company. I've been in that space of innovation, change, transformation, and wicked problems for 24, 25 years now. It's nearly half my life, chose my age. I, I'm originally trained in sort of design, art and design, design thinking and innovation. So if you think, you know, Stanford ideal, all of that stuff is sort of my, my roots, my origins. And even though I wasn't aware that seemingly wicked problems go hand in hand, nearly with the design thinking approach, I was working for years with that. And I live in London. I ended up working for lots of different companies and lots of different industries from automotive to healthcare and so on and so on, initially on innovation where you look at these kind of human centered research and approach to solving very complex problems, not just on a technology level, but on a human level. And so eventually the wicked problem idea came into my life realizing it's not just technology linear approach to things, it's a very iterative need to look at a problem context. Because one of the main characteristics that defines what it's called a wicked problem compared to a tame problem, it's that, that a wicked problem keeps evolving. Yeah. Because even if you put a solution against the problem, it will adapt to it. And the reason for that mainly is that wicked problems have a big human component. And as an example, you could have a, a bridge is a very engineering team, straightforward, linear problem, right? You build a bridge, you can build a bridge in Germany, you could build a bridge. In Japan, it would pretty much work the same way. But if you say let's do and do something about the urban space and crime, or let's do something about, you know, social media and community behavior, you suddenly have people reacting to it and looking at solution. And you put something down and people start behaving differently around it. They learn, they evolve around it, they try to hack the systems, what people tend to do and they will have opinions on it, and then they will grow with it. And then it will change. The dynamics will just change. So you have to keep to keep developing a more iterative approach to it. And over the years, the thing that I observed was that in a lot of organizations, we don't, we, we are never quite that iteratively in terms of how we have teams looking at, at the thing from various different angles, how we build baselines, how we really gather enough information in the problem context because companies want to make money. And you can't have a company that doesn't make money, that's obvious. However, because of it, we want to do things rather than just think about things and observe things. And that worked really well all the way through the industrial revolution in terms of mass production, great factories, one amazingly on efficiency. Amazing, right? It's a controlled environment. You do this, but that doesn't work with services and the real world services being often in contact with people, feedback, da, da da. 'cause That's a wicked problem. And we're still structuring organizations as if we would live in industrial era problem space with tame and linear problems. But we are not, we are living in a very systemic, wicked world. Or VUCA is another abbreviation coming a bit more from like the military area that just recognizes that, hang on a second, the world's more complex. And I think one of the myths that exists is that companies still think that this is too complex for us to approach. This is complex for us to spend money on. It's too expensive to tackle it, so we're going to just do a little simple thing and that's why we're going to get away with, and that seemingly stops working or maybe stopped working 15, 20 years ago. And I think it's a major contributor to why a lot of change, transformation is failing, why a lot of amazing technology that's out there is failing to get adopted into companies. And it's failing to create value. And I started looking at that, started observing it, and I started to more and more adopt that into my work. And therefore started to really call out with organizations say, look, you are too tame. You're too linear. You have to shift the way you work, shift the way you look at things. It's all do, but now it's all actually, you can have a sustainable approach and a valid approach and a, a business value approach to starting to tackle wicked problems. And I think we're still very far away from that, but I made it my mission to a little bit contribute to, towards the fact that people know more about wicked problems, know more about how to run teams, how to run processes, and are able to somehow tackle these big scary things. And I think it's really prevalent these days 'cause we're, covid was one of the big, big things that happened globally. And epidemics are er problems. And I think we have to get more and more used to these kind of things hitting our organizations, our culture, our society. So I think er problems are going to be a bigger, bigger deal. And I hope I can help everyone to understand a bit more of what these things are and how to set themselves up to respond to it.

Wade Erickson (06:48):

