Episode 9 - AI Hype, Wisdom & the Future of Work with digital journeyman Vito Forte

In Episode 9 of the Digital Mythology Podcast, Declan Goodman is joined by Vito Forte to explore the growing hype surrounding artificial intelligence, the rise of AI-first organizations, and why wisdom and critical thinking still matter in technology leadership.

Using the myths of Icarus, King Solomon, and the Court Jester, this conversation examines:

• AI hype cycles and exaggerated promises
• the illusion of AI companionship
• ageism and experience in tech
• why business strategy should lead technology adoption
• customer-first thinking in digital transformation
• the danger of losing critical thinking in an AI-driven world

Vito shares insights from more than four decades in technology, reflecting on previous hype cycles and explaining why organizations must balance innovation with judgment, trust, and human understanding.

This episode is a thoughtful discussion for leaders, technologists, strategists, and anyone trying to make sense of the rapidly evolving AI landscape.

Guest: Vito Forte
Host: Declan Goodman

Digital Mythology explores technology, leadership, storytelling, and the human side of digital transformation.

The Digital Mythology Podcast is here to help you bridge the gap between complex tech and human understanding, transforming your digital efforts into a narrative that truly resonates. As you embark on your digital transformation journey, remember that success isn't just about the tools or technology—it's about how well you can tell your story. By leveraging the timeless power of mythology, storytelling, and emotional connection, you can engage stakeholders, win buy-in, and inspire action.  

Join host Declan Goodman as he guides you through this journey, one story at a time.

Transcript

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Hello and welcome to the Digital Mythology podcast. I'm your host Declan Goodman. Today we're going to be talking about AI, the ageism in tech and the power of being the contrarian, the sage. I'm excited to be joined by guest Vito Forte from Perth, Western Australia today. Vito self describes as a journeyman, someone who's been through a lot of tech over the years, quite a lot of hype cycles as well. And we're going to share today some of Vito's insights into how we can make more sense of this overall AI hype and what does ageism sort of look and feel like in digital and also how to be the one who applies judgment and apply some wisdom. So Vito, welcome. Delighted to have you on the podcast today. Thanks, Declan great to be here. So today we're going to be talking about a few things. But before we start, I'd like to just ask Vito if you don't mind giving a wee introduction to yourself and for our guests. Okay. So you're correct in the journeyman tag as you sort of indicated. I've been in technology now for 43 years it's been as of this year and pretty much seen it all from early days of personal computing, mini computers, early days of networking through to dot com hysteria to SaaS, cloud, now, I guess, another hysteria called AI. So, you know, it's been a long journey, and it's been interesting to see in that journey where technology really provided capability to industry and organizations and people. where I guess, and part of the thing you want to talk about today is where We're seeing it not really doing that now and becoming a tool of, for want of a better term, oligarchies to use against the very humans that it's meant to serve. Yeah, it's a, it's an interesting one, isn't it? We, um, it's happening a lot on LinkedIn as well. We're starting to see the hype become a little bit more apparent to people. They're beginning to question the value of it. And it's in the media as well. I think it's everywhere at the moment. Um, in usual digital mythology style, I was going to use ancient storytelling or ancient myths to help explain this. the three myths we're going to talk about today is we're going to talk about Icarus, which is the Greek myth around flying too close to the sun or flying too close to the water. And we're going to be talking about King Solomon. And we're going to talk a wee bit about the court jester. So it is very excited to share these sort of ancient stories with our guests today to make more sense of this. And of course, we'll be using the three pillars of the digital mythology. framework, which is Xin which is heart mind, which is about an emotional drive. It's metaphor, how to use good metaphors to tell a story, a digital, especially all this AI to make sense of it. And catalyst, which is a bit about motivating people. So really excited to get to get these insights. So Vito, maybe we start at the first one. So AI, it's a hype cycle, right? And like I mentioned, in Greek mythology, we had the Daedalus and his son Icarus and they were trapped at the tower. they both had to jump off the ledge and glide away from over Crete And it was all fine. But the Daedalus kept saying to his son, look, don't fly too too high. because you're going to get too much too close to the sun and don't fly too low because moisture isn't good for wax. the myth goes that Icarus, you