The Real Work Begins: Why We're Talking About AI and Human Teams

In this first episode, Dominik Fretz (AI consultant, Harbour Edge Intelligence) and Sean Irvine (team dynamics expert) explain why they're tackling the messy middle ground where humans and AI collide in the workplace.

Forget the hype about AI replacing everyone or being a magic solution. The real story is about integration, adaptation, and the very human challenges that emerge when AI joins your team.

The hosts share their complementary perspectives—Dominik from the tech trenches and Sean from the human side—and preview the critical conversations ahead about fear, trust, truth, and practical implementation.

This is your starting point for understanding not just what AI can do, but what happens when it meets real people doing real work.

Transcript

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Welcome to Real Work: 0:00

AI and the Human Team. Where human potential meets artificial intelligence. We explore the critical space where people and AI collide, collaborate, and create something better together. From trust and fear to teamwork and transformation, we tackle the real challenges of making this partnership work. No hype. No jargon. Just honest conversations about the future of work—where humans and AI succeed side by side. Here are your hosts, Dominik and Sean. So hi Dom. Uh, welcome viewers to our first episode of Danger Will Robinson? Well, we well, we don't know if we're going to call it that yet or not, but we've got two people having a, having a conversation. And we're really having a conversation not about AI, not about, so Dom's an AI expert, I'm a team coach, but about the interaction, about the about what happens between humans and AI. I think this is a really interesting topic, you know, there's lots of, lots of experts in one field or the other, but it's just an interesting thing for us both to talk about. Yeah. So yeah. What what are you doing? So for me with AI, I'm playing with AI just now. You know, I get it to write things for me. Does some lovely documents, that sort of thing, but really, really basic stuff. I I did try some coding. Uh, yeah, that was fun. That was that was days of of me uh, I think I actually broke Claude. Oh, really? Yeah, yeah. Did you fix it again? Yeah, I went away. Oh. I mean, I mean, you're you're doing team coaching, right? So I hope you could coach Claude a bit. Oh, oh, I had one of those, but that was with chat GPT. Sorry, I had to pause for a little minute there. I'm a little bit dyslexic, so I sometimes get my T's and my P's mixed up and they're about the same so. Yeah, yeah. So I, I I was working with with uh chat GDP and I asked it a question. And it it it gave me some really interesting data. And I was really excited about it. It was really useful for me to approach a client, do a sales pitch in around this area. And I, the document, I I then I decided I would check out the references. And the document took me to it took me to a document that was dated 20 2023. Yeah. well, that's that's fine. But then I thought, I should read this document. I'll read the whole thing. And actually it was presented in 2000, the report was presented in 2017. Didn't exist anymore anywhere else except in this article that had been redated. Okay. And I, I give, I give Chat GPT a lecture. Yeah. Yeah, what about you? What are you doing? Um, I, I just came back from the US, living in the US for a couple of years, um, and really over the last year, I've been doing, um, I've been working with companies that want to learn a bit more about AI and how they can integrate AI, um, tools and technology into their, into their team or into their work. Cool. Uh, really to accelerate their team. Um, um, and in that direction, I, I'm just building my own company and I'm using, I'm using AI every day, multiple times a day. So one of the interesting things when people hear you're just back from the US, you're you're an expert in AI, you're doing all this work and you're getting it to do the work for you, etcetera. And uh, one of the interesting things is you weren't in Silicon Valley or even Texas. You're you're in Alabama. I I actually was in Alabama, yeah. Um, that was, was definitely a bit different. Um. It's Alabama is a little bit more hesitant to adopt technology, at least the south uh South Alabama, it's away from the technology centers. Um, Birmingham is Alabama is much bigger uh on that already. They have a have a vibrant AI scene even now. Um, so that's, that's uh, is is one thing, but in the south, they're a little more hesitant, um, uh, and cautious not to like, yeah, too brash to to run up to new technologies, um, and use them. But there is also a lot of people that really embrace it, um, and really want to want to use it. Um, another thing that I learned is, um, what's probably a little different to Australia. A lot, there's a lot of people that like, oh, I have an idea, I want to, I want to test it out, I want to go and like, I build a product or like try and sell a product, um, try to see if anyone is out there that wants to buy it. And often here, I see that a little bit slower, there's a little bit more hesitation. Um, that's interesting. More innovation, more, more drive for innovation than in Alabama than here. Um, we are, we are, by the way, if you're in Sydney, Australia, so we we've both lived here. We might not sound like it, but we've both