Embracing AI in Creative Processes

In this episode, Brian Milner and Lance Dacy dive into the evolving world of software development, exploring how AI and automation are reshaping the landscape. They discuss the essential skills developers need in this new era, from embracing AI as a tool to mastering emotional intelligence and continuous learning.

Overview

Brian and Lance discuss the transformative impact AI and automation are having on the software industry. They explore the importance of adaptability, continuous learning, and cross-functional expertise, emphasizing how developers can thrive by embracing AI as a tool rather than a threat.

The conversation highlights the growing need for soft skills like emotional intelligence, curiosity, and collaborative leadership, and encourages developers to be open to new technologies and ways of working to stay competitive in the ever-evolving tech landscape.

References and resources mentioned in the show:

Lance Dacy
Big Agile
“Be curious, not judgemental” – Walt Whitman
#54: Unlocking Agile’s Power in the World of Data Science with Lance Dacy
#63: The Interplay Between Data Science and Agile with Lance Dacy
#82: The Intersection of AI and Agile with Emilia Breton
#99: AI & Agile Learning with Hunter Hillegas
Accurate Agile Planning
Mountain Goat Software Certified Scrum and Agile Training Schedule
Certified ScrumMaster® Training and Scrum Certification
Certified Scrum Product Owner® Training
Advanced Certified Scrum Product Owner®
Advanced Certified ScrumMaster®
Join the Agile Mentors Community
Subscribe to the Agile Mentors Podcast

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This episode’s presenters are:

Brian Milner is SVP of coaching and training at Mountain Goat Software. He's passionate about making a difference in people's day-to-day work, influenced by his own experience of transitioning to Scrum and seeing improvements in work/life balance, honesty, respect, and the quality of work.

Lance Dacy is a Certified Scrum Trainer®, Certified Scrum Professional®, Certified ScrumMaster®, and Certified Scrum Product Owner®. Lance brings a great personality and servant's heart to his workshops. He loves seeing people walk away with tangible and practical things they can do with their teams straight away.

Auto-generated Transcript:

Brian (00:00)
Welcome in Agile Mentors. How's your week going? I hope everyone's week is going well. Yeah, I'm switching things up. I'm not saying things exactly as I did the past 100 episodes. But welcome in. I hope you guys are having a great week. We are back with you here at the Agile Mentors Podcast. And I have one of our favorites back with us. I have one of our repeat visitors, Lance Dacys with us. Welcome back, Lance.

Lance Dacy (00:28)
Thank you, Brian. Great to be here.

Brian (00:30)
Always excited to have Lance with us because we always have such great conversations. And I wanted to have Lance back because we were talking about something recently that I think might be a good topic for us, might be on a lot of people's minds. And that is really kind of getting into this, what we've loosely termed the new age of development. With the new tools and new kind of the way that AI has worked its way into things and automation. How is this going to change and affect our teams? How is it going to change and affect how we develop? How is it going to change and affect the software industry? Lance, I know you had some thoughts on this. I'm going to just open the floor for you and let you take it from there.

Lance Dacy (01:15)
That's great, Brian. My heart is always with organizations and developers, just trying to help people get better. You and I shared that vision that I remember a long time ago, even at DFW Scrum, one of our vision statements was just trying to help you to do better today than you did yesterday. It's like, what are the things that we can help teams and organizations? And something's real heavy on my mind lately as I work with these teams. You know, we have these notions out there like Agile is dead and, you know, where is Agile headed? And that's not really what this is about here because I think what's happening, as a lot of people have already said, it's just become more of the mainstream. Let's quit labeling it. You know, like Mike always tells us, object -oriented programming won. We don't really call it that anymore. Objects won and off we went. So I'm not really focused so much on the agile type scenario, but we do work in Scrum and agile teams and I see plenty of organizations that need help with that. And I still encounter to this day, developers who are lagging behind on their skills, right? We get so focused in the day -to -day feature development of our roadmap and things like that. that I just fear that developers aren't setting enough time aside or not challenging the organization to help them do that, to learn new skills. And I started compiling this list of like, if I go in and start teaching teams how to do scrum and how to manage your backlog and how to do that, it doesn't matter if they don't have the skills because everything we talk about in Agile is based on reducing waste and the more of these skills gaps that we have. then I find the more handoffs and the more bottlenecks and you know that's one of the eight waste, you know, of lean. And so that's what I wanted to talk about today. And I love the topic like the new age of development. I'm not going to sit here in a spouse to claim to say, here's all the skills you're going to need. But as you and I work, I think we can find plenty of examples to help guide some of these people, even Scrum Masters that are coaching teams or agile coaches, you know, just kind of put some thoughts in their mind about. know, these skills and I have about a short list of five that I've seen growing and then thought we'd go from there.