know, got very excited as people do with AI tools and we're all very excited and ignored the guardrails and of course went too close. the sun and then spiral down. How does that feel in terms of a myth to you to explain this Vito and in your experience, how does that resonate with what you think is happening in AI? It sort of parallels, I guess, what's happening at the moment. I guess the difference to a certain extent is those guardrails haven't really been defined. And they haven't been defined because the people that are driving the creation and adoption have self-interest, right? Their self-interest is to get more adoption than the next. organization or tech company, whatever you want to call them, in order to drive investment, capital and things like that. Right. And as we've seen over the past, it's probably now three years at least when, you know, when chat GPT first came out, there's been a lot of promises made in terms of where we were going to be within a year and then where we're going to be within two years. And I think even when chat GPT first came out, think There was all this talk about AGI being out within the next two years. And I think one of the interesting, you know, I guess myths, we talk about myths in this podcast, but one of the interesting myths there is, is just the basic understanding of what large language language models are. They are fundamentally a probabilistic algorithm that just picks the next word, not based on it thinks or conscience or sentience and all of this paraphernalia that gets spread by the AI companies because they're trying to humanize what is fundamentally inhuman in order to drive adoption, which then drives revenue, which then drives investment. Right. So I think understanding the motivations is important. As we are seeing those Promises or the predictions that were made several years ago are sort of not becoming true There's there's been a lot of talk of especially recently Of AI slot and we're seeing that everywhere. I think there was a comment I think you raised it around, you know if if I like on LinkedIn and it's probably worse on other platforms if if an author just publishes uh AI generated content, is it actually appropriately, does it have an author? And my answer is no, because they're not the author. A machine is an author. And it's just chosen a bunch of words that sound really good. But if you really dig into it, does it really make sense? Does it have the human context associated with it? And we're starting to see, you know, reports of OpenAI and their capital expenditures with very little revenue, they're masking Microsoft, and it's obviously very visible failure with Copilot. think their market cap dropped by a trillion dollars, right? I mean, it's astounding the amount of money that seems to have been lost, yet it doesn't seem to matter. Now you think of that volume of cash and what it would actually do to the world, right? I think there was an estimate once that said total world poverty could be eradicated with, I think it was 10 or 100 billion, one of those, pick one, but that's still much less than a trillion that just disappeared in the space of the week. So I fundamentally see there's a number of organizations that their wax is melting, it's melting very quickly, yet they're trying to, let's say, clutch the feathers together and flap like crazy to see if they can survive. Yeah, flap like crazy. And it's funny that it is because that's why I like using that myth because there's this kind of element where I like it a bit further than just the fact that there should be more clear guardrails. But it's also the fact that it was an escape because I think people feel the urge and organizations and leaders feel the urge to get off that ledge and jump into the AI. cycle. If you don't, then what are you doing? not a progressive leader. But if you do, how far do you go with it? And it's kind of, you know, another point that was raised by someone I think, you know, talking about, and you see it everywhere. Everybody wants to be an AI first organization. And when I put my large decades experience hat on, never in the past has any organization said that they want to be tagged with a technology first mantra, right? their customer first there, you know, they want to be within their industry because the technology is always been the supporting infrastructure, the nervous system of the organization in order to deliver whatever it's outcomes are saying your AI first is putting the tool ahead of everything else. And why would you do that? How does that make any sense? You might as well say I'm Excel first or I'm database first or pick an application and I'm back first because that's what it means. I mean, as a customer, as a lay person, you're going to look at that and go, doesn't make any sense to me because my customer service capability is still terrible. I can't access the things that I need to access because that's still terrible because now I've got to deal with a chatbot that just, and I've got great examples where banks and others have done it and they spray all of these options in a chat window on a phone that goes past the bottom and you've got to scroll