With AI, Everyone is Ironman

Speaker A: This is the Future of Work. Welcome along to another podcast from Ian and the crew on the future of Work. Let's join them now for the new episode.

Speaker B: Well, good morning, good afternoon, good evening, Good grief. It's another podcast from the Future of Work. Uh, I'm joined today by Eric. Uh, how are you, Eric? How's Seattle? Is it as hot as it is?

Speaker C: It is not, which I'm very grateful for, Ian. Actually, it was pretty chilly yesterday and rainy in the morning. Um, but, you know, summer. That's how it is oftentimes in June in Seattle, we call it January. Um, so I'm grateful that it's not blazing hot like, uh, England and Europe right now. So, yeah, can't complain.

Speaker B: It's really hot and humid and England was not designed. The cities and the urban spaces are not designed for hot weather. They're just not. I mean, I could be in Barcelona at these temperatures and it'd be fine. They've got cool breezes, they've got lots of trees everywhere to shade you. Um, England is just not designed like that. It's designed for the heat to stay in the cities because it used to be very cold. So not a great place. Meanwhile, we're recording this middle of, um, in the middle of the FIFA World cup that's happening in America and Canada.

Speaker C: Yes, that's very exciting. I am definitely following that. So we'll see how, uh, how, uh, England does now that the knockout rounds are starting today.

Speaker B: Yes, well, I hope they get better because they're not brilliant at the moment, but there we are. That's it. So great to see you. Great to chat. Um, quick few shout outs. Lots of people have been saying how come now podcast for a while. I have been busy in Africa. You've been busy as well. But we want to do get some more going. Quick, uh, few shout outs to Tim and the team at Christians Against Poverty. Uh, thanks for all your encouragement. We finished a big course with them this week. They were nice. Uh, Chris, uh, Chris d', Amato, who may well join us. Um, um, he's in, uh, Washington and wanted to join us. Uh, uh, Mike as well, and Steve. So, um, what we want to talk about today, it's a little bit to do with, you know, would anyone be surprised to hear we're going to talk about AI? Nobody. No, nobody at all. Someone, uh, said to me the other day, AI is the new Agile. And there's a reason why people are saying that, by the way. And it's, it's because what Agile was really about was how to get things done faster and better and get market quicker. And I think sort of AI has taken over that sort of slight agenda, if you sort of mean. So I thought we'd talk about that today, Eric, if that's okay.

Speaker C: Yeah, that sounds good. And I actually like how you've um, phrased what people mean about AI. AI is the new Agile. Because you know, one of my pet peeves doing Agile coaching and senior Scrum mastering for so long now, like 14 years, is that people love to say that they're agile but they don't really know what that means. So in a similar.

Speaker B: Now they're saying that they're AI, but they don't know what that means either.

Speaker C: Uh, exactly. That is exactly what I was going to say. So like people say they're. And I'm a bit cautious about this because, you know, my first question to you is, what do you think the consequences of leadership? Just telling everyone to quote, use AI and then not have much direction with that. It feels like, like, you know, in the Minions movie, it's just a bunch of people running around bumping into each other, trying to figure out the best way.

Speaker B: Well, first of all, if you're watching this on the video system, you will find that there's a dog in my scene and there's a cat in Eric's. That's very much how we live. So, yeah, um, what are the consequences? Well, in the past they used to senior leaders, C suite execs would go, we need to be faster, we need to get to our market quicker. We need to understand all this chaos, all this VUCA world. The answer's agile. Now they're saying, oh, the answer's AI, how do we get to AI? And the one thing AI is saying as well as everything Agile says, in my opinion, my humble opinion is AI saying and it's cheaper. Not only is it faster, but it's cheaper. If you think about what the fundamental understanding is that's going in the market. It used to be, uh, you know, to get a job done you needed eight teams. Then it became to get a job done you need just five agile teams. Uh, do it because they're efficient and they know what they're doing and they get into the right things first and you know, they're focused and all the process stuff is there. Now what, what's being said is to get the job done, you need, you still need five teams, but now those teams, there's one human and four or five agents doing the job that was being done by the team. And I'm not sure that's actually true. I was listening to a call with Nick Singel, who's an American guy, and he said he had a wonderful presentation of this that was just showing all these big trends we've had in technology since 1945. Every single one of them was, this will be the end of humans. And they never were. It was always an expansion and growth and extra things. So we'll leave that aside. So I, I think so all CTOs or all CEOs of any kind are going, oh, must do, must. If I'm not saying AI, uh, I'm going to lose my job. I better start saying AI. But there's a few things that you have to put in place to get this to work. You really do need to understand and think about the entire ecosystem of what's happening in companies. So I'm talking about the architecture, the processes and the people. And all of that still has to be thought through. When you do AI, it isn't just everyone in the company now has access to Claude or Claude cowork or, uh, access to ChatGPT or Rovo or whatever you're using.

