Episode 1: People Over Prompts

Brian Milner (00:21.836) Welcome, welcome, welcome, one and all. This is the inaugural episode of the People Over Prompts Podcast. I have launched this new podcast and we we've launched it with the tagline that this is the place where we're going to talk about the future of teamwork in the age of AI. My name's Rupp. Brian Milner. I am coming to you off of hosting another show called the Agile Mentors Podcast that I did for years. And I am starting something new for a lot of different reasons. so let's let's start with this. I think that there's a question being asked in a lot of organizations right now about how do we add AI. To the way that we work. And I think there's a fundamental flaw in just that line of questioning, in that approach to questioning AI. I I think the the better approach that I think sometimes is getting missed right now is if we were designing work today, if we were starting from scratch and creating our system for what works best today. Knowing that AI exists and knowing that we're gonna plug AI into our process, would we design it the same way that we're doing it today? And I I think that the answer to that in a lot of different cases is just absolutely not. I think we're we're trying to see if AI can do certain things for us and fill certain gaps and holes within our process, but we're s we're not asking the the deeper questions about. If that process is even necessary. or how does it change in this new world? So that's what this show is intended to talk about. It's yes, we'll talk a little bit about technology. We'll talk about ways that teams are using this kind of technology, but it's not a latest tips podcast, there's plenty of those. Brian Milner (02:47.213) If you want to find out the latest skills for Claude or how to write a good prompt, all those kinds of things, this is probably not the the place for you. as I said, there's there's just hundreds of other podcasts that will touch on that. I'm interested in how it changes how we work. that's what this is about. It's it's about what happens to teams when AI becomes Part of the work. What what should humans still own in that workflow? What happens to judgment, trust, skill, accountabilities? Learning what happens to that in an AI world? What what changes when one person has a bench of AI agents? What changes when our team is no longer that seven to ten person grouping of humans with different skills cross-functional that work together for the same goal. What if it's not that? What if our team is two people, three people, and those two or three people are acting more as orchestrators of a team of agents. There's still coordination. There's still crosstalk. There's still dependency. There's still some of the same problems. But there are other problems that are now gone in that world. And there are new problems. And I think that's really where I'm trying to head with this is taking a fresh look from start to finish, from the moment we come up with an idea to build something. Brian Milner (04:46.862) To the moment that someone actually uses it. And examining each step along the way over the course of this podcast to try to talk with experts in their field to bring that information to you to say, here's where it is today. Because here's the truth, friends. This is still in motion. At the time of kicking off this podcast. This is not a settled question. I fully anticipate that there will be sets of practices, and there already are some practices that teams are employing to work more effectively with AI. But I think there'll be more. I think there'll be larger, more wholesale changes in how we do things. So let me frame this up a little bit for you, because if if this is your first time hearing me and you're kind of wondering what does this guy have to to say about any of this stuff, why should I listen to him? Well, I'm not an AI expert, so I I I should be clear about that. I'm not Building the latest large language model. My past is a process past. I come from the agile and scrum world. I'm a certified Scrum trainer. I've taught classes traditionally that are focused on those small teams and how those teams work best together. But I I think one of the important aspects of that is Agile, the Agile portion of that was never really about practices. It was never really about here's how to do this thing. It was more about how do we make the work transparent and visible? How do we periodically stop and inspect that work to see if it's meeting our standard? And then how do we adapt as we move forward? And those things I don't think have changed. Those things I think apply here, maybe even more so, than they have in the past. I Brian Milner (07:02.646) I'm a teacher and a coach. as I said, I train classes, but I I'm also a practicing agile coach and that I help organizations look at their entire system and try to understand where the friction is. I I'm very you know, you'll you'll learn this about me if we you haven't encountered me before, but I'm I try to stay very pragmatic about my approach to things. it's about the purpose. And if there's a purpose behind doing something, and we agree that that purpose is valid, then yes, go forth. Continue. If it's working and providing you value, then there's a reason for doing it. But the reason for doing something has never ever been because that's the way it's been done in the past. It should have always been. Do we need