around and you go, it's too hard. Right? So what is it serving? Is it serving you that's giving them money or is it serving them by some way that they've got some weird internal metric that says it's all great because everybody's using it? Well, that's because we don't have a choice. That's right. We don't have a choice. it's Alright. we've been through these cycles before. mean, not quite like this one, but I have this feeling that this one is a wee bit different than the rest because it's sort of like it's very seductive, you know, like it's very like Before we had cloud and then we had maybe virtualization and then mobility and all of these new and customer personalization and all this stuff. But now we have this companionship that people are experiencing on a one-on-one with their AIs talking to them on the daily. And, know, well, I can use the word companionship with inverted commas, but my point is there's an immediate deceiving factor, guess I feel is that it just feels like a human. And so it's very easy to assume that they don't have a I will have the same analytic or problem solving for predictive skills as a human. And I know only recently it came out only a few days ago. I think Microsoft said most of us with white collar is going to be able to work within 18 months or two years and stuff. And you're thinking, how is that going to work? It's not it's it's not it's nonsensical. It's it's again, marketing ahead of any substance, right? Because they, as I said, they've lost a trillion dollars in market value, how they're going to try and get that back, whether they need it or not is a different discussion. And that's by trying to say, I guess, things like that, that sound remarkable, because they're not Don't forget, they're saying that not to people like us. They're saying it to CEOs and executives who just see people as a cost that needs to be reduced, right? Anything they can do to reduce that cost just means that their margin and whatever other revenue they're looking at will be greater. They're ignoring whether it's good, bad, we'll actually get them any more customers or not or whatever, right? that doesn't even come into this frame of mind. So I think once you put that lens on this sort of talk, you get to understand what it's really about and it isn't about improvement to society or anything like that. It's fundamentally about money and that's it. the next topic I wanted to talk to you about around ageism. In terms of mythology, the thing I'm trying to refer back to, it's not quite mythology, but it's King Solomon and this biblical character about when the great creator said to him, I can give you anything you want. What do you want? Do you want power? Or do you want wisdom? He chose wisdom. He chose the ability to judge more wisely because King Solomon seen that been able to, you the long game, the strategic game. And of course he went on and he wanted to build an entire temple and build an empire. And he knew to do that, he could only do it with wisdom, What are your thoughts on that Look, as someone who is in their twilight years, I guess I can say, but uh it's been, it's been in tech terms, well, yeah, it's been prevalent for a while. And it's actually gotten worse. And I think it's related to the fact that coming back to your point about wisdom, people perceive your ability to discern, let's say, false idols, right, as a negative, right? And, you know, vendors now have substantially more power than they used to have. They have an ability to directly influence very senior people in organizations with promises of magical ROI and productivity gains and you name it. I've heard it all before, right? And they get them to sign up to all sorts of stuff. But when it doesn't get delivered, it falls on the relevant department to deal with it. But no one's necessarily held accountable. There's no view that says, well, hang on, you promised X, Y, and Z. Why didn't we get it? And it turns into this, let's sort of bury it. let's not talk about it. It's sort of good enough and let's just move on. Right. If you put the AI piece on this as well, the challenge with that is that how are you approaching what you want to do with AI? Is it just from again, I just need to put AI in because everyone else is doing it without actually understanding, is it actually going to help your business? Is it relevant to your business? Is it relevant to your customers? Is it relevant to your staff? Why are you doing it? And it's always needs to come from that perspective of why, right? This is how you, you get people to engage. This is how you get people to buy into whatever it is that might be. It's not by just pronouncing from up top, we will now do this and just people go, well, do we need to do that? Is that money better spent there or should it be spent on the actual systems that we currently have that have never been updated? for the last 15 years, which by the way, has all the data that they had, I systems used, but it's all garbage because no one's maintained it. So you end up in a situation where they'll put in the shiny object, shiny object doesn't work. It'll be somebody else's fault. and then the organization just goes