Speaker C: Yeah.

Speaker B: Uh, now there isn't anything wrong with giving people access, but that is really just like saying to a, uh, young kid, here's a bike. You'll get around faster on a bike than walking. Here's a bike. Off you go. Without structure, without process, without some training, uh, some will succeed, but a lot won't. And I think that's the problem. So, uh, I guess the first thing I should say about leadership is, and I'm saying this all the time at the moment to leaders. And that's what I do now for a living. I'm not AI. Enablement is what I'm doing all the time now, wherever I am. I think you've got to. The first thing you got to do before you start using AI is set up a really good AI governance body. And, uh, that body is made up of senior people, uh, policy, legal compliance, cybersecurity for the company, how to use it. Well, put a framework around that correctly, get that in place, get everyone to sign it. They have classic stuff in like, I don't know, do not let the AI system look at your emails.

Speaker C: Yeah, exactly.

Speaker B: Because it, ah, can, it can do all those kind of things. So I think the first thing is to get a really good governance body. And the problem is a lot of companies are throwing the problem of AI to tech people.

Speaker C: Yeah.

Speaker B: Oh, this guy's a brain box. We'll let him do the AI enablement across our company. And it's seen as, it's just like Agile was seen as coming out of the engineering space. It's the same thing. Oh, AI is coming out of the engineering space. We'll let them organize it. No, no, no. What you need is an across the company governing body that says this is how we want to use it and uh, particularly this is how we want to keep ourselves safe from abuse.

Speaker C: M. Yes, and that is actually a good point. I was talking to one of the senior leaders at the company I'm at, uh, like two or three months ago about A.I. of course he was out visiting from back east and in Seattle and he said it's like everybody has an Iron man suit on right now. So he's really so, you know, like using a. Is like every. But then I, I mentioned that to someone and I was, and I thought, okay, I don't know about that. I'm like, sure, you can be really powerful. But then another, uh, an architect that I work with clarified that more and said that, yeah, but you don't know if you're going to level a building. It's like you could put on the Iron man suit, but how do you use this super powerful tool that you've just been given if you're just like, say good luck young lad. Lad or lass, have, have fun with this thing, it could really be potentially literally destructive for your company.

Speaker B: Uh, and in reality if you say, if you take like two companies and one goes, oh, we must be AI everywhere to be that competitor. Well, if the other companies go, we must buy everywhere by AI everywhere to be that competitor. All you've really got in your analogy is a bunch of people in Iron man suits.

Speaker C: Uh, right.

Speaker B: In two different companies still competing, but now they can compete faster and do more damage. I'm not, I'm not trying to be negative about AI by the way. I just want us to understand what it's meant be doing for us and what it is doing for us.

Speaker C: That is the exact point that I've been looking at as I'm watching the company I. And working with the company I'm with ONBOARDED now they are going to slow, um, and being cautious because they're just, they're in the financial space which you want them to be. Um, but it's interesting now they're starting to bump into things like uh, you know, this problem is coming out of the engineering or this tool is coming out of the engineering space. But I think your point about you need across the board adoption, uh, to make sure that it's just not a bunch of engineers figuring it out. I like that point because it's, it's so expansive and all encompassing. But it's, you know, I'm seeing them question about the cost of it now, for example, like, if everybody's like, how efficiently are you using the AI? So you're not burning through all the tokens that you need to buy to use this platform.