Great. So what, what I think about when you said 20 years you know, it that's, you know, we're looking at about 20 to 30 years that the internet really has started to move in. And that probably has been the one thing that has brought connectedness together in our society, in no other way has been in the history of the world, right? So you know, and, and we're talking about, you know, breaking down Taylorism, you talk about the industrial age. Taylorism was the, the job of Taylorism was to break down complex tasks. And it came from the craftsmanship industry where one person might build the whole item. And so Taylor and many of the other, you know, Henry Fords and all that said, well, we need to break this into smaller pieces, but why, when you're doing that, it's like taking a puzzle and chopping it into pieces, but you are losing other parts of that. And when you try to put it back together again, there's missing pieces. And I think, you know, electricity was a interconnectedness, right? And the phone, the telephone was really the early days of connecting societies together and understanding the differences we have in the world. And then the internet has just exponentially changed that, whether it's applications or communication. And so like you said, the wicked problems now are really the interconnectedness. You take a human body, you chop it in pieces. If you don't put the nerve endings together and the nervous system together, it is not going to function. And that's the problem, is when we're chopping these things up, we're losing that nervous system. And I think the internet really is exposed that, like you said. So tell me about some of the work you do with corporations as you see them solving tame problems, as you say. How do you get them to think about the, the realities of these complex scenarios? And 'cause we're, you know, our, our whole learning system science and everything is about breaking things up into smaller pieces so you can understand them in a simply manner. And then when you try to stitch 'em together, you think they're going to come back together. And that's often the problem. Tell me a little bit about how you get these companies to think about these complexities that may they maybe never have, even as a, an individual, how do you get them to talking about that?

Marcus Kirsch (09:09):

Yeah, so obviously a big part of that is communication, right? And I remember one of the CEOs of respect, Rachel, she, she said at some point, you know, 50% of change transformation is communication. I think she's absolutely spot on on that one. So communication's one of the things, because essentially if you want to introduce a new kind of mindset into bigger groups of people, you basically have to start a movement. So a lot of the tactics I used, or when I get there, it's sort of, I'm, I'm, I'm boring from, you know, how would I create a movement? Cause The movement will shift their minds and it will help people communicate to each other, and it will start a story and hopefully plant a story in as many people as possible. And it can grow so that you don't always have to fuel it. However, in terms of practicalities it's usually a mix of being able to look both at sort of the, let's say the portfolio level. And you look at product or service portfolio level of a company and you look at how it's structured and obviously you will likely, easily see that there's a ton of silos there in terms of practices and how the services products are structured. And you'll likely see that, hang on a minute, maybe these things are structured in a way that they can't help each other. There, there's no synergy there. And you want to have that, you want to have better communication between those different teams to help each other solve problems quicker and also be able to actually see a bit bigger, a bit more of the whole system. To give a, give a very concrete example. At the moment I'm working on a contract with the Naturalist Museum here in London. And the main thing I'm actually doing there, instead of building teams and running processes, is actually to create artifacts that they don't have that connect the, all the systems and the technology with the actual services that are running end to end and in contact with the visitors, the scientists. 'cause The Naturalist Museum is also a science and a research facility here in London, and they don't have that mapped because the silos works so independently that they have never had the time to put this together. So I'm trying to build them a bigger map of understand of, of helping the individual services understand this is me as a team, I'm working on this thing, what's the rest of the museum doing? And is there anything similar to me that I can help them with or they can, or I can help them with or they can help me with. Right? And this is sort of getting slightly into a systems thinking, or at least an ability to see the bigger impact, the bigger system, the bigger ideas. And in this case, it just takes I'm using the tactic of creating artifacts, artifacts that represent multiple people, multiple areas, technology and the end user, and seeing where all the values sit, seeing where all the bits and pieces are sitting and what they do to each other and the dependencies. So, and in that sense, these kind of visual artifacts can actually help the conversation. Again, it's building a lot of the thinking of if I can have the better conversation and communication and showing other people what other bits and pieces are doing of the system of, you know, the body and all its organs, then I can actually build an organization that is more self-aware, is more aware of all the other areas. And that generally starts to enhance the idea that people will think more in terms of, I'm not just doing one part in a silo, I'm actually affecting other bits and pieces. And together we can actually achieve more to together, we actually have a chance to tackle this bigger complex wicked problem. So in this case, it's artifacts in other areas and other projects, it has been just the ability to connect with reality more. And what I mean with that is to often introduce companies to the idea that, you know, research and understanding what's going on with the customer or what's going on at the factory floor. So both outside of the company and the partnerships and customers you might have, and internally with the employees and what they do and the processes they do if you connect with that better and more often, you'll get a much better and wider and more holistic view on what's actually going on. You enable teams, you get more data to run with. And the big classic myth usually that exists is that, that it's too time consuming. It's too granular, it takes too long, it's going to hold us up. I mean, every transformation project I've been in the last 10 years, someone at some point would say, ah, we can talk to these people because it's going to hold us up. It's going to hold back decision making, and we're going to do, we want to do stuff, we're going to build stuff, deploy stuff, you know, look at the requirements and it'll be fine. Yet, most of the time when they didn't do that fell over. So it's helping organizations even bigger and complex ones to understand that we have the tools now we have the means to actually gather that information, bring it together, and understand just about enough to even tackle more complex problems like wicked problems. So there's, there's a really a myth that's been stuck with a lot of organizations where people just go, I can't do that. It's too complicated. Like, no, it's not. There's ways to go about it that you can do that in a sustainable way that's not going to hold you up. And actually that really, really derisks every investment you'll be taking. And I have tons of examples where we showed to organizations where the second you start doing that, you do that in the beginning, quite small, quick, cheap and easy. It exponentially pays for itself.