back to doing what they did before the shiny object appeared and then that gets buried in several million dollars later, they'll start again. And that pattern repeats often, right? In many organizations. because there isn't the right conversation. And I'm a big fan of you want to really prove it two or three times before you change something. There are instances where those changes need to be done and there's good reasons to do it. But prior to AI, all of those transformations were additive to an organization and to its people. The AI stuff isn't. tends to be negative. It's negative to the staff. It's negative to, because if it's not negative to staff, it doesn't return. There's no return. There's barely any return now. So the only return they can deliver is by saying, well, we're going to replace X number of people in whichever department and replace it with agents or whatever the case may be. And then you've got a set of things, and I'll use that term, running that don't And this is the other thing people underestimate the level of complexity in many organizations processes, right? And think that the complexity is there because people don't know what they're doing. The complexity is there because the organization doesn't know what it's doing and hasn't chosen to fix it. Yeah. So there's all of these layers that seem to get forgotten about when, especially when the AI stuff starts to, uh, starts to appear on boardrooms and all the rest of it. And instead of taking an approach to say, you as the people that do this day to day, if you had a tool that could help you deliver this quicker or you could do this job better or whatever, what would that look like? That's where you start. And you get them to do it and you get them to prove it. Because if they don't do it and they don't prove it, they will never buy into it. And you will have a nice shiny set of stuff. that no one uses and adoption is one of the key metrics of any technology capability. If there's no adoption, I'll go back to Microsoft, right? What happens? Yeah. And look, that's the kind of King Solomon aspect of it, isn't it? It's having that wisdom to know that if you've been through this a number of times, remember, there's a lot of expectation nowadays. mean, every tech conference there is, they're talking about AI and how important it is to get on board. But that's a bit of pressure for leaders today to say, look, I can't not do AI. I have to do something. when they look for what should I focus on or what at least should my strategy, then what are the maturity capabilities I need to build first? I think you get a lot of that benefit from people with experience, you know, from the, from the, yeah. right? This is one of my pet peeves, right? And for many years, you know, my view was always that the technology strategy is aligned with a organizational business strategy. It's not independent of it, right? So if we're now going down the realm of creating an independent technology strategy because it's got AI, the two letters of AI in it, How does that make any sense? So if your organization is about selling services, right? You're only going to get revenue by selling more services and those services are of an appropriate quality that people want to pay for them, right? Yeah, that's where you start. Now, whether the AI helps or doesn't help that, that's part of that journey. It's not from, we're just going to do AI and then work backwards and make them and hope that we get quality and capability and all the rest of it. It's the wrong way around. And this is because The people that are selling it are selling it that way because they're not accountable for it not to not working. You are they going to say we only provide the pipes and plumbing because it doesn't work because you're not making it work and they walk away with their millions of dollars. There's not much point in writing a strategy about an enabler. The strategy should be what does the business need and how is it going to help us be more successful as an organization or what are the customers doing? What way are we heading with our market industry? I was a big fan of one page strategy on a page, right? It needs to be articulated in a manner that's understood and buy in actually happens from the people that are meant to deliver it. And that's how you measure its success or failure, right? If you don't, you can write a 60 page document, right? But then that's not a strategy, right? That's either some sort of project definition or some other thing, right? And this is where we get caught up. And if you end up with, you indicated there, five, six, eight, 10 different strategies, who's going to make sense of that? And who's going to care? Yeah, well that's a... and also what'll happen, what'll happen Vito is they'll just give it the co-pilot to summarize into a top... Well, exactly. So what you'll end up with is a strategy that's formulated by an AI that looks very professional, has all the fancy buzzwords in it. So you can tick all your buzzword boxes, but actually is nonsensical and doesn't really mean anything. Right. And I think that's the other danger here. And it's becoming prevalent in organizations that