Speaker B: Well, I mean, right now I was reading some stuff about the court cases going on in America because AI is America and a little bit of China, but mainly it's America. Uh, every one of the big, um, AI, uh, labels is being taken to court over its policies and over its. So classic. One here is Claude is being taken to court on a class, uh, action suit on. What does 20 times faster mean if you buy the 20 times faster subscription? So loads of that's going on as well. We're trying to understand what it can do. I mean, it's powerful stuff. There's no doubt about that. Our, uh, friend Ricardo that we know well, introduced me to Claude, uh, introduced me chat GPT before it was even public. I was already, uh. So it's been around. We know what we've been doing with it. But what if you don't get the governance right? It's not safe, but the government's. It's designed to give you something else as well, which is the answer to the question of what, why, why, why does it help us with our business? So, for example, one of the companies I'm working with, I said, yes, native AI everywhere. But everyone's doing that over the next two years. What's your unique selling point afterwards? What is it afterwards that you're unique at that will keep you in business? Please. Because what won't keep you in business is going AI. Because everyone's doing it. Everyone's doing it. In the classic. The saying is, in the gold rush, California gold rush, the people who made the money were the people with the shovels. And then.

Speaker C: Yeah, I was just talking to my dad about that the other day. The shovels and ropes.

Speaker B: Yeah, shovels, um, and ropes.

Speaker C: Yeah, yeah, so.

Speaker B: So it's really exactly about that, I think. Sorry, go on, Eric.

Speaker C: No, no, that's good, I think. Yeah, keep going. Because I want to talk about this why a lot. Because I've been thinking about this a lot lately. It's like you want us to build, use AI, and you want us to do all these things. But why, I think that gets down to the heart of what a coach is. One of the things that the coach is good at is asking those questions and helping people take a step back and seeing why the heck they're even building something in the first place. Because it can get so diluted as to like a technical ask in. It can be so hard for the teams that are building it to see the whys of why they're asking them to build a certain tool that they're working with. Um, and when that communication is not clear, like, how does this tie into your okrs and your roadmaps, Things go awry and you end up building stuff that's not needed or take too long. And AI is the same thing.

Speaker B: Well, I found that personally, I mean, um, I have built. Because I finally could. I built several products myself for me, uh, for business. A, uh, lot of the I built training thing that I use for training. I've built an AI assistant. I, uh, built a media assistant. What I've realized having done this is just because I could build more and more features into it, because AI could let me. Didn't mean I should have.

Speaker C: Right.

Speaker B: What I've actually done is I've confused a couple of my products with what they should be. Classic, absolutely classic product owner stuff that you ought to understand. But what's happened is because AI has been involved, the feedback loops are faster. So instead of me taking three months to find, I've gone a bit AWOL with my thinking I get back in three days or three hours. Um, I get back what I've. So I've gone a bit fuzzy on one of my apps. And it's the same problem. It's always the same problem, which is because you can go faster and the market wants you to go faster, and your businesses and your customers want you to go faster. You go, okay, let's go faster. But you've got to know where, why, and where you're going. My analogy of the bike, for example. I, uh, uh, used to go in the park with my two kids when they're quite small. I mean, they're in their late 20s now, but they go in the park. We'd cycle slowly into the park. Yeah. And then we get in the park and they both whiz off in the bikes. Super f. Neither of them check where I was going, where I wanted to go to the park. And after about a minute I'd call them back and say, hey, Josh, you've gone the wrong way. Come back. And of course they'd whiz back just as fast as they whizzed away. But, uh, that doesn't mean they got anywhere useful, if that makes sense.

Speaker C: It does make sense and that's why AI is definitely at that stage right now. I like what you said about we need to take a classic product ownership approach. And for me, the company I'm working with right now, they didn't hire product owner. So uh, as soon as I came in I'm like, this is, this is a huge gap. Like you've got the executives wanting to do something and then you have the tech side, but you don't have anybody that's shepherding the product owner mindset. And we're seeing that come back to haunt us more and more with disorganized backlogs and no connection between what the executives want to do and the timing they're promising people and the teams that are actually executing it. And then you throw in AI in the mix and, and it makes things, you know, it speeds it up and makes it even the mistakes even faster. But it's, it's really frustrating. You need to have that, I think you need to have that five whys, that basic five whys approach. You know why you're doing this? Okay, why are you doing it? And just keep asking each other that.