Wade Erickson (14:57):

You know I think a lot of people see AI as finding those connected parts that maybe get lost in the complexity of it all. And as somebody that's been seeing fantastic technologies struggle to be adopted by the corporations that absolutely need these technologies, tell me a little bit about your thinking about how AI may or may not help to understand those complexities where we can. I mean, the whole point of generative AI is you throw some prompts at it and it builds stuff. And you originally, you probably never would've came up on your own, but you can read it and say, I can, I get that, where the AI generated that, right? And people are hoping that that's going to help, whether it's cancer medications or whatever. Yeah. All these things. Quantum computing, whatever. Tell me a little bit about your thinking on how AI could help and where it's probably not going to be the savior we're hoping.

Marcus Kirsch (16:03):

Yeah, so obviously it's a mixed bag, right? And I've been working with some of those tools now for at least a year. And I think it took me about three months to see where the limitations are. So in broad strokes, if I think about post, you know, post.com or a couple of years later, you had sort of big data being a thing, then you had streaming, then you had, what else, you know pirate base bit torrent, which to bit torrent in itself is an amazingly decentralized and amazing technology that got demonized because of Pirate Bay. And then no one ever, it could have solved Netflix's problem amazingly, but never touched it because it felt like, oh, it's what criminals are using. So no one touched it. And then you go further into like blockchain and all that stuff. And or even before blockchain or after big data, somewhere in the middle that there's APIs. I mean, I got so excited about APIs and 'cause you know, I have a tech background as well. I still run my server, I run my APIs and a couple of things. And I have the privilege to be able to, you know, pull my stuff, you know, build my own tools at times. S I still, the, the, the power of these things is, is incredibly amazing. You know, there are at times short of magic where you press one button and 20 things happen. And it enabled me as an individual to, you know, run my podcast, do other bits and pieces, run some prototypes, do all sorts of stuff, and also be able to talk to technologies and say, look, you can do this. Like why, why we're not doing this here. So I always been excited about technology and I'm also very excited about ai, but because I've been knowledgeable about the technology thing, I'm also wary about, it's like it's got its limitations. AI does a lot of things run down the mill in the middle a bit. Like, you know, if I'm being really harsh, I would say it's a bit like Microsoft 365. It does a lot of good stuff. It's sort of not that great either. And if you use it, you're probably going to be doing run down the mill stuff, and it will be more effective. It's better. Like I was just reading today, someone saying, you know, actually the teams chat is not better than Slack because not that many people use Slack teams is more integrated as whatever you might think about the teams app. And it's probably a horrible piece of code, so to say, but it works, it's there, everyone can use it. And it's, it's, it's been more adopted than Slack. So it's a good point to say like, yeah, it, it does, it still does that. So it does good things. And I think that's true for absolutely everything. So the question really is then that, and that's the thing I'm trying to say more and more is basically that I think organizations have failed these technologies a lot because they failed reality in a way where, and by reality, I mean they failed the reality that no technology ever sits without context. And the context is human. So even ai, and I know AI is heralded at the moment even more and more, it's like, it's going to automate everything. It's going to do X, Y, Z. However, if you just think this through for a moment, if you apply, let's say critical thinking, you know, you could say, well, but who's going to update the ai? Who's going to add more features to it or who's going to swift it and shift it and a little bit check it so that it sits where it should be sitting and does what it should be doing. And if it's not interconnected, you know, it'll not upgrade itself. It will not interconnect itself. Like in the Cipher movies, I think that's pretty clear. So you need a ton of human beings who understand enough where it should sit, why it should do what it does, why it shouldn't do what it shouldn't do, and all of that. And before you know it, within five minutes of thinking, you go, hang on a second. That means I need a ton of people to actually understand reality better in order to do AI better. And that's the context, right? That's the wicked problem context. 