are using these tools in that way. And the challenge with that for most people is it removes that thinking you raised that earlier. You're thinking about, so if you're accountable for delivering something, you've got to think about how you're going to do it. How do you convince people to do it? And then how do you make sure that it continues to work appropriately? If you take that, those people out of that loop, who's going to do any of that? The AI. Right. So what are you going to see? You're going to see a nice looking. fancy documently charts and verbiage, but a wasteland of delivery. Yeah. So this is really nice. Lead us into the next topic. And that one was really about being there. So, you know, been brave enough, I guess, and having the leaders and organizations having the space really to be able to challenge them what's going on. And again, nice archetype I like to use is the court jester. So back in the medieval times, the only role that could challenge the king or the queen and like make fun of what's been proposed because it's so preposterous was the court jester. So they were allowed in fact in other philosophies to court jester different names. They're kind of often referred to as the fool but not in the fool and been ignorant but they play the fool because they can see that the whole thing is just a hype, it's a game and they see through it. Right. So that's what I like about this one is the third topic for today. And it's really around that catalyst side of the pillars is how do we give people and empower people to be the court jester, right. As in to be the one to say, well, know, hey, on, you know, we we we can we can do all of this AI stuff. But, you know, we need to maybe um look at the bigger picture and say, you know, maybe challenge it. Like I sometimes think it's almost taboo these days if you start challenging adoption of AI because everybody else is doing it. I think now more than ever, need that court jester type archetype to just be the contrarian and say, and that's what ties in well with the people who've been in the industry for long enough to know. Cause you know, that's often another aspect that the court jester was they were quite sage, like they were wise, they'd been through many experiences with the court. And so they were the ones that they had the sort of the, the, the currency, really the knowledge to challenge the powers that be on it. I'm just wondering, you know, does that, how does that, does that kind of what you're tending towards when it comes to this, you know, been, courageous and just questioning why, what are we really doing here? We need to do it. and bravery is required. The other point in this is trust, right? So you need trust between the leadership and the relevant parties involved in developing any this, right? And, you know, it's one of those things, and you've probably heard it before, and I hear it all the time. And I think there was another post a while back where someone talked about You know, AI should be should be led by IT and not the business. So my, my, and I always pick people when I hear that kind of stuff. said, but, I teach part of the same organization that finances. Do you say that it's the business and finance? Do you say it's the business and HR? You don't. So why is it? I'm singled out as being different and requires that extra level of. Fundamentally, it's a complex discipline. It's become more complex over the years. It's critical to an organization's overall capability and success. So it tends to attract that. But the fundamental part in terms of being successful, whether you want to challenge the status quo is a level of trust within leadership that allows you to do that, right? If that doesn't exist, and this links back to the previous part that we talked about around wisdom, right? Because generally what happens is that contrarian attitude comes with experience and wisdom, which generally means older, which then generally means are you still actually there? So you tend to have the situation in many organizations now where people are still um people in particular leadership positions don't have that perspective because they've never been through that perspective. And by the time you do have the perspective, you sort of no longer want it, right? You're sort of surplus to requirements. So it's getting worse. So that spiral is getting worse at the moment. You know, if I look back at my experience, there were probably four... organizations where that trust existed and we were very successful in terms of making sure that we got those capabilities and transformations done in a manner that delivered real value. And there were other organizations where, let's say that that wasn't there and then they were prone to substantial failure. So you end up having to survey the organizational politics because that will drive everything. You can be the court jester or you like, but if the organization is not one that actually respects that opinion, you're wasting your time. And I know it sounds fatalistic, but fundamentally is right. And they will search for an opinion and advice that matches their particular view and will not accept any other advice or