Digital.ai’s 18th State of Agile Report with Derek Holt

Hey, everyone. Welcome back here to Techstrong tv. We have, uh, another good interview for you.

I, it's always good when I interview this guy, so I think it's gonna be a good one. Um, let me introduce you to my friend Derek Colt. ai.

That was the very first company I ever knew that had the do AI domains, right? And this was before AI was a thing like that. And, uh, boy, that was acid.

Derek, welcome, welcome back to Text Drunk tv. It's good to see you, Alan. Always good to be, always good to be here.

And, and, and you're right, we were on the early edge of the, of the Do ai. Uh, we've gotten a lot of friends now that are sharing the do AI with us, but, uh, heck yeah. Um, uh, certainly exciting time in the industry is always great to spend some time with you to, to, to chat through, uh, where things are, where things are going.

Absolutely. And Derek, before we jump in, we, we've got a nice new, uh, report we want to talk about, but before we do, just real quickly, you're the CEO of, of digital ai, but you know, you, you've helped usher this thing along. Give people a kind of sense of your, of your arc.

Yeah. So, so, uh, as, uh, I say to my team, often I'm a computer engineer at heart. I, I've, uh, been building software for a few decades.

ai in the large scale enterprise. So think globally distributed teams, um, uh, large, uh, uh, code bases, very composite applications. And, and, uh, as I've said to you, I think before, um, it was exciting when the internet became obvious in the late nineties.

Obviously, cloud and mobile took us from, uh, hundreds of millions of users to billions of users as the industry has scaled. And, and now we find ourselves at yet another really interesting inflection point, uh, when it comes to the role that AI plays in this business process of building and delivering software. And so it couldn't be more, uh, excited to, uh, be here and have the chance to work with, uh, you know, over half of the Fortune 500 today on, on helping them navigate that, that journey.

Absolutely. And it is, it, you know, you think about, I mean, you could have been born at the turn of the last century and thinking electric lights were great or the, the birth of TV and radio and, and these kinds of things. But what an exciting time to be involved here in, in, in the tech industry.

And Derek, look, digital AI is a company, you know, from the name. It's hard to, you know, to figure out exactly what they do, what y'all do. So for those who maybe aren't familiar, why don't you just give 'em a little bit of the digital AI kind Of Yeah, a absolutely.

So, so we formed the company, um, with a hypothesis that that, and I think a very, uh, e easy answer hypothesis, which is software is gonna continue to, uh, change the world and, and, and gonna continue to be a huge part about, uh, around the way that large scale enterprises and, and all companies, uh, and, and, and government entities for that matter, deliver value to their employees, to their end users, uh, et cetera. Um, and so we really focus on the end-to-end business process of building and delivering software. We have a special focus upstream from development in, in terms of planning, which we're gonna talk a lot about, uh, I think today, and then also downstream around, uh, uh, a test automation and security, uh, and, and, and software delivery, uh, as, as well.

And so we really thinking about, um, originally using the data that comes off of this business process to make better decisions and predictability. ai. But obviously as, as large language models and generative AI has become, uh, more commonplace, we're really thinking about how do we unlock the value of AI and agentic, um, beyond just coding copilot.

So those are great and are very, very important, but I think we all know that where a lot of the bottlenecks are, especially in large, complex enterprises, is upstream and downstream from coding. And so we have a set of, uh, agent solutions, uh, on, on either side of that, of that key coding task to help unlock the value. Love it.

Fantastic man. Alright. Well actually, so dig, obviously digital AI is the website.

Let me just tell people if you want more information on different solutions, that's the best place for you to start. Fantastic. Yep.

Yep. But, um, Derek, I wanted to spend our time today because you guys recently announced the, I'm gonna make, I'm reading off my other screen here. Yeah, Yeah, go ahead.

Yeah. Uh, The 18th state of Agile report, 18. So I, I'm Jewish, if you couldn't tell, eighteen's a very big number, uh, you know, significant number.

It, it, it, it's high, it means life. But at 18 it's life, right? It, this is a, a, a big thing.

There aren't a lot of reports out there that are 18 years old, right? There, there aren't, and, and I would say there's also not a lot of topics that have spanned that, that length of time. I think some of these reports come and go because the topic areas change and, and evolve.

But yeah, I mean, you and I were talking before, uh, I think it's 24, 25 years since the signing of the Agile Manifesto 25. Uh, interestingly enough, and not randomly, it kind of coincides with when the internet became obvious because obviously the internet is what has allowed us to d to deliver software more incrementally. And that's becoming more and more the case with, with, uh, you know, wireless connectivity and mobile and and whatnot.

But yes, we have been studying now for almost two decades, um, uh, sort of how agile as a methodology, how agile as a mindset has evolved. And, and to the, to the, to date, we've interviewed and, and surveyed tens of thousands of practitioners, coaches, um, uh, um, consultants, et cetera. Uh, uh, and, and each year publish a, a study to kind of say, where are we at in this agile journey?