Brian (03:30)
That sounds great. I want to dive into one that I know is on your list and it's one we kind of talked about here beforehand, but that is kind of how AI is affecting teams and the skills needed to be relevant with that. Now, I want to preface this by just saying my own personal opinion here on this. I'm not a doom and gloom person when it comes to AI. don't really see it much different than...

Lance Dacy (03:34)
Thank So, I'll see you.

Brian (03:59)
how automation really changed things like testing. When automation entered the testing realm, we didn't lose all our testers. We still needed testing. It just was a tool that enhanced the way we did testing. And I think AI is sort of going to be that for how we program. don't think we're at a place where, or I don't know, things could change quickly, obviously, but I don't feel like we're within 10 years. of it completely replacing developers. I think we're still going to need to have expertise. We're still going to need to have that guidance. Maybe 10 years is too big of a window. don't know. Maybe five years? I don't know.

Lance Dacy (04:42)
These days you don't know. I just thought yesterday something changed. No, I'm just kidding.

Brian (04:46)
Right, right. But I don't see that happening in the near term window for sure, just because it does a lot of things well, but it doesn't create. It can do things based on what's already been done, but it can't really then go through and create something entirely new itself. So I think you still need human beings for that component of it.

Lance Dacy (05:04)
Done.

Brian (05:15)
And I think for developers, learning how to integrate that kind of tool set to help you reduce your errors, define bugs, AI is great at looking over a huge chunk of your code and finding potential issues that you can go back and look at. That can save you enormous amounts of time. So I think there's skill involved there for for the developers segment that I think is embracing it rather than kind of holding it at arm's length and saying, that's the enemy, that's gonna somehow replace me. No, think of it like automation. It's not to replace you, it's just another tool to enhance and give you time to do other things.

Lance Dacy (06:02)
I think, you know, you mentioned, don't think you and I either would be convicted of being doom and gloom people. think we're pretty well optimistic, right? It is scary. mean, obviously these things that are changing, you're like, my gosh, I have to, the main word I keep thinking about is adaptability. You know, I've got four kids. I keep telling them the best skill they can do is learn how to learn, you know, and I think you just used a perfect example in development about test automation.

Brian (06:10)
Yeah.

Lance Dacy (06:30)
We weren't scared of that. The testers might have been because they're like, well, what do I do now? Well, you got to go learn a new skill, right? But it freed us up. Can you imagine still doing, there's companies out there that still do manual testing, and they have to wait until all the changes are in until they do testing, and you will never compete. in a good hyper competitive marketplace doing things like this. So the test automation freed us up and actually what I used to tell my teams is it gives you more confidence, right? So developers can make more radical changes in the code without feeling like, know, you. You blow on something and then it breaks. know, y 'all ever seen code like that before? And it's like, I think it builds their confidence that test automation helped them to be more efficient and more productive because they can experiment more. think that's the goal is I write this code and I can quickly test to see what happens. And I start building my confidence and I can make more radical changes to the system instead of tiptoeing or walking on eggshells. So I'll date myself a little bit. Your example is probably much better than mine. But can you believe I don't use a Maps Go anymore? Y 'all remember the days of trying to navigate a street address with a Maps Go or a real map? I mean, I'm kind of at that bridge where we started having online maps, but you still had to know where you're going and print it out before you left and then take it in your car. You're still trying to read it as you're driving. I mean, who does that anymore, right? So I get in my car these days and now I don't even have to plug CarPlay or Android or whatever you have. It's wireless. You just get in and I'm now a co -pilot in my car. And we kind of laughed about that. think the last episode we're on and I can just drive around in it. I just do what it tells me to do. But it'll never replace my experience, my opinions, and my knowledge of the world. So I can.