view. So that's the other part. can sit there banging on about it, but you will find that in those organisations it won't make a difference and you need to make a choice. Do you want to stay or do you want to go and take your skills elsewhere? in terms of summarizing this, this overall space, then when we talk about AI and what it means, have Icarus, the Icarus myth, which is there are loosely defined guardrails, but before you jump off the ledge, or you may already have jumped off, just keep an eye on. being too ambitious, going too far or being, I guess, too not knowing where you should be heading, which could bring you too low and it could be a bit of a major failure. So the answer to that, I guess, is, you know, just just try to be a little bit guarded there and use some some reasonably good thinking ahead into where you want to end up. The next one was the King Solomon. So that's really about the wisdom piece, which is just about rather than quick fixes, think a little bit longer term into building foundational AI, adopting it, as you mentioned, in an adoptive way that because adoption is key. So have a few small pilots maybe and go slow. And then the third one is the court gesture. That's really just about searching out the truth, you know, really challenging, at least, you know, yes, a lot of hype and yes. this thing's moving, but is it right for our organization? And does it make sense at the moment? Should we be a leader with AI in this or should we be a follower? Sometimes it can make sense to be a follower if it's not really part of your core business. They're the three kind of areas I wanted to call out, which Vito very well articulated in terms of getting some takeaways to before we wrap up for our audience. We have the, you know, Xin heart mind is about finding the why and making sure that within your guardrails, it makes sense to play an AI space there. The metaphor pieces around Solomon, and we all know how wise he was, but also bringing in the, you know, ageism aspect. There can be a lot of value there. And then lastly is really around the gesture. As you mentioned, the catalyst that's empowering people to ask the right kind of questions to challenge. whether or not AI makes sense. Have you any other takeaways you'd like to share with our audience today? Well, fundamentally, and I've always worked from the premise that says you always put yourself in your customers shoes, right? So whether it's, you know, your customer is an internal customer, whether your customer is an external customer, are you public facing, are you not, whatever the case may be, one of the key I guess failures I see and have seen over the years is where people do not do that and deploy technology based on their own perspective, which destroys customer value. Right. And, know, most organizations are out there because they deliver something to customers. Well, what is that? And how can that be enhanced or improved by any deployment of any technology? mean, at the moment, all the hype's around AI. but you only have to go back a few years where a bad app can bring down an organization, right? And those sorts of things. Yeah. it's not a difficult, well, it shouldn't be a difficult thing to do, but we, many technology people seem to have an innate ability to think that they're better than their customers and forget who pays their salary. So. You know, I think that's, that's one of the key takeaways that I would indicate. And, you know, having been in education institutions, mining institutions, in engineering, know, um, shipping, all this sort of stuff, various assortment of different customers. One thing I can say is that they are fundamentally all the same. They don't want to be hassle. They want their job to be easy and they just need to get their stuff done so they can go home. So. It's pretty much there, right? And if you cover all of those bases, you're doing pretty well. Yeah, look, that is the key though, isn't it? It's like a technology should be there to make business and customer experiences easier, Yeah. Yeah. talk about that all in this sort of stuff, right? know, simplicity is hard to do. Right. So people find it difficult and choose. Complexity, right? And sometimes it's chosen because it makes people feel like, see, I know what I'm doing because look how complex this thing is. Right. Doesn't need to be complex. Right. Yeah. who are you trying to convince? Right. So I think using those particular perspectives is important and will make whatever it is that you're doing much more adoptable and usable. And that's how you spread the word on whatever it is that you're doing rather than falling into the trap of making something complex because it's looks good or feels good to someone internally which is completely irrelevant to the people that actually have to use it. important. suggest that many organizations, if they're smart, and they have their really good marketing people will start to look at their competitors who are busily saying that they are AI first and they will choose a different mantra. So you know, if you're a university student, and you need to choose a university, do you want to go to the one that says that says