that purpose? Is that purpose giving us anything of value today? And if so, let's continue it. If not, let's get rid of it. Or maybe we need a new purpose now. Right? Maybe there's new problems to address. I I also am very focused on the human side of work. And that's where I think this kind of crosses over. Because The agile scrum world is very much about process and I in the in the last few years that I've been interacting with teams, I've been more and more drawn to really the small microcosm of how a a small group of human peop human beings you know work best together. How they communicate, how they collaborate. that's Not going anywhere. The size of our team might be changing. I mean, traditionally, we've looked at things as a team being sort of, you know, a group of about eight to ten people or so. Seven to ten people. Whatever. You know, Amazon famously had the two pizza team kind of paradigm. Well, I think in an AI world, it's it's pretty safe to say the two pizza team, those days are gone. Brian Milner (09:28.76) There's something new that's on the scene. And if that's true, if our teams are are not going to be those seven to ten or so people, if they're gonna be two to three people, then the process, the practices that we have been using kinda no longer apply. At least some of them. They were meant to solve problems of a team that size. Well, that paradigm is shifting. So that's what I think I bring to the table is an ability as sort of a systems thinker to look at this from the aspect of what's the entire system? And what's the role that this portion of that system plays? And does that bring us value? That's what we're trying to examine here as we go through. Now, with that setup, I I kind of want to just go through a few of the key mistakes, just a few quick hits here, that I think are big-time mistakes that are being made today in implementation of Agile, not Agile, sorry, Agile on the brain, implementation of AI, and how that's being propagated amongst our teams and in the ways that we work. The the first one is really the core of this concept of calling AI another team member. Treating AI like it is a human team member. I get it. I think part of the thing with AI in our large language models today is we've made them conversational. And that conversational nature gives us as humans the impression. That there is an intelligence, a hum a humanity, even, on the other side of that screen when there's not. There's programming. And I think what we see a lot of times is kind of this this attitude of implementing AI as if what we need to do is treat AI like another human team member. And I think that's a really false paradigm. Brian Milner (11:58.183) I think what's much more relevant is asking what what kinds of things that the AI can do. If AI is not a team member, but we we start really recognizing it as a tool, then we stop trying to build systems around AI as if it were a human. It doesn't have the same hangups. It doesn't have the same needs. So why are we designing the way we work around AI being human? It's not. Now, don't get me wrong. This is people over prompts, but it's not AI is bad. Right? This is not throw out your AI. we're very pro-AI here. And we'll always be. But it's it's not about being pro or con, it's about the right way of implementing it and and and doing it with open, clear eyes. So that's kind of the first one is the the mistake I think people are making of of treating AI like it's a human. Another one I think is handing existing parts of their process, including roles or events, over to AI. And it's sort of a similar mistake, right? It's it's saying how can we have AI do this other thing for us now? so how can AI be our tester? How can AI be the scrum master or our project manager or how can AI be our business analyst? Brian Milner (13:53.697) Again, that comes back to a little bit of that paradigm of treating it like it's human. You're taking your current system and you're saying, can I pluck out this component and replace it with some synthesis that I I've designed an AI to become? That's the wrong call. The right call is to fully clear-eyed see what AI does best. And what it struggles with, and find the right task, find the right places for this to fit in, not replace a particular person, right? Because there may not be a need for that role in this new paradigm. I so rather than asking things like can can AI write requirements or you know, if you're more agile, stories? Can can AI do our estimates for us? Can it create tests? Can it act as these roles, or can it act as a developer even? I think rather than that, that's still kind of assuming that the structure that we've built is correct for this new paradigm. And rather than asking that, I think we have to kind of look at what were the limits of humans that caused us to need those kind of systems and do they still exist in this new world? Because I think in a lot of scenarios they don't. As I said, it doesn't mean that there aren't other problems, but those are new problems. And I think that's where new practices come into play. I think the third big mistake is that we're having AI just speed up bad work. AI can make things faster, but it doesn't always make things better. It can. In fact, that's kind of there's a three-prong test I always use to try to determine whether I should use AI. Is it going to improve the quality of something I'm doing? Brian Milner (16:12.994) That's