Speaker B: I mean you're bringing out a point that I want to make to anyone in our audience, which is, you know, agile coaches, do they still exist? Um, my answer to that is yes. But now I think what companies want is utility coaches, coaches who can advise and exploit and create guidance for the use of AI, the use of product, the use of Agile, or all of them together and delivery. Because I still think there's a sort of a market, sort of almost whisper going on that um, the agile coach is divided into a bunch who just tell you what you should know and a bunch who can help you get on with it. So for example, my uh, my byline on my emails now is I use AI, Lean Product and Agile to get stuff done and to help others get stuff done. That's what I say I am. And uh, you know, I'm, I'm still here. I hear of a lot of people I think have really good understandings of agile who can't get jobs, want to become a postman, for example. A lot of that going on. So uh, before we carry on with AI, I do want to make this point which is, yeah, that's good. What we need to be as a community is multi purpose. What does the company need? Not what can I give it, but what does the company need? And have I got that in me to come across and do that? So particularly the higher levels, the C suite level, you need to be got, have done some C suite work, but you've got to be on top of these things. So, uh, a classic example of this would have been a couple of weeks ago, my company that I'm working. Someone out of blue rang me up and said, I've got this idea. I said, great, why are you ringing me? And he went, well, you're the, you're the AI guy, aren't you? You know how to deliver these things into the company. And I thought, well, good that I've got that reputation now. Not just about Agile, it's about all. So general advice, but let's go back to the topic of Agile. Uh, AI. Sorry, forgive me, my pen's just.

Speaker C: No, that's good. I liked, I'm glad that we asked that because that, I mean you basically answered the question I had is like, for Advil coaches and senior Scrum Masters, how do we need to rebrand ourselves? And that. You've done this, Ian. And so it's not that you're totally, you're jettisoning, jettisoning your AI or your uh, Agile and coaching backgrounds, you need that probably more than ever actually. And, but you're just, you're expanding into all the other tools to get stuff done. You're just, it's just part of the toolkit.

Speaker B: I would put it like this. To be a good coach, you need to be good at coaching. And I'll leave what that means for the moment to another podcast. But you need to have subject matter expertise in what you're talking about. So if all your subject matter is in Agile and nobody wants to talk Agile today, you haven't got much you can coach in reality. If, on the other hand, you've taken the time to make sure you get the training you need, investing in yourself, not just in coaching, but in how AI works. I mean, you know, there's a ton of free AI courses. You can get every AI company anthropic. You can go, right? Yeah, I've got a friend, um, you can just get them free. You can also get lots and lots of courses where you're taught how to do it really, really well. Um, there's a bunch of people in my work, senior manager who went on, they, they each paid about four grand to pri. Individually pay to go on a course about how to use Claude to create agentic AI. And uh, if I'm, if I'm Honest, I've seen the course content. It's not, it's not worth that amount of money, I don't think at all. But, you know, so one of the things I'm doing, for example, is I. I'm. I'm. Now, my, my business company now certifies people for lean portfolio management and AI. So if you come to me and take a course from me, I can certify you in AI. Now, do you need a certification? I'll go back to what I've always said about certifications, which is, it's good because the stuff you learn is the good stuff. It's designed by experts to say, this is what you really need to know in this area. You know. Yeah, Imagine I was a footballer and someone said to me, you go, footballer. I said, I'm fantastic at football, thank you very much. And then, uh, they said to me, how good is your left foot? And I went, oh, I need my left foot to work as well. Uh, nobody told me that. I've just got my right. So what certification gives you is this industry sweep of, ah, what's really worth knowing. Which is better than a cowboy saying to you, oh, I know what AI is. Come on my course, because I'm brilliant at it and they're not, they're just not. So. But I still say to every coach, learn the other. So, uh, you know, whilst I did agile and then learned to coach using agile, I then learned how to do lean using agile and how to do business transformations. Coaching business transformations. I then spent time, effort, money, learning how to do leadership Circle profile or Belbin teams, which are all ways of doing really strong leadership agendas, subject matter, expertise. And now AI. I've done the same thing with AI spent, you know, I spent multiple thousands training so that I, um. So that when this guy rings me and says, well, you're the AI guy, I can go, yes, I am. I do know it, thank you very much. And that will be the move. Now, going back to AI, though, the first thing we said was, you know, get your board right, get this governing body right, make sure you know it. And then the next thing that really needs to go on in companies, you need to give lots and lots of people training, go to training, have training camps, get them to know. It's a bit like my story of the bike. Don't just give them a bike, put them on a training course. When I asked my dad when I was 16 if I could have a motorbike, he said, well, you've got the money. He said, But I'll buy you the bike if before you use it, you'll go on the AA's training course for, uh, safe biking on a motorbike, you know, so before I ever drove my bike on the road, which I could do literally as soon as I bought it, the licensing system in England was terrible in those days. Before I even could do that, I'd gone on eight weeks of training on how to drive safely. And of course I've never had a bike accident. So the point I want to m make about that is just giving people access to Claude. And Claude is one of many, I could name many. And people will tell you, this is so good, you don't need any training. I'm, um, sorry. Bullshit. Everything.