they are AI first or the one that says that they are student first or they are job first or they're a professional first, which one would you choose? Right? So I think that's part of that thought process, right? Cause saying AI first means nothing to most people, right? Apart from certain leadership or the, and if any organization says that, as I said before, it is not directed to their staff or customers is directed to their investors. And that's basically all it's about. Yeah. So just another, just another point, which generally, um, isn't just about AI or technology, but, you know, fundamentally life in general and, you know, life is about contrast, right? If you don't have struggle and low points, the high points mean nothing. Right. So you talk about people coming into tech now. Now, if all they've ever learned is to prompt engineer and outcome. How do they know that outcome is actually the best outcome? So where do they apply those critical thinking skills? How do they know that actually what I'm generating and I've got a good example. I'll use my son who's in cyber and he's been using one of the big LLMs to help and do code and that and he's been doing that for probably at least 12 months now and the other day he just said to me off the cuff he said I'm going to stop using it now because what I've realized is that it just generates code that's overly complex, very repetitive, and just requires me to spend so much more time dealing with it than to me just doing it myself, which is becoming very prevalent in many areas as well. Now, the AI companies don't want to hear that. But again, if we go back to what an actually an LLM is, that is not a surprise. And this is the challenge for newcomers, right? You know, when I was a newcomer, there was none of this stuff you had to learn and you learn by making mistakes. Right? How do you do that when you will, you've got these abstraction layers between you and I'll say reality that mask a lot of this, yeah. And then it becomes your problem to try and decipher what's being created. And this is where there's probably not as much discussion about because in 10 years time we're all gone and we're not in the industry and we're not there saying, that doesn't look right. Who's going to say that? Yeah, that's a really good point. Who's going to be the, the jester at a stage to say, this doesn't make sense. That's if you've still got a job, right? Because based on the predictions of many of these organizations, all the white-collar people are gone. So there's no one left. So no one's going to be able to do it, And I know about you, but I really don't want to live in that kind of world. No, know. I tell you one thing, it's going to be a very interesting world. you know, I think about people who are in college now or high school looking to go in. It's going to be very interesting what they're going to kind of world they're growing into. You know, can't put an old person's head on a young person's shoulder. you know, often you have a push, a drive, and then afterwards in hindsight, yeah, wasn't the best. But the key takeaways would be go ahead and move with the tide that's coming, which is AI, cause you have to be, remain competitive, but do it with a kind of a sprinkle of sensible judgment because I'm bringing those people more mature in their career or look for some advisory assistance from people in your network who've been through one or two hype cycles because I think that's what will really bring that human led decision making to the table, which will help. Vito, really lovely chatting to you. Before we finish up, Yeah. oh level, know, have you any, you're based out in Perth, WA, have you any hobbies? Do you like surfing or something or what is it you do to come down off recently taken up swimming because my wife did a lot of swimming and I've chosen to take that up to honor her achievements and she managed to do a solo crossing to Rottenest Island here which is a 20 kilometer open ocean swim and she did that in 2019. So It's hard work. I knew what she did was absolutely outstanding, but now I know it's even more than that. And respect to her for that. Apart from that, do just general stuff. There's nothing too exciting. I'm a pretty boring sort of person, and I like my sci-fi and various other bits and pieces. But I'm looking at you know, trying to help others where I can and finding, you know, purposeful activities and that journey continues. So definitely not the AI space that to me at the moment is not purposeful. It's just a rabbit warren of deceit and dehumanization. Let me say that. And I know that sounds very negative, but it's becoming um it's becoming. from that perspective. But yeah, apart from that, that's basically it for me. Fantastic. Well, look, thanks again for being such a guest. Lovely chatting to you. session. If someone wants to get in touch with to avail of your court jester or of your King Solomon or maybe some Icarus. search grumpy old man. Yeah, grumpy old journeyman. Yeah, that's right. They can find you on LinkedIn and connect and go from there. Fantastic. Well, thanks again for your time. It's been a great session. Fantastic. Wonderful. Thank you.