lived here for quite some time. Yeah. Um, yeah, it's not so much the the drive for innovation, the drive for technology. But it's a, it's the mindset in the in the US, which is is a little bit more entrepreneurial, I think, than than it is in in in Australia at times, and in Europe where we're from. Um, and so the, the entrepreneurial spirit is is much bigger. And I was a I was part of a of a program called Builders and Backers, um, and, um, in Mobile, Alabama, um, it was driven out of the innovation portal. Um, where we met a few times and I've met many people that came through the innovation portal, which is a co-working space and acceleration place for for startups. And there's a lot of a lot of people that like have no business background, but they have this one idea and they they go and find the people that have, um, experience in building things, um, and then they they run with it and and like yeah, I've met someone that, uh, that built, um, essentially an an using AI back end, um, and using AI, um, I think it was a a website about spirituality, um, and about how Wow. Yeah, yeah. It seems it seems completely wrong to go from spirituality to AI and use AI to to promote spirituality. It it's sort of, you know, your gut feel on on AI goes completely that goes completely against the Um, yes, but they used AI as a tool in this case because they're they're not a technology, they the person wasn't a technological wiz, they used, they know how to use a computer but um not not an expert and they don't necessarily know how to build a website and um and also don't have the funds to go and hire a web design agency to build their website. Mhm. But they Yeah, through the program I don't I don't either. My my website's awful. Yeah, well, maybe, maybe we should look at that with Maybe we should. Maybe we can get some of your tools because we were just discussing just beforehand how the the various different number of different tools. And they're all specific to certain areas of expertise. They can't do all the things. But I'm going to go back a step, Don, you said Alabama and they you said some hesitancy and some acceptance. And I'd like to go back, that's a really good start point for our conversation together. Where, where, you know, there there is a hesitance, and I think you talked about a fear. I think we should do a whole maybe a whole podcast on that at some stage. But there's a fear in people that it's going to steal their job, it's it's going to tell lies. And well, that's another episode because, you know, when we talk about telling lies, I I see a whole world out there where we we don't so much tell lies as except as they source our own truths, I think. And I think that's something similar what AI does. We should do that. But let's get back to this hesitancy. Do you find that hesitancy here in Australia so much? Um, it depends a bit on where you're going. So here in Sydney, the and this is this is my bubble that I'm moving in, obviously, I'm a technologist and I um I'm Except for me. Yeah. Um I need to counterbalance. Yeah. Um, and so I move in often in circles that are very accepting and and experienced using new technology. And so, um, the people that I often talk to, they they are very accepting and very exploratory and they they go and use it. Um, I also, but you're on a business and you talk to people who don't do that. How do you find them? Um, the again, Sydney is is further advanced. So here we there's a lot of people that are very curious, that are already using tools, um, or at least their staff does. Maybe the maybe the bosses, especially on on like smaller businesses, um, often people don't have or the the operating offices, um, ops managers or CEO, they don't necessarily have time to like look at technology. If they're not a technology company. Mhm, mhm. Yeah, yeah. Then they don't have time. I get that. Yeah, yeah. They've got people to do that. Yeah, and but often enough, like if you have a smaller company, um, let's say a lawyer's office or a landscaping company, they they often don't necessarily have someone that does their IT stuff, right? They they might they might buy this in from a service. Um, or they just have a few computers laying around, um, and so they're working on their business or in their business and they don't really have the time the time to to look at other stuff, but often enough there is an employee or two that like got a new phone recently. And with the new phone, they have a year's worth of Gemini, Google Gemini, um, subscription. Or they really like how Chat GPT can help them to do meal prep by it's like, hey, Chat GPT, I have this in the fridge, I need to make food for a week. Um, give me recipe ideas. That's that's interesting. Yeah, because, you know, for me, I love to cook, as you know, and I've cooked many times for you and and and as you have for us and we we would have parties at whatnot all and and share food many times, but when I look in the fridge and I come up with a recipe like that, it gives me a sense of satisfaction, pride that I've actually done this. Yeah. How does that work for? Um, how does that, how does that, how does that, what we call it, self-esteem, how does it build self-esteem whenever you actually cook a good meal for friends and use AI to do it. Um, it's often it's just it's, um, time poor, um, time poor professionals. Mhm. Um, like me. You, you run, yeah, you run your own business