Brian (08:05)
Right.

Lance Dacy (08:20)
you know, sidestep any suggestions it has, but it helps me be more productive. It knows where traffic is. I don't know that. You know, I know the city I live in and I know five different ways to get somewhere, but I don't know if there's a road closed or anything like that. So I feel like with developers, we need to start embracing some of these tools to help you be more confident, help you. mean, goal of agility, right, is to go faster, go faster than our competitors. So I feel like that's the premise of what we're trying to accomplish here is optimism with these tools. AI is just one of them. But we all have that in our day -to -day lives. test automation is good. I've got the driving. What's another one you got, Brian, that's made you more efficient with AI?

Brian (09:01)
Well, just before we move on, one thing I wanted to kind of throw out there because I heard this example recently for AI and I thought this was a kind of a really good practical example. If you've been a developer for any amount of time or if you've ever developed in the past, you've unlikely encountered a situation where you've had to go into somebody else's code. And when you do that and you have to enter, especially if it's like a rat's nest of code that you can't really make it out, it's been there for a long time. and it's fragile, no one wants to delve into it. Well, I read this article from a guy who basically had used this legacy code base and entered into AI and had AI go through and comment and help them learn what the different sections of the code did and how it was structured and organized. And it just saved them an enormous amount of time in trying to understand what had come before. Because you know, Like I said, we've all entered those places where we've had to come in behind someone else that is no longer there and try to figure out where we get started, even if it's not code, right? Even if it's something else, but we've all had to come behind someone else. And if we can take a folder full of documents, feed it into AI and then say, help me understand blah, blah, blah. Yeah, summarize this. Help me understand where would I go for this? That's just an enormous time saver. And that's what I think is really great about it is

Lance Dacy (10:17)
you summarize this.

Brian (10:27)
So as far as skills are concerned, think prompt engineering is a good one. think coding, interacting with code with an AI agent so that you can create your own AI agents so that you can programmatically call that information. If you're a coder and you can do that, man, to me it's like it just exploded. And now the possibilities are endless of what you can do with that kind of stuff.

Lance Dacy (10:57)
just dated myself with Cliff Notes too, right? Just think of it like on the fly Cliff Notes. And I heard Alastair Coburn, one of the thought leaders in our industry, been around for a very long time trying to help humans and machines interact better. And he kind of summarized really well about what it's doing in his life is saving him keystrokes.

Brian (11:03)
Right!

Lance Dacy (11:19)
And that's kind of like what I wanted to focus on with developers. Can you imagine if you got to spend more time being creative and less time writing on a keyboard to the computer, like you just talk to it. I'm getting to the point now, I used to text all the time and I used to laugh at people that hold the phone up to their voice and they talk into it. I fat finger things and misspelled things so much, all I do is just talk into it anymore. So I feel like coding, that's what it's, you're not even going to tell it the code to write. You're going to have to be... more problem solving design engineer, you less code writing, more problem solving and understanding the domain in which you're trying to automate and algorithm design and ethical considerations that go along with that. But the computer won't be able to do that, but it'll save you keystrokes. It'll save you time. And I think Alistair summed that up pretty good that way.

Brian (12:07)
Yeah, it's architecture, right? We have to be better architects at what it is we're trying to develop. that way we can give the rough architecture and let AI do the dirty work of the small details to fill in.