'cause It's a human context. And human context creates wicked problems. So AI is probably the closest tech we ever had that starts to be already out of the box be wicked problem. And we already see that we have sort of data blurring off and the results not being that great just because more people are using it. It's this weird black box. And we're already seeing these kind of things evolving out of it where you read the articles and the scientists go, we don't really know where this stuff does what it does. And it's like, great. That's the same that I hear all the time when, when people try to deploy some tech in a company and then they go, oh, we don't know why the teams over there are not adopting our tech software is great, why they're not doing it. So they're now talking about AI in the same way. It's like, we don't know why AI is depleting there. We don't know why AI is suddenly bringing this stuff up and does different things. And so for me, that's all the same problem. That's nothing new. It's now tech starting doing that. And that again then means for me that we need more people rather than ever to look at these things, understand these things, and connect these things with reality. Understand the context and the story and the scenario better. You know I remember having a chat a couple of months ago with someone going like, oh yeah, should we get more like prompt engineers? It's like, I have no idea what the idea of prompt engineers came from. I would put some, you know, movie script writers on this, or poets. I would put poets on this. 'cause They know more about language and words and how to tweak and how to shape it and reality than some engineers. Engineers. And I count myself roughly as someone not formally trained as a computer scientist, but I can code various languages. So I'm some of them and I love what they do and I love what I can do with it. But they function on an abstraction level that is so far removed from reality where you go, your language isn't even appropriate to describe and fill in the gaps and there are gaps. Cause You're sitting in a vertical, and we can go back to Henry Forty's killing in that you're sitting in a vertical and abstraction level that is a bit too far removed from reality. Find people that are closer to reality and bring that to them rather than the other way around. So in terms of technology, ramly, long story short, as I might've warned you earlier, it's basically that bring these things together. The more you bring a technology, the more you understand the context within a technology is supposed to work, I think the better of a deal you're doing with it, and the more likely you're not going to get it wrong, right? If you rely too much on it like anything else you know, if, if all you have is a hammer, everything looks like a nail. You know, and I remember working in advertising where we had it was around the time when social media became a really, really big thing saying everything our social media specialist was recommending was to do a social media campaign and write some tweets. That was it. That's all we ever got out of that. It's like, yeah, that's great, but within which context? What is it connecting to? It was a very restricted silo. And I think making the silo mistake of saying AI is going to do this or that, no, AI will not ever create the value it can unless you connect it to the right things. And knowing how to safely connect it to the right things is knowing reality. Is knowing, understanding it a little bit better. You will never fully understand it impossible. But invest more in the beginning into getting closer to reality. And trust me, and I can prove this to you, it will pay out way better than the classic approach we have at the moment.