What's changing, what's evolving? And, and I'm always really, uh, taken by the things that, that jump out. Obviously some things are a little bit more of a, of a slow grower, and, and year to year you don't see a huge delta, but every single year, there's a couple of things that, that jump out at the survey that, that, uh, both make us pay attention as tool providers, because obviously we're, we're thinking about how do we help drive, uh, new, new features that, that either help solve problems or help double down on on high value areas.

But, but, uh, it's been a great guiding light, I think, not only for us as a company, but you see this popping up in, in, uh, you know, endless presentations and references and blog posts and others by folks that we don't know. So it's been a really cool, uh, survey that kind of has a life of its own. Another What it takes a life of its own.

Exactly. So, Derek, though, I've got to imagine that this year's survey is unlike any other, right? You, uh, you Of what we spoke about earlier, right?

A a absolutely, I think agile and, and frankly probably a lot of different methodologies and business processes is at a crossroads, right? With, with, with AI coming in and sort of being the, the, uh, elephant in the room if, if, if you will. Um, and, and in particular the, the survey, uh, uh, outlines some really interesting trends that I think are, are sort of, uh, agnostic to the ai, but there's a whole bunch in here that is around, uh, how AI is impacting the, the broader software development lifecycle.

How AI is, is being in the early days being used around, around planning and, and we'll talk about it a little bit, I think in, in some ways is also teased out, I think some, um, maybe not optimized approaches folks have had here in the early days, uh, when you think about the end-to-end business process. So, so we can dive into some of those things, but yes, this is a, a report that is, uh, unprecedented, I would say. Absolutely.

Um, you know, but here's another thing before we jump into particulars on the report. It's not that AI is replacing agile or making agile obsolete. It's not replacing or making DevOps or platform engineering obsolete or cloud native or software development in general, but it is stamping it, right?

So we have AI native dev, it's kind of the next iteration you will, if you will, of DevOps ai enable platforms and, and platform engineering. What, what's the, the impact of AI in, in the Agile process? Well, I, I think it, it's actually, um, very similar to, to what you had described, and I, I, you know, you and I have talked about this, I think in the past, I'm a firm believer that if you don't understand the business process, and if you haven't automated parts of the business process, the likelihood of using AI to drive significant improvements is very low, right?

Like, in some ways that is the evolution that we are seeing that it's gotta be a well understood process, right? That's, that's, that's, that's documented and everybody kind of follows a similar process. Um, ideally if that's the case, you've driven some automation, whether that's in testing or DevOps or, or, or coding.

And then, and then subsequently, then you have a really, uh, an area that is really ripe from our view for AI disruption and, and, and agentic disruption. I'm with you. I, I spend, I've been lucky enough to spend a lot of time with customers.

Um, every customer has a much longer todo list than than amount of people and time to do it. So we look at AI as not replacing, but actually giving us a chance to scale out to, um, to be able to actually get to that, that long, long to-do list that, that every company has, everybody has more features, they wanna deliver more value that they wanna, they wanna drive, and hopefully this gives us a, a, you know, a, a 10 x or whatever the, the right, the right, uh, multiplier is around, um, each, each individual as well as, as teens. It was interesting to me as we think about, uh, agile and ai, right?

And what I would say is, and this is a a bit of a dichotomy, uh, the survey outlined that about 84%, and this aligns with many other surveys, see, and about 84% of enterprises, um, have started to use AI in their software development lifecycle. But when you go one layer deeper, what that really means is adoption of coding copilots, right? Developers using, co using coding copilots.

I was frankly a little surprised to see that only 18% of organizations have started to think about agile planning and the role that AI has in the planning phase. And I'm surprised by that because I think we all know that, uh, on average you're spending about 70% of your time in that idea to, to, to backlog phase of making decisions, especially in kind of larger, complex, uh, uh, enterprises. And the coding tasks are, are not as anywhere near as large as that.

And so some ways we've been applying AI and what I'm gonna assume is not the bottleneck in most people's SDCs. Yeah, agreed. Agreed.

So, Eric, Terry, first of all, this report is available right now. Yes. People go to digital AI and get it.

Yeah, I always like, you know, when I'm, we do a lot of interviews, obviously around reports and surveys and so forth. I always like to give people what do you think are the three biggest key takeaways here? Yeah, there, there's a couple that I have.

So first of all, um, uh, one of the key takeaways that I had was o obviously the adoption of AI continues, but what we saw, and this was a, a big number, 74% of folks are starting to use what I would describe as hybrid blended or, or homegrown methodologies. And so you see, you're seeing a little bit of an evolution where folks are picking and choosing parts of kind of well established frameworks, and they're starting to make it, make it their own. So 74% was a, a, a big number that jumped off the page.

Critical mess. Yeah. That's entirely that, that jumped off the page to me.