and you can, you can set in a way your own time schedule more or less. Um, the obviously your customer is your boss in a way, but um, and you might have a take a little bit more time to to decide, oh, I want to do a good meal with my friends or for my family. Um, I do that. Um, but there's other people that have a full-time job, they have kids that go to sports practice, they might just not really have the time and brain space, um, to to think of a menu menu plan for a week, right? So they're not actually getting their self from that. Yeah, they they're not they're not cooking for love. Yeah. They they still might from time to time, but the bulk cooking is like I need to be feeding my family this week. Right? Um, and that's not, that's there's no like judgment on that. It's just that's just what it is. Um, but so what I was getting at is these people like this have, um, have experienced whatever it is, chat GPT, Gemini, Claude, um, and they, um, do then take that into the office because they're like, hey, I this really helps me with cooking and with other stuff. So how about I ask it to help me with tasks in the office? I'm I'm, as you know, dyslexic, I'm dyslexic, I I get my letters mixed up and I was a bit traumatic because in my day there wasn't such a thing as dyslexia. There was, you're punished for not doing your homework. And I, what, what I find really beautiful is that it can help me frame words and take take that fear away of of writing prose of any type. Even even a short email where I need to have an impact. I find it really useful for that. And I think just thinking from a personal perspective, not from a team perspective, whenever I I sat with a PowerPoint this morning and a run sheet and two days of of complex interactions. And there was two of us worked through that and did the PowerPoint ourselves. And moved the PowerPoint, shifted some stuff, designed some new slides, added some other slides in, took some slides away, and just from our our sort of bank of slides. And I could have asked AI to do that and I'm sure it would have done a good job. If I told it what the what the intention was. However, I find that actually building it in that way helped me understand where my my my clients will be mentally, you know, what what sort of mindset they will be in as they go through. When to slow down, when to speed up because I'm sort of experiencing it as I write it, as I develop it and design it rather than just throwing it into a chat GDP. Um, and this really depends on how you use the tools, right? Um, in this case, you're working with your colleague and you're talking through things, or maybe you're working by yourself, but you're mentally going through your presentation and like, then I say this, and then this is the points and this is the story that I want to tell. It's actually more, what what I'm doing is more it's more of an interactive facilitating thing where people are doing exercises that put them in a different mindset. And they, for instance, you know, if I'm working with a team, working on team purpose, it'll be, and I tell them right, write your purpose. Here here here's a format off you go. People won't be able to do that unless I do some things before that, like take them through and depending on the team and where the team sits, take them through something like a stakeholder chair where they role play as one of their own stakeholders, or you know, a nightmare and dream type concept where they they they what happens if we do do our job well and do come together as a team, what happens if we don't, should we and it's start start them to think about what what they're what their meaning is, what what's the purpose of this team before they write their purpose. Yeah. So I, you know, I I find that a useful process. Yeah. And then I'm ready to actually do the presentation, do the the team event, do the interaction, or the yeah. And I, I sometimes wonder how well, how how well we actually to say, this is an AI task. Yeah. This is not an AI task. And sometimes the problems we have with AI are because we've given it a task that really shouldn't be its. Yeah, absolutely. Um, but kind of going back to what I was starting before, it it is how you talk to AI about problems like this, and I'm coming from a software engineering background and I I learn new technology things all the time. I don't remember how many, um, how many, um, programming languages I learned over my my years, um, but now I can actually use these AI tools to help me learn quicker. Because if I if I want to go and write a an application in Python, I'm not, I'm not good at Python, I can read it, but I don't know the the thing, um, in depth, but now I can actually go and say to AI, hey, um, help me write this in Python. Um, and I can even say, I want to write it myself, you give me tips on the way. Or you critique my code, you tell me, you let me write this and then tell me what I could do better. And this works on so many levels. This works within the within the um the programming environment that I'm using, but these these things are more and more rolled out in the commonly available AI systems. And even today with Claude, um, you can, you can go in and essentially say, hey, I want you to be a tutor and I want you to help me learn um this topic, um, and I going to ask you or I going to present problems and you have to ask me questions about it and then critique my my