Wade Erickson (23:52):

Yeah. So I think a lot of folks want AI to be the puzzle, but the people that like you're talking here realize it's only a piece of the puzzle. The puzzle is much more complicated than the AI is going to be a piece of it. And it's going to be different parts of AI that are going to be used smart. 'cause Right now everybody's using what's obvious to them, which has helped them, generative AI. And you know, there's got to be at least 20 different ways to do machine learning and AI that, you know, as far as the use case and stuff. So until we really understand all those different things that have been going on for 20, 30 years you know, both machine learning and AI, we won't even appreciate what the base technology has to offer. And I think that that's just a level of complex thinking that it's a lot to ask of people in our society, the way we've been educated and stuff. So it is going to be unique individuals that are kind of the gurus, the AI gurus, and maybe even centralize some of that thinking, you know, playing around with, you know, centers of excellence for AI within companies and stuff so that you can, can consolidate those rare, rare minds to help solve the problems and see the connectivity and be the oracles maybe of the corporation. Because I mean, I would love to be able to think that, you know, a large portion of society can understand these complexities we're talking about. But I, I just, I just haven't seen that. You know.

Marcus Kirsch (25:19):

I think, I think the, the and, and maybe I'm a bit biased because, you know, I come from a more creative and art background. And by even saying that, if we look at the history of where innovation came from, it often has come from outside of the industry. It's, it's come out from outside of the industry standards. It's come from outside of, you know, conceptions where like, oh, we think that's what it is, is that's what we do. And someone from the outside who actually had no specialist knowledge would come and it's like, I have a different idea. I think I can do it. You know, the idea that we have these contenders or had it, especially during the digital era now, you know, like digital, mobile banking, all that stuff. Bunch of young people revolutionizing this and getting away with it. Not necessarily say they have the same reach 'cause they don't, they don't have the same marketing budget, but they are giving everyone the run for their money. And it's proven again and again that these things often come from outside of the specialist area. So therefore, I would rather say that there's a good place for specialists, there's a good place for efficiency, you know, six Sigma, all this stuff, removing variants. But I think the future is in between those verticals, in between the spaces the people who can actually create more variants. And that, you know, gets you to like Ashby's Law First Law Cybernetics, which says, you know, variants will defeat other variants if you, if you, if you, if you don't create variants and you are more creative with it, the system you're dealing with will run over you like that because it, it, it's an exponential, it's a hydra fight, right? Chop one, head off, two, come back. If you can deal with that. If you keep being not a hydra, you know, be a hydra to fight the hydra. So, you know, experiment. The efficiency approach is, and I think there's numbers in this where, you know, the whole digital transformation thing's like, oh, efficiency 3%, 4% more, great. If you do innovation, you experiment, you find 10, 20 or more percent. And, and I think it goes back to the innovative dilemma book. You know, I think it's been proven back then where it's like there is no future in just being more efficient, polishing your existing box a bit more, you know, finding materials that are slightly more cheaper to produce the same product and, and, and, and shift the margins a bit. That is never the real future of your company. If you rely on that, you are on the downtrodden path. You just, you go down, you are on the, on the down slope. You need to innovate. And it's a bit tricky really, when you look at the economy and you look at industries that through covid and other mechanics, I think it's probably harder than ever for companies to say like, oh yeah, we're just going to build another innovation department and it's riskier, but we still believe in the idea that that will get the next 20, 30% of our growth rather than the four or five decrease in spend of operational costs, and therefore that will make us survive. I haven't heard that talk for a longer time now, and maybe it's a bit of sign of our times that it, it gets really tricky to say, you know what? We're going to be brave. We're going to go out, we're going to invest in those kind of things. And that's tricky because that means that no one's in, everyone's taking the safe route and being linear and tame rather than fighting wicked problems by, you know, what we do variants. We don't do enterprise solutions out ofthe box. We actually believe in customizing, personalizing, tailoring, 'cause that will give us the edge. I haven't heard that story for a while and I wonder if it's a trend or not. And it makes things really hard.

Wade Erickson (29:10):

So you know, we're getting at the top of the hour. I wanted to get in a couple more questions. Really, this is the pivot of the show, to talk about you as a, you know, your career looking at how you came into this space that we're talking about. And, you know, I, looking, looking at your experience, you did start out very traditional work, traditional jobs, and then at some point, you know, you, you pivoted into more of an author, a thought leader, those kinds of things. What, tell me a little bit about what was the, because usually there's something that happens in our lives to, to get us started out of things. What, what was that? I don't know if you can share it or not.

Marcus Kirsch (29:51):

Oh, I'm happy. I'm happy to. Yeah.

Wade Erickson (29:52):

But you know to, to make that jump, you know, for me, I was in the traditional defense industry as a mechanical engineer in 1995. I got a hold of hand creating HTL. Yeah, I saw APIs, I saw that in my head. I was a musician. I saw where it was going to affect music long before there was an MP three. And that I can point to is why I am tech in tech today was I started hand coding HTML and it blew my mind of what could happen. And it, and it all happened, it took decades, but I saw that in 1995 and you know, at early domain names. I mean, it was it was, you know, I can point to that period and tell me a little bit about what, what was that pivot point?

Marcus Kirsch (30:37):