one good reason to use it. Is it gonna speed something up? Will it be able to handle this faster? And then the third kind of prong of that I think is will it make it easier to do this? And if it's not going to do one of those three things, then it may not be worth doing. It may not be worth using that tool. It just may not be the right tool for that job. But the fact that we're doing things faster does not inherently mean that they're going to be better. I talk about this when I talk to people in the product area. and and the the concept here is, you know, there's been multiple studies that have shown that there's some percentage of of things that we're building in today's world, in the product world, that aren't being used at all. you know, in software there's a famous study from the Standish group that has a lot of flaws to it, so I'm not Hanging my hat on this study on its own. But this one said that 64% of the the features in our software are rarely or never used. And I've seen others that put it closer to 49%, and then another one that I saw put it as much as 80%. So there's discrepancy in this. but I I I would even argue there that even if it's the low end of that, right? The the lowest one in our our data set here of different studies, if it's Fifty percent. That's not acceptable. Fifty percent of the things we're building no one cares about. Well, now here comes AI. And now we're doing things faster. Is that gonna change that percentage? Brian Milner (18:06.828) No, it's not gonna change that percentage. That just means we're producing more stuff, right? And the more stuff that we're producing is the same percentage of stuff no one's using. I I I've never thought the problem was the speed of the developers. I've always thought the problem has been discovery, finding what people actually want. And that doesn't change with AI. So that's the third thing is is kind of just that that speeding up doesn't mean that it's better. It just means it's more. And more does not always mean that it's gonna be better. So, what is this new platform? What is this new show going to explore? We're going to talk about what does teamwork mean when AI is part of the system now? What does a team mean? How does a team change? What should a human never delegate? What are things that we still want to keep under human control, human judgment? What things does AI do well? What does it struggle at currently? And I have to say currently, 'cause it's changing every day. How do we build trust in an AI-assisted world? How do we handle responsibility, accountability? Right? If we have AI helping everyone to do their work, trust is going to be based on whether that person verifies, whether that person owns the output, the outcome that comes from that work. Speaking of outcomes, are we putting that first? Brian Milner (19:56.269) The outcome versus output. Again, we could have a ton of output that doesn't really do anything. But it's the outcome that we should be looking at. How d how do we avoid replacing collaboration with isolated AI productivity? not just for developers, product area as well. There's a danger that I might overemphasize simulation kind of data. And not end up talking to my customers. So there's a a real danger of isolation. I I'm just I'm I'm really less interested in whether AI can write a better user story. That's just not not my focus. I I'm more interested in whether a user story is still the right format, whether it's still helpful. I mean, that format in particular was written to help. Product people. convey information to developers. But now we have a different paradigm. We're conveying information to AI. So see what I'm getting at? These formats that we've always taken for granted may not be applicable in this new world. My my big kind of point is I I don't think that the future is gonna be defined by any specific tool. That's why I'm not gonna focus on those. And that's why I'm not gonna make this podcast about the latest tip or trick that's out there. Because those change daily. And tomorrow, Anthropic or OpenAI could come out with a new model. Brian Milner (21:48.921) That has a new way of working and it has new strengths and new weaknesses. And the tips and tricks I gave you might no longer apply. So I want to take the long view here. It's not so much about whether I know the latest new AI tool or trick. But I think the future work is going to be defined by the choices that humans make around these tools. What safeguards we put into place? What process we find works best? For the time being, there's still humans in the loop. And there's different configurations of humans, but those different configurations I think are what drives us into needing new ways of understanding this work. So what does people over prompts mean? It it means humans over hype. It means judgment over. Automation. It means, as I said, outcomes over output. It means that learning is still important. And learning is is more important than shortcuts. It's about responsibility over delegation or falling through the cracks. It's about better work, not faster work. And I want underline that last one because this has always been something I've tried to promote. Quality comes before speed. Brian Milner (23:41.45) If you do low quality faster, you're not doing anyone any favors. Not your company, not your customer. I'd rather do high quality at a slower speed. And this is not, again, just have to