Lance Dacy (12:21)
Well, you mentioned something too about boundaries, right? So AI has to operate within boundaries of what you feed it to learn off of. It's very, I'm not going to say never always really, that's a hard thing to say these days, but it's going to be very surprising if AI can just generate new ideas. It'll probably generate new ideas, but from what? I was working with a client yesterday that comes from more of the manufacturing world and he's really struggling with leadership agility. Like how do I lead and build a culture in a world for people who do the kind of work that we normally focus on with software engineering and development? He said he's a mechanical engineer and I kept using the word knowledge work, right? So the people who do our kind of work, the reason it's so complex, risky, uncertain, unpredictable and all those things is because it's kind of like knowledge and critical thinking and creative work. And he goes, but how is that different? I'm a mechanical engineer. How does that differ from software engineer? And I said, you know, it's a really good point. It's nothing about who's smarter than who, right? So I'm not trying to put anybody down on that. But in the world of mechanical engineering, you are bound by physics. are like you work in the space industry. Yeah, you're doing some cool things and you got to come up with new ways of doing things, but you still have to operate with. physics and astrophysics within those boundaries that we know about with space. But in software, and I sit down and start writing something, there's no boundaries. Like I can use any technology I want, can come up with any, I'm limited by my own skills and abilities. So why not let AI go help me get ideas? I'm not saying you got to write it all for you, because hey, I told one of the AI tools to write me an e -commerce site in Ruby on Rails. and it gave me all the scaffolding and if I would have taken that and start putting it in, then I can start elaborate. But how much time does that save me? How am gonna construct the file? So it kind of handles that architecture, but then I gotta put my critical thinking on it. I just feel like it's gonna make us, if we embrace it correctly, it's just gonna make us more efficient in that way.

Brian (14:22)
I agree. So what was one of the other skills that you had down that you thought of as being a new era kind of skill?

Lance Dacy (14:29)
So I'll just go through the four left real quick. I was thinking about cross -functional expertise and we can dive into some of those a little bit. Most Scrum teams we say, hey, you got to have cross -functional teams. And that doesn't mean everybody knows everything. It just means we have all the skills on the team to bring something usable by the end of the iteration. But I feel like cross -functional these days is no longer about coding. Like I know a front -end developer, back -end developer, database person, tester, UI, UX, architecture. These are more like understanding what we call now DevOps, cloud infrastructure, hardware, software integration, particularly in fields like, I work with some defense people, some aerospace engineering, writing code is like bare minimum anymore. So if you can do that, celebrate that, but you've got to move beyond that and start understanding these machines hardware, which leads me to my next one, which is continuous learning and adaptability. because the rate of change in software frameworks and tools we just talked about has accelerated. And if we're not keeping up with that and learning from that, you're gonna be left behind. So be agile in that regard. The last two I had on my list, one I'm just gonna brand it as cybersecurity.

Brian (15:47)
Yeah.