answers so you can, if you want to, if you use the tools correctly, you can actually use the tools already to be a tutor to learn new things or to to critique your own work rather than just throwing everything at it and let it do its thing and taking the shortcut. I I have actually done had some experience with that, but before I, before I talk about that, about exactly what you're talking about, from a less coding background, my my the last coding language I used was basic. I don't know if anybody's even heard of that nowadays. But I, I, I did keep up some sort of coding going after that. And I did, I do remember moving from Siemens S7, S5 to S7, I don't know about nine, didn't get there. I programming PLCs and that sort of stuff in in operations and in factories and stuff. I, yeah, the piece around, I I've had some stuff, some experience with that. And I've had a really good discussion with Claude and I've told it to do the research thing because there's a research button. You told me about it. And I done all that and it was quite exciting and it and it sent me down a path and I, no, that's wrong. And said, okay, that's wrong. Let's go this way. And it took on board my opinions, went out and found some stuff. And yet, it it took something on that it kept telling me that the methodology we use is complex. Whereas actually it's not. But it's found somewhere or other that that it's complex. You know, we there are some simple models for team coaching around. That aren't based in science, ours is based in science, the one I use is based in science, the main one I use is based in in science, research, peer reviewed, all that sort of stuff, but it was too complex. And yet I look at other team coaching, most other team coaching methodologies are even more complex. They're actually almost complex to the point where they're, I I to put it, glorifying the team coach. Whereas we're trying to bring it to a level that that real factors. So I didn't agree with everything we ended up with, but I do see where it's coming from and it is an avenue for marketing for me. So, yeah, it was it was an interesting, interesting adventure. No. No. Mhm. Yeah, um, so what what do you see besides like doing research and and that, do you what do you use AI systems for or where do you see a a benefit for you? For me, you know, there's a distract, a destruction that it creates. It keeps offering me suggestions when I don't really want suggestions. I just want to open the email, that's all, I don't need a suggestion on how to open the email. I, I do see that, uh, if I was selling widgets, a huge opportunity for it to do all the background stuff. I do see building a a bank of of information and using it that way. I don't know, how would you put it, if I could actually link various different exercises that we do in teams, link them to purpose, bring that in, get it to learn from that. Because I'm not 100% sure it learns, I asked it about team coaching and I asked it to do something around team coaching. And I went, no, no, no. I'm not going to get them to blow up balloons or whatever ridiculous thing it asked me to do. And and I I sort of gave up at that. But I think it's worth having another little look and say, what are the things we can do? Yeah. Yeah, and with with this, I always look at it as the the tools that we have right now, they have an incredible, I want to say knowledge base because they're trained on so much data, human data. And that human data sometimes is flawed and is contradictory, right? And that's where problems sometimes come in where it's like suddenly trying to reconcile two two different points of view, um, and make one and then present it as a solution to you. But it's, I often compare it to, um, a very intelligent or very fast, um, intern essentially that hasn't much life experience and doesn't have much business experience. And so if you imagine, it's Monday morning and your new intern starts today. He, he or she comes freshly from college, doesn't Reads really quickly. Reads really quickly, writes really quickly, writes pretty well. Right yes. I must admit, the the called large language models. They're they're fantastic at language. Um, and so imagine they they they have their their mindset where they're coming from. I put that phone on do not disturb. It doesn't really care about that, hey? Um. So they come in and they have they have their own upbringing and their own school experience, but they don't really have a business experience. Yeah, yeah. And then you say, hey, go and give me 10 ways to do better team building because I have a presentation to a customer tomorrow. I need to build a presentation. They would probably go and like search the internet, um, Google it. And even before Google did the AI summary, um, they would come up with a few websites and then there is probably a few websites that say blow up balloons together and like fall into each other. Absolutely, yes, yes. Roll balls down tubes and things like that. Exactly. Whereas, you know, from from my experience over the last many years, teams don't get better throwing balls down tubes. They only get better doing the work that they do. Yeah, so now compare that to you, the new intent comes in, and same scenario as before. Um, but now you give them your training materials that your company develops. Your extensive knowledge of what worked for your big big and small teams. Um, your maybe, I don't