Speaker C: That's exactly what I'm seeing happening. Or here's a. Here's a port, here's a portal. Look at it.

Speaker B: Everything needs training. Everything needs training. You need to invest in yourself, train yourself to know what's the difference between good and bad. Whatever the subject is, it's just not true. So camps, training camps. So literally, you know, buy a day's course on how to use Claude brilliantly, look for a good one. If anyone is on the podcast and wants to know a good one, ask me, I'll reference you. The really, really top ones on using Claude, on using, uh, um, chatgpt, on cowork, on, uh, cursor, on any of them, what the really good courses are, because you don't want to. If you're going to invest a day, don't invest a day to get average, Invest a day to get really good. Um, and then I would say I have some AI labs which are part of innovation, which is, let's try and do this in an AI way now, how can we learn to do this? So those are the key things. But then what's happening, I think. And now I'm going to ask you to just ask me lots of questions, Eric. I'll finish with this because it's in my brain to dump to you what's actually happening in the market is everywhere is piloting, but nobody is driving it to good production. Everyone trying things out. We're all doing, I mean, literally, I was on a call on Friday with a, um, um, uh, for a company that's, um, got like a center of excellence for people learning, uh, to do a certain thing. And they're all learning and they're all trying things out and, you know, there's probably 90 of them all trying to learn the same thing. Um, and they're Just playing about and it's exciting, it's interesting, it's shiny. But my question all the time is how does that get to production? The classic in this is, here's a classic. Have you heard of gxp? GXP means. Yeah, so gxp. For anyone listening who doesn't know it, that means M. You've got to be able to show you've followed all of the business standards and industry standards on how you do things and particularly in some areas like finance, healthcare, a few others. It's man, you do this. Imagine you're putting a software to live and you've got to create all your GXP documentation and part of it was done with AI and you don't even have an audit. I mean AI done well is like code, it needs auditing, it needs literally, uh, that. One of the things we're doing where I am now is every piece of Claude skill. It's like a code is audited, it's put in a cmd database, it's GitHub, so we know exactly what versions used. So if someone says to us in five years time, that piece of software, how did that come about? We can go, well, this skill was used in part of the requirement gathering. Here's the skill, here's literally the skill we used. It's GitHub version control, it's all that. And so I mentioned the gold rush earlier and the sort of idea for a reason, which is at the moment we're very much in the wild west still of um, we're trying to.

Speaker C: I'm glad. I think this is a good place to finish for today, Ian. I mean, uh, we could keep talking about this for hours, I'm sure, but this is uh, this is really great. I like how, you know, the emphasis on training right now. We've been talking about this for a while and I know and I saw you in the early days when you were ON beta for ChatGPT and you were just playing around with it. There was like no direction. But that mind that's is still what's happening, but it's just happening and mass. It's not just a few niche people that were lucky enough to get or and curious enough to be part of this beta. Now it's just like everybody's doing it and it's really, it's really frustrating. So asking I think that question, how does that get you to production? Is a really excellent way to do that. It's one of the things that I've personally been doing, um, where I'M working right now and like I've set up what I call an AI Tiger team is it might just to see what we're doing but having that training, I think locking into that and oftentimes you need to do that on your own. Like this is outside of your uh, day to day work chaos. You just have to, you have to seek it out on your own. Find these courses, get certified like most of us for the ALGE coaches and the senior scrum masters on the call. Just like what you did with your agile coaching certifications, your Lean certifications, whatever. Right. This is no different.