put out this kind of warning if you're listening. This is not me saying, so that means AI is bad. No, AI can do quality. But it's up to us as the humans in that system to ensure the quality, to verify the quality. And that takes a little more time. But it's faster, it's better for everyone involved if we do it right the first time than have to keep coming back to it over and over again. So I just want to set that expectation of what this is about. It's it's more expansive. it is heading in to some new areas. We you know, I I know I I come from an agile background, it doesn't mean that that's what we're going to talk about all the time. What I'm interested in is practical. I'm interested in what works today. And I I really have no axe to grind about anything that's existed prior. If what has existed prior still works or works in a modified way, then I'm interested in it. If what we've done in the past, just like other things we've left behind, if what we've done in the past is no longer applicable, no longer provides value, I'm ready to move on. Brian Milner (25:35.603) And that's what I hope to really focus on in this this show, this podcast. I want to set the expectation that this is not about answers. don't don't think that you're gonna tune in every episode and I'm gonna give you a nice buttoned up here's here's the solution, and here's the answer to this problem. I'm I'm gonna ask more questions than provide answers. I'm gonna try to challenge assumptions. you know, in the US we talk about sacred cows. I'm gonna talk about sacred cows. I'm gonna talk about the things that we have that people feel like, well, that can't change because that's that's a given, right? That's the way we've always done things and there's value in that. Well, no, that's a assumption. And I think we have to challenge all our assumptions all over again in this. I'm gonna look at AI through a specific lens. I'm gonna look at it through people, through teams, through the systems paradigm, and in just an overall way of working. That's what I hope to do with this. So that's what I challenge you you with, as listeners, is if you're looking for a show that that is gonna give you prompts. Skills, tricks, this is likely not the place for you. but if you're looking for you know what happens to people, to teams, leadership, collaboration, judgment. All of these things in a world where AI is now core and part of the way that we work on a day to day basis, then I think you're in the right spot. Brian Milner (27:31.415) You can find out more about the show and we're going to be posting our episodes on my own website, Agility Evolved. So you can find this this podcast show notes, you know, our archive of past episodes as we grow at agilityevolve.com slash podcast. That'll always be the place that you can go and find out more information. We're gonna try to give you as as you know in-depth show notes and Transcripts and everything else that you might need for this, links to anything we talk about in each episode. That's what I hope to provide for you as we go through this journey together. So once again, this is something new. This is a podcast called People Over Prompts. And we're going to ask what happens when the future of work stops being just human, but still has to stay deeply human. So I I hope you'll join me. I hope you'll come along for the journey on this. I want to take this where you want it to go. So one of the ways you can help me with that is a couple of things. First of all, I'd love to hear from you. If this struck a chord with you, if you have things you want to say about this, if you have topics you want me to cover that you think align with this purpose, this vision for this podcast, if you have guests that you think would be really excellent. To weigh in on this discussion. I'm going to ask you to email me. My email is Brian, B-R-I-A-N, at agilityevolved.com. And just like agilityevolve.com slash podcast is where you can find the show. Brian at agilityevolve.com is how you reach me. So send me any of those things. I'd love to hear from you as listeners to the show about what you want to hear. I'm also going to make the plea that you go ahead and subscribe. Subscribe in whatever platform you have. Like the show. This is brand new. We're starting from zero. So some of you may have listened to me before on the other podcasts. Some of you may not. And we want to find people who are interested in this topic. So if you help us by subscribing and liking the podcast, you'll always get the new episodes when they drop. Brian Milner (29:59.994) And we'll maybe help some others along the way find us and join in this community that we're trying to build around this topic. So that would be a big help to us if you would do that. And then I just say buckle up. Stay tuned. We're excited. I'm excited about this. I I think this is a a really good direction to head in. And I think it's gonna open us up to a lot of. expansive topics, a lot of areas that kind of travel beyond, you know, where I've gone in the past. So buckle up, stay with us. I hope you enjoy this topic. I'm glad you joined us and gave us, you know, the the try here on our first episode. Stick with us. We've got some really good episodes coming up. I've got planned for you and I think you're really gonna enjoy them. But that'll wrap us up today and for this week. on this very first inaugural episode of the People Over Prompts podcast.