Lance Dacy (15:47)
cryptography, like I got a, went to school and for data science, you know, got my master's degree when just after COVID started, I had no idea what I was thinking, but it actually was pretty good because it was all online anyway. But I had to take a lot of cryptography classes way over my head, but at least I understand the terminology and the nomenclature, but that's going to be the key. is, and I've read somewhere, I can't remember the article, but there's like a shortage of 79 ,000 jobs in cryptography. So if you're looking and you're scared for the future, go start learning cryptography and security because these, you know, specifically zero trust architecture, these things that a lot of blockchains have been pioneering in the last couple of years, we're going to have to start locking these things down because every time we find a better way to do security, a hacker undoes that. And this was the cat and mouse game forever and ever. I don't think that will go away. So cybersecurity and more like risk management, you need to understand coding practices for that, as well as how the hardware, the protocols, how do these things talk to one another? And then the last one I just branded is more like... collaborative leadership and communication. need a stronger, you know, used to we would think of software coders sitting in a dark basement, just leave them alone and let them code. And I think we're getting to the direct opposite of that. They need to be leaders out talking to the people who need these systems, going back to that cross -functional expertise. you need to do better communication to the non -technical people so you understand what you're trying to accomplish and automate for those people in the world of cybersecurity and how software tools are changing. People get tired of the buzzwords, right? The technology jargon. So you're going to have to learn how to do that. And I think data scientists are going to be, they're kind of the first group that I've seen this happen. Like when we talk about data science and analytics and AI and Scrum, We've done a couple of podcasts on that. The issue is not just, I'm going to demonstrate what I've shown you, but now I'm going to partner with you and say what I think we should do next. Like I can model a data system ad infinitum, but my theory is I think I've done the best we can do. You can spend two more million dollars and we'll get this much or spend a thousand dollars. do this. And you have to partner with them on that. So those are kind of the five here. You mentioned the first one. So AI and automation, integration, things like that, cross -functional expertise. continuous learning and adaptability, the cryptography, cybersecurity realm, whatever you want to call it, and then collaborative, more collaborative leadership and communication. So those were the five gaps that I think if developers are scared and want to shore up their skills, those are kind of the five that I'm telling my teams to go look for.

Brian (18:38)
That's a great list. I throw a couple, I don't have a full list like you brought, but there's a couple of things that just popped in my head that I would throw into that list as well. One is what I'm just going to call teaming. Because I think there's a need, there's a real need in the marketplace today of people understanding how to do work in a team. Because regardless of what the work is, regardless of what the industry is or the

Lance Dacy (18:51)
Yeah.

Brian (19:07)
backdrop is, you know, most, most jobs, you work together with a group of people to accomplish something in some way, shape or form. That's part of the reasons why shows like The Office or movies like Office Space are so funny is because it's so bad in so many places that people don't really, we laugh at it because we all painfully are aware of how bad it is. Right? Right.

Lance Dacy (19:35)
It's real. We get it the mark.

Brian (19:38)
So being able to understand how a group of people actually do work together well to accomplish something. And I'm not talking about hokey kind of motivational, hey everybody, let's make sure we put on our happy faces today. Right, I'm not talking about that. I'm talking about just, we all go, know, the way I explained it in classes, do we think of teaming as sort of the way you would do golf on a team? where everybody goes and shoots their own 18 holes and then we total up the score? Or do you think of teaming more like it would be in football or basketball or soccer or something like that where everyone's on the field at the same time, we all have the same goal, we're all moving towards the same goal and we do whatever is needed to accomplish that goal. We have to work together. If you go to any youth sport in the world that's a team, what's the one thing that you'll hear people say, from a sideline over and over the coaches say to the team, you got to talk to each other. Right, communicate, talk to each other, call for the ball, right? And that's such an essential teaming kind of component of that, that I think that's one of the big things there is just being able to understand how to team.

Lance Dacy (20:37)
Communicate, yeah. Well, and if you don't know what you're supposed to do, ask somebody. So that's the, you know, I'm not going into psychological safety, but how many people feel safe in an organization going, I don't know how to do this because then you're like, my gosh, if I don't know how to do it, I'll get fired. I lose my job. do this. so cultures have to change as well. I don't have that on my list because this was more specific to contributing it as a team. But I think that's a really important call out. know, professional sports get a bad rap when we use analogies. I love them. because I love sports and I know some people don't play sports and I get that, but you at least have seen them. But that's a great example of five people, 11 people, eight people, whoever it is on the field together with one goal. How important is that? And how often do organizations do a good job at centering people around a one goal? Terrible. We do a terrible job at that. But that's out of the, developers, when I say collaborative leadership, they need to start pushing on those things. So that's, I guess we could call those soft skills. What would you call those, Brian?

Brian (21:53)
Well, actually that was gonna be my next thing was kind of more of these soft skills that I know a lot of people really hate that term and you can use whatever term you wanna. Right, I mean, that's one of them, right? But I mean, just being able to navigate conflict on a team.

