Building Ignition: Colby Clegg on Innovation, AI, and the Future of Industrial Automation

Season Kickoff And Guest Welcome

SPEAKER_00 0:00

Welcome to Automation Ladies, the only podcast we know of where girls talk about industrial automation. This episode is brought to you by Inductive Automation. Guys, this is a brand new season of Automation Ladies. I don't even know what season number it is. Eight, I think. We didn't have too much of a hiatus, but we wanted to take a little break and come back with, you know, fresh season. It is the fourth quarter of 2026. And we have, to kick off the season, Colby Clegg with us from Inductive Automation. Colby, welcome.

SPEAKER_01 0:31

Thank you. I did not know this was going to be the debut episode of the season. So uh extra pressure.

SPEAKER_00 0:36

Well, I didn't want to put too much pressure on you.

SPEAKER_01 0:38

That's all right. I am excited.

SPEAKER_00 0:40

Uh so Colby and I met for the first time at a very well, I don't know. We may have brushed shoulders at ICC before, but I just remember being invited to a very nice dinner after we spoke at ICC a couple years ago. Um, I think it was maybe the last time that you guys were in Folsom before moving to the uh Sacramento Convention Center. I don't know. I'm bad with dates and times.

SPEAKER_01 1:03

It could be, so that would have been 2024. It could have been.

SPEAKER_00 1:06

Yeah. Or maybe it was 23. Um so somewhere around that time. And I just remember I don't know, even though you're like you were the CEO of a fairly large company at this point, it it was just uh very it you you don't you I heard this recently, actually after this year's ICC from some people that went that you're very approachable. Um and I felt that Ali and I felt that, and we felt a really big like I don't know, we were very impressed with the community feel of of ICC. It really lives up to its name as the Ignition Community Conference. Um and then yeah, we were very lucky to have you attend our first community conference, which was partly inspired by your experience at at ICC. And so uh we really appreciate this this relationship, which has kind of been you know on for a few years. We've had people from inductive automation on the show before. But yeah, so I I really um so we've had Susan Wilson