Um, uh, number two, um, I, I was really struck by a couple of things that, that, um, uh, that, that were more around the measurement. So only half of the respondents, it was 55% or something were in that range, um, indicated that they had visibility across the end-to-end SDLC. That's really concerning, especially when we start to think about AI adoption.

'cause again, I think of this as a, as a operations management problem, which is there is a bottleneck, apply the AI to the bottleneck, and a new bottleneck will emerge, right? Like we've been doing this for, uh, decades in the operations management space. Yep.

EE, exactly. And so the lack of visibility across of that is a problem because you won't know where the, where the, you know, ultimate bottlenecks, um, are. And then, um, the other one that, that really jumped out to me, uh, was continued success at the team level, but challenges at the portfolio or teams of teams level.

Uh, and I think we've, we've heard this a lot from customers, Hey, we feel agile at the individual and team level, but we don't feel as agile as an organization, right? And I think that has always been part of the, the evolution of, of, of agile. And so, um, this idea of really, really thinking about, uh, how do we help drive, um, uh, more agility and more collaboration and, and and iteration at that level.

You know, you mentioned it before that every one of these, every one of these, uh, reports has something that just kinda catches you, I, I call it. So I didn't have that on my bingo card. What, what was the, I didn't have that on my bingo card for this one.

Uh, one of the ones, and this is part and parcel to kind of like a lot of what, what what we do. Um, one of the, one of the ones that that I would say kind of jumped out to me, uh, was the also the inability to kind of measure, right? And I think this is one of the key things when you think about, um, uh, uh, adopting any new methodology or any new technology, if you can't measure the end-to-end throughput, the end-to-end improvements, getting better, getting worse, uh, et cetera, um, it, it becomes really, really challenging to then justify that investment and that spend, uh, longer term.

And so one of the things that I think we're seeing a lot of customers now getting, uh, excited about and, and we've talked about it on prior, um, uh, discussions, but the, the whole software engineering intelligence space, I think for a while was seen as a nice to have. But when you're now in this environment where we are in, we are, we are fundamentally changing some of the ways, you know, that, that we, we build and deliver software, um, and we have, we have, uh, you know, folks within the organization that are saying, Hey, we, we gotta have business outcomes here. We need to know if we're we're doing this more efficiently or we are we more effective.

Boy, you know, the old adage, you can't, uh, manage what you can't measure really, really comes into, into play. And, and again, as an industry, I think we've done a good job at measuring at the, the kind of task area. You know, how, how, how well do we, uh, dev develop, do, do we code, how well do we test, how well do we, uh, deliver?

But, but we gotta really take that end-to-end systems view of, of this end-to-end process in order to make sure that we're making the right decisions on where we're driving improvements. As I said, reports available up on the website. Yeah.

But here's the one thing for me that I'd like our listeners to take home. It's pretty amazing. After 25 plus years of Agile, 18 years of doing this report, it's as relevant as alive still evolving.

AI is changing it, and it will change it and will continue to change and evolve, but still useful. And, and you know, right. It, it's, it's the, the methodology framework that developers are still using, right?

Yeah. It it has a staying power that I, I would put up against any, you know, any other me methodology and any other engineering discipline You doing 25 years ago. Exactly.

Yeah. Yeah. No, that's exactly right.

I think you might've Been the Nobel NetWare guy 25 years Ago. I, I, but, but I think it's also like, you know, maybe unlike some methodologies in some other areas, given the astonishing growth rate of software, right? Just generally the category of software, and given the fact that I think it was 2012 that, that Mark Andreessen wrote, the software is eating the world Yeah.

Uh, blog post. So even that has, has certainly aged very, very well. But software is, is, is everywhere.

And with ai, it is getting even more, uh, more penetrated into more parts of our, uh, of our life and our work and, and, and, and whatnot. Um, the methodology is not only held true, it, it has led, uh, or it has taken a bit from its own advice, which it's been nimble, right? It's evolved through those, uh, those years.

It's adjusted the feedback. But, but boy, in the fast-paced world that we're in today, I can't, I can't imagine that it's not more important than ever to be agile, like lowercase agile. Absolutely.

And, and, and, uh, and with that, uh, we're excited to be able to share some of these findings. Um, we're excited to be able to see some of the areas that feel, hey, we probably as an industry have a bit of work to do here. That's, that's part of the, the evolution as well.

Um, and, uh, yeah, you, you and I have talked about it before. This is about as exciting of time as I've, I've remember in this industry. Alright, my friend, I hope to see you in person soon.

Um, keep up the great work again. ai website. Go check it out.

And you know what we'll be hearing about the 19th year soon. We'll, we'll be, we'll be there. And Alan, thanks as always for spreading the, always a pleasure spreading the, the news.

Thank you. Thank you. Derek Cole, digital AI here on Text Drug tv.

We'll take a break. We'll be right back.