Lance Dacy (22:01)
emotional intelligence. I've heard that. Yeah, fill in gaps when you don't have a skill. Go learn it. Solve, work the problem. You know, remember Apollo 13 is like one of my favorite movies. It was a really well done one. And Ed Harris is a great example in that, as he plays Gene Crantz, know, as Apollo 13 was having its issues.

Brian (22:17)
Yeah.

Lance Dacy (22:27)
and work the problem people, they don't know what they're doing. They're all smart people getting together, but they need something. They have to talk and collaborate. So I think that's a huge one. how do you learn to do that? You gotta go do it. You can't read a book and say, how do I get more collaborative? You gotta have, I call it attitude, aptitude, and drive. If you don't have the right attitude or tone when you work with people, They're going to shy away from you and not tell you everything you think. So you want to be approachable. You want to be, hey, bring me any problem you have. Let's talk about it. Like you want to be, that's what I call the right attitude to succeed. Aptitude obviously is your ability to learn something new and get up to speed. And then the drive to succeed. How many people have you worked with where they just do the bare minimum getting by just collecting their paycheck, you know? developers face that, right? So if you're one of those people, if you really want to shore up your skill, go figure out how to change your attitude or maybe you're in the wrong business. But how would you, you know, that's a good one to think about. How would you help fine tune those as a person? What could you go do to shore up your attitude, aptitude and drive? I'll put you on the spot, Brian. I'm sorry. you've done a lot of good talks recently on the neurodivergent and I know you've

Brian (23:38)
What?

Lance Dacy (23:44)
you know, the research that you've done on that, that's more of what I'm talking about here is finding your place in the world of every, you know, bring your gift and talent in whatever state it is, but how could you train yourself to be more approachable and have a better drive? What do you think?

Brian (23:59)
Yeah, well, so my biggest advice there is, I'll quote Ted Lasso who's quoting someone else, but right, be curious, not judgmental, right? That old phrase, which is not his, I forget where it comes from, I think it was, I don't wanna get it wrong. Right, right.

Lance Dacy (24:10)
We all knew something from Ted Lasso, right? You'll put it in the notes, I guess, later.

Brian (24:27)
But that phrase I think should be kind of a hallmark for how we approach things is with curiosity. Like why is it this way? Why is it working this way? And what's behind that rather than that's wrong or that's bad or that's whatever. Right, right. You know, someone does things a different way. Well, that's curious. I wonder why they do that that way. Is that the best way to do things? Let's discuss it. Let's analyze it.

Lance Dacy (24:42)
Or what are you making?

Brian (24:56)
I just want to briefly say too, when you mentioned the sports analogies things and how we get in trouble sometimes for using sports analogies, I say this in my classes, at its core, I can't really completely get away from sports analogies because Scrum is a sports analogy.

Lance Dacy (25:17)
In 1986, they used a professional example, team example, of how products were succeeding in 86. Sony, know, Honda, Canon, all of them, and that's what spawned that article for it, right?

Brian (25:23)
Right. And that article says, you know, the relay race approach to doing things is not the right way. That's a sports analogy, right? It's talking about relay races and handing the baton off between one runner and the other runner. And, you know, that's a sports analogy. And think in teaming, there's an inherent kind of, all right, we don't have to get into all the rules and regulations of the different sports. You don't have to follow them. But I think we can, like you said, I think we can all understand. that when you have a team on the field at the same time, there's a big difference between that and, like I said, golf, where I'm just gonna go shoot my 18 holes, right? But what somebody else is doing doesn't affect me, right? I mean, it affects me at the end of the day with the score, but it doesn't affect, if I'm on the fifth hole, I don't really need to even know what anybody else is doing because I'm just, I'm shooting the best 18 holes I can shoot, right?