know, if you have case reports that you keep for your own records so that you can if you go back to the customer um, in six months. And you give them all to that intern, and if that intern is human, then it will probably take them a week or two or a month to read through all of that and process that. Never mind actually I create some opinions and concepts from that. Yeah. Exactly. But now you could go and say to your intern, here is all that knowledge, um, process that, and now create a specific output. This is what this is what I give you as an input. This is what I expect, here's a couple of examples. Go and do that. Then even the human, um, the human equivalent would probably do a much better job than just blow up some balloons. Um, and the same is true with the AI tools that we use today. So if you don't give them a a goal that is measurable that they can work towards, and don't give them specific knowledge about what you want to do. And don't tell them it's wrong when they do it wrong. Yeah, then, um, then they're they're just here, they they're programmed to please and to make the best of it. And so, um, that would lead to a bad outcome, but if you give them the tools and the context, they will get you much better result. You still will want to work through stuff and edit it yourself to make it your own program. But to get a baseline, um, outcome, you will get much better results. So, some things sprung to my mind, some nice little wrap-up points. I don't think, you know, we we can do a little bit of a wrap-up now. I don't know how long have we've been going. The duration 300 milliseconds. I don't think that's the right number. Anyway, uh I, the the intern on on the intern concept is very powerful for me because what I found was that when we lead people, we've got to be conscious of a whole lot of things. People got to get satisfaction, they've got to, they've got to sense of achievement, we've got to design their jobs in ways that they're motivated, and people will actually do better. They will do better than than AI. However, AI is wonderful for those sort of tasks that you nobody really wants to do and keep doing them. And you don't have to worry when they first start about, about, will we return them or will they leave or you know, what do we have to do? And in the long run, human's going to be, going to be better at their job. But first time you ask him the question, AI might do a better job. Yeah. Hmm. Yeah. It's it's definitely changing how we work and um in the in the prep to this um to this video, we talked a bit about um how technology has changed in our lifetime and before our lifetime. We talked about the mechanical looms that come in and the the the the thetes yes, yes. that came in to smash them. Um, and then how how that might have changed from the great-great grandma who knew several dozen different stitches um, to to make make a fabric or make the um weave the fabric, um, and then the the her daughter might have now known how to use a manual loom, and then the the the grand granddaughter might know how to program the loom. And and how the magic, the magic of the loom working itself that the Lates saw could still be the magic of AI. Yeah, and it was and we we we talked about a story earlier where I was working with somebody who, I'm a little older than Dom, who had just, just got a computer, we used to walk around with a stiff floppy disc, you know, one of the nice hard ones, the 3.1. just after the five or three three inch disc and said the five inch disc, 3.1, I don't know why that number's important in computing. Everything seems to be 3.1. Uh, but uh we we put the we put the the spreadsheet on a disc and we marched it around all the various different departments and then we brought the data to a central location to actually assimilate it and and kept the backup at that central location and then every day we walked around and we got everybody's data. off which was which was uh yeah a crazy thing. But so much better than the reports but this one particular guy I knew I had working with me and he had no idea of computing and brand new to computer. Somebody put one in his office. That was the first time he'd seen one in real life. And they he could take a car apart, put it back together again. He knew exactly what was going wrong. He would listen to a car driving down the street said you need to do something with your taps. All that kind of thing really really good at any kind of machine. And they he couldn't work computer. And he got really tied up. Well, every time I asked him, well you just put it in and it'll do that and it'll do that, it'll do that. Yeah, but how? Yeah but how? And he had real difficulty uh understanding and letting go of that how. Bit like the lot dates. No, no, no, no, no. I can't do that. you know, that's scary and a bit like some of our what would we call it? AI today. Yeah, no. Yeah. I think we've got a lot to talk about Dom and uh maybe next time we should talk a little bit around this topic, some of the things that came out today. Maybe talk a little bit about AI and fear and job security because job security and maybe even I how are we going to build the skills for next time? Mhm. Mhm. Yeah. Whenever we don't have the intern. Whenever the intern is unpaid. Well, there's a subscription fee. But yeah, yeah. Yeah, absolutely. Um good talk. Good chat. Thank you Don. Thank you. See you all next time. Good.