Speaker B: So 100% mate. So yeah, thank you for reminding me. 26. I could talk about this all day. Maybe what we need to do Eric is pick some of these themes that we've briefly touched and deep dive in them and talk some more on each of them.

Speaker C: Well, I think the training is a good one. When I'm looking at AI, I often think of Occam's William of Occam and Occam's razor. Right? Like what is the Occam's razor approach here? Keep it simple because it's quickly getting weirdly complicated like throwing that when you're throwing a on top, on top of the later and people are forgetting like basic tenants with lean and agile about trying to keep things simple and putting the guidelines those guide rails still need to be placed. You're still driving down a road, you still need a center line in the road. You still need old guide rails. Right. Just because you know. So.

Speaker B: Okay, let's get to the end of this episode. It's great to speak again. So I'm going to ask me a question and I'm going to ask you. So question to me is what's the most important? What am I saying? I'm seeing two things. One, I'd advise anyone get your AI governance body in place in your company. If there isn't one petition for it, argue for it, push it up. If you're not listened to, you know, reach out to me. I'll. I'll write some guidance article for you to send to your company. Number two, individually, get yourself trained. Get yourself trained. So you where you want to be is what you know I want to be. Which is when someone thinks I've got a problem and I know AI uh will solve it. Who's the guy who I should talk to? Ian's the guy and you want that self now it doesn't mean there are other people who can do it. In my company there's Loads of brains in my company. Unbelievable. But I don't want to be left behind and I want to adapt myself to what's needed for the next 10 years and find the right training. Why did IC Agile make all its progress and work it did in the last 10 years? And it was because they worked out. Not that people needed training, but they needed the right training. And so they got lots of industry experts to help them understand what the best training should be, and then they push that out. So you know that that's why, um, the people who do Safe Safe is declined. Uh, IC Agile hasn't declined because there was a right level. I'm not trying to make a political statement about either of those, by the way. I'm just saying find the right training. You can start with a LinkedIn Easy Course on whatever tool you want, or general AI, you can find those, but then you want to go further into good training. So that's my two main points for the day, Eric. So what's hit you today then? What's what's worth.

Speaker C: I mean, those two points are really important and, uh, the thing that I've been thinking about, like, for the rest of this year, I keep telling my friends and family I feel like I'm in school again. Right. I really do. Like, I knew this was coming tonight and I, you know, we've been talking about it for a while now, probably literally a couple years now we've been talking about this, but now that it's really ramped up, it's, you, uh, know, I feel like I'm in school again. And so take that mindset. I would say just like put yourself in a student's mindset. And I think your two points are excellent to end on. Like, get your AI governance body in place if you don't have one already, or at least familiarize yourself with what they're trying to do. But I think even more importantly is the second point you said is get yourself trained and get the right training. So start with those free YouTube ones, start playing around. Don't be afraid to get a Claude subscription or whatever you, a ChatGPT subscription, whatever you want to do and play with it. Um, but then seek out the good training. So, you know, for those of you who, uh, heard Ian just a minute ago say, reach out to him for the right training, do that. He will send that to you. So I think that is, that's the right, that's, that's where I, I feel, I feel more optimistic at the end of this talk than I did at the beginning of it.

Speaker B: So, uh, thank you. Well, let me finish with just one phrase to anyone who's listening, which is in a year's time, your ability to be in control of what you decide to do with yourself is utterly down to how much you invest now, this year, while you can, while you have the space into these things. You can't turn up in January 2027 and go, Ah, uh, now I need to know AI. Silly you. If that's what you do, what you need to do is take your moments now to do it, get some training in now, become, uh, a lifelong learner. Now we are all going back to school and it's fast and uh, but it's doable. I think it's really, really doable. Eric, great to listen, great to chat. Nice, uh, to see the cat. I hope if you've got a video, you'll see this is, ah, the garden. I'm in the garden because it's too hot to be in my office at the moment. Um, hope we get together next week. It'd be good. Um, yeah, it would be good. Thanks, Eric. Bless you.

Speaker C: Yeah, see you in.

Speaker A: That's it for this week. Join us next time for more insight on the future of work. There is also a linktree site which is at linktree. Ian Banner. If you like this podcast, please like subscribe, follow and tell your friends. Send them a link. It's for free.

Speaker B: Sam.