Lance Dacy (26:08)
Do the best I can in my one skill. Yeah. And you do have a shared goal, right? We're trying to get the best score, but you're more limited. You can't help other people. Like what is the, it's the attitude I really think, I wish I had a better word for it, but when you walk out on the field, you either are there to do whatever you can to succeed within your capacity and have an attitude of, let's pick each other up. Everybody's going to have good and bad days. We know that. So somebody's going to show up on the team and be like, man, I'm sick or. I'm moving and I'm scattered all over the place and I'm going to be a little flighty this week. People pick each other up. Like, how do we learn to do that, Brian? How do we, how do we, how can we teach people, especially developers to contribute on their teams in that way? It's not about your skills. It's about your attitude, your aptitude and drive.

Brian (27:12)
Yeah, and I think what's at the core of that for a lot of teams and I had several conversations with the different agile conferences I went to this year with people about this. There's this cultural aspect that is so much more important than any of the details that we get into as far as meeting length and who attends and all that. It's just at its core, do you inspect and adapt? Right? Do you actually take time when you...

Lance Dacy (27:21)
Yep.

Brian (27:42)
And it sounds so simple, right? But how many times have you been involved with something at work where everyone knows it's the wrong way to do it, right? Everyone knows that's a terrible thing that's happening in our work. And we all can just kind of shrug our shoulders and say, well, I guess that's the way it has to be. Why? Why don't we inspect and say, why are we doing it that way? Is there another way we could do things? And then we try something different.

Lance Dacy (28:07)
Well, and pull it up because the other problem is the hierarchy of a traditional management driven organization is do I have the courage, you know, one of the scrum values courage to raise that flag and stand up for what's right or our fear of losing my job. And I'm going to encourage you developers out there. If you really want to do a great job, you're a great developer and you're not just trying to get by. I would challenge you like I had to learn a long time ago and say, if I do those things and I get fired, I don't want to work at that organization anyway. But that takes a lot more courage because you got a family and you got all this stuff. But you might have your answer if you start raising the flag. don't be an ass about it. Be an attitude, aptitude, and drive. But that's why I said number three on my list here was continuous learning and adaptability. You have to learn that.

Brian (28:54)
Yeah. Yeah. And I'll give you kind of a practical example here. So if you're working on a team and let's say that you need to get approval to do something, okay? If you have to get that approval and you know that approval is going to cause a delay because I've got to go get approval to do this. Well, be curious, ask the question, why do I need to have this approval? What's the purpose behind getting this approval? And if the answer, if there is a good answer, right? Well, we have to do that because compliance is really important with us and our safety or whatever. And if we don't do that, then we can have a catastrophic event. All right, there's a good reason to get approval. But if the reason comes back, well, because that's the way it always has been, we've always had to ask four layers of approval to get something done. Maybe then question it and say, hey, is there a... Can you help me understand the purpose of getting these four layers of approval? Is there really a need to get four layers of approval for this? What's the downside if I don't get approval for this? Is it catastrophic if I make a decision that maybe one of those four layers of approval disagrees with? Can it still be changed later? What I try to tell people is the speed you get from not having to go through those four layers of approval is far outweighing any kind of small mistake that that person might make. So that's kind of a practical example to say, be curious about it. Try to inspect and adapt. Why is it this way? Does it need to be this way? Is there a reason why we're doing it this way? And if there's not a good answer as to why, then I think it's not bad to question it.