Yeah. And I think it would probably go along those lines of what you say, like, what's the thing that made you angry or something. And it reminds me of, you know, as you know, I run more on podcasts now. I was lucky to get people on like two, two people I met where that made me really feel comfortable going there and going maybe brazenly into like, I'll tell you why. And you know, and one is Tom Peters, who's a management guru, and he, he, he did not mince his words. And I had him on one of my shows and he would just, we were not sure we could put this on YouTube, but we did. So he went there, but he's, he's in his late sixties. He's like, he doesn't have to care anymore. And the other one was the and now I'm drawing a blank, but you know, turned the ship around. So the, the author of that book and which one of my other favorite books and, and, and I asked him like, why did you write the book? And I was like, 'cause I was angry. It's like, well, you were angry. Well, I turned the whole, you know a nuclear submarine management around and made it best ship and fleet. And then I tried to do it again on another ship and they fired me for it and like the heck. So I had something slightly similar like that. So I had, I had started work, I had started work on innovation project and sort of change in companies and I would say maybe it was around about 2007. So I had, I had done a whole gamut of, you know, design innovation. I got hired as the math professor or the weirdo that comes up with weird ideas, a weird approach to figuring out what people can do with digital technology. And it was fun, so much fun that at some point as a joke, I bought myself a white lab coat and hung it next to my desk because I knew people I, yeah, I was okay with not fitting in, let's say it that way. Did that for a while. But I got very frustrating because whenever I push these things, it helped get clients in, but it never converted. And it's like, oh, come on, please. Like if I'm just here for show then I don't see a point of this. So I ended up going freelance and then, you know, ended up with Nissan building active bike and stuff like that. And that started my thinking of, hang on a second. There is really something there, there's something there where there is a deeper value there, but because I'm now doing this as a contractor freelance, I'm not in a bigger company for longer to spread the word. So I have sort of put myself back into a more limited way of being a thought leader or convincing people that this is the best better thing to do and everyone can do it and believe I'm not that special. I think everyone can do this kind of stuff. I do. But I lost sort of the platform that I had previously when I was working full-time in bigger corporations. So then I said, well, you know what, I'll write a book put on Amazon. In theory, millions of people can buy the book and read it, right? In theory, right? But, but, but basically that's the thing, right? If you have a story to tell and you want to tell it to more people 'cause you really believe in it and you got angry about it, that maybe also some people are not going to listen here and there and you're going to go, you know what? I put it out there and whoever wants can pick it up instead of me having to push it on people. So I put it in a book, the Wicked Company, and I started a bit talking about these things that are exponential and systemic and different organizational structures, all of that. I said, you know what? I put story out there 'cause I can't go around the planet and talk to as many people. I'm getting older. I don’t know how many people I could talk to. I'm not, you know, I don't have the profile to go and stand in front of 10,000 people on a stage every Friday. So the book was the thing. And that sort of got me a bit more into the thought leadership and that story that I'm still build building on top of and writing articles on all of that. So, you know, it was sort of stop believing in the idea that I, I I just work for a bigger corporation and a bigger scale and more customers and put these things out and that will give me the opportunity to do so. That sort of failed for me. And so I went out and then I found a new platform and that's, that's essentially what I'm still running with. The only thing is that that went from going out and working in innovation to going out and working on massive global change and transformation projects as much as training. So I just finished training three days on critical thinking and decision making. So the training thing works as well, which still sort of, you know, this week I had like 11 people in the room. It's fine. But it's, I started just to say I need to diversify. I need to bring a mix out of things and a book will help still find to finish the second one. But, you know, try to find new channels. And I think that got me into the idea that I have that energy to not just do my job and work on projects, but I want to talk about it. 'cause I feel, and there's enough evidence in my opinion that what I say can benefit and therefore I just keep doing it, just putting some extra energy into it.

Wade Erickson (35:48):

Excellent. Excellent. Alright, well I need to introduce next week's show and then we'll wrap up if that's okay. Great show. I love this deep thinking kinds of conversations and talking about, you know, things that are a little more than the obvious, you know, and, and, and bring that, bring, bring, bring awareness to, you know, the world of complex thinking and deep thinking and all of that stuff. So anyway, next week we have Andrea, Andrea, GarGall, I probably pronounced it wrong. But CC co-CEO of Amity Co. And we're going to talk about SDKs, APIs and prebuilt applications. And so yeah, it's next week, Wednesday, same time, 9:30 AM Pacific time. And yeah, hope you join next week. Alright Marcus appreciate our time again. Always enjoy. And then what's the name of your podcast? It's is The Wicked what's the name of that again? I think you had a couple that you do, right?

Marcus Kirsch (36:57):

Very, very, very creatively. No, no, it's just one enough. No very creatively. It's called the Wicked Podcast, so there you go. Okay. That's an easy one, I hope. Yeah. And yeah, yeah. And it's like, it started as a reading a business book a week and talking to the author and now it's gotten also a little bit more into talking about team dynamics and talking to CEOs. I would love anyone out there if anyone listens to, I'd love to talk to a couple of CFOs, which I rarely do and might be scary for me, but bring it on. So if any, any of your listeners are CFOs, please, you know, hit me up and I'd love to have a chat with you. Yeah, to pick a podcast,

Wade Erickson (37:36):

Take go. And, and you got a new book coming too, so we'll, we'll get

Marcus Kirsch (37:39):

Yeah, it doesn't have a title yet. It's going to be about teams and team surviving organizations is Okay. Currently what I'm trying to go with. Let's see if it's going to end up there.

Wade Erickson (37:48):

Alright. Wonderful, wonderful. Alright, thanks everybody. And I know we went a little bit long today, but I, I it's all, we're not on broadcast tv. So we're, we're have a great rest of your week and until next week.