Lance Dacy (30:39)
Yeah. And they're never going to say, well, we like ossified and calcified processes. Every time we have a problem, we add more checks and balances to them. We never remove them. And that's one of the bane of the team's existences these days is, yeah, we got to mitigate risk and we can't be haphazard, but that's why you got to shore up your skills on this automation and get better at problem solving, less coding and more problem solving. And I tell you what, Brian, we were going to wrap up at the end of the podcast with what I wanted to talk about is don't be scared about AI because I don't think, like I said, I don't want to use the word never or always, but I really think it's going to be hard for AI to learn and take our place in number one, emotional intelligence and empathy. you know, AI can certainly analyze patterns of what it's been for, but truly understanding emotions, nuance, and the complexities of human relationships, which is what we're talking about here. Tone AI don't, I don't think it'll ever really learn how to do that or well. All right. on top of that, be the ethical side of it, right? The cultural things and ethical, know, you could put boundaries on it. can give it rules. But I think humans have a really good, well, most humans have a good sense of that. So I think emotional intelligence and empathy, I creative problem solving and artistry. I kind of use the word artistry for developers as well, like writing code and architecting code and the hardware infrastructure and all that that goes into that. AI can generate the beginning, like AI can generate art. It can generate music if you heard some of these things. I mean, they're good. I see the art, I see the music, but it's all based on patterns. It lacks the ability to produce truly original works that stem from like live experiences and personal insights. So celebrate that and bring that to your job. And I think alongside that is complex thinking, know, strategic thinking, leadership, critical thinking, things like that. know, AI is effective at optimizing and analyzing data and helps us, you know, like COBOL used to read and write data faster than any other system. Humans can't keep up with that. Our processor is the bottleneck. So use that, offload that to something else. But your leadership requires abstract thinking and foresight and the ability to motivate people is something that AI really is not going to be able to do. So start shifting your focus from, you know, the things of data and analyzing. let the computer summarize that and then you put your critical thinking on it. And I think that's where you're going to find a better place for yourself as developers. You're going to be and need to be technologists, but that blurring of the line between DevOps and coding is coming and coming and coming. So you have to start learning the hardware that's running all this stuff and make higher level decisions and less of the lower level. So celebrate your emotional intelligence. your empathy, build those skills up, never lose sight of critical problem solving and artistry that you bring to the table and complex thinking and adaptability. Those are the things that you need to focus on, I think, as developers and embrace this AI to make you more efficient. That's my opinion.

Brian (33:59)
Yeah. And I'd say, you know, I just tag one last thing on that and it's to say, you know, with the new tools, with the new kind of AI stuff and things that come along, be curious, not judgmental. Ask about how I could use that to my advantage. You you mentioned the music kind of software. I think I know musicians who are using that kind of software to help them, but they see it more as a tool, not as, and now it'll do the job for me. just like I wouldn't go and put in into chat GBT, write me a whole book on something, right? Right, right. I'm not gonna go, if I'm a musician, I'm not gonna go say write a whole song and I'm gonna just take that lock, second barrel, here's everything that that put out and I'm not gonna alter their change. No, but I can get an idea, I can get a melody or a hook or something that I could use and then I can build upon that. So.

Lance Dacy (34:34)
And then just spin that over. Yeah. And those are always patterns, like every music you hear somebody, it could sound like another song. So you're not really violating ethics there. Like I used AI one time, you my son's learning how to do guitar and I play piano, but I was like, give me eight chord structures that are sad. I mean, there's a certain number of combinations and you listen to them and you're like, okay, now I can add a song under that. But I didn't have to sit around and pick forever and ever like they did, you know, in the old days, which I celebrate that. I think that's great. But why not have eight of them there? And I say, I like that one or don't give me eight more, you know, give me eight more.

Brian (35:13)
Sure. Right, right, right. So think of it more as a tool, right? Well, this has been great. think this is, hopefully we've given everyone a lot to think about here. And if there's one thing I kind of sum up, I hope that people look at it, maybe we're a little too Pollyanna about this, if that's a dated reference too, but naive. But I would say,

Lance Dacy (35:32)
Yeah.

Brian (35:57)
try to be more hopeful about these tools and say, can I use them to my advantage rather than how can I, how is it going to destroy it?

Lance Dacy (36:04)
Attitude, aptitude and drive. Have a great attitude, right? Say, hey, I'm going to embrace this stuff and not so much doom and gloom. Go figure out how you can use it to your advantage and you're going to separate yourself from everybody else. Totally agree with that.

Brian (36:07)
There we go. Love it. Well, Lance, thanks for coming on again. I appreciate you taking time.

Lance Dacy (36:21)
My pleasure. As always, I look forward to our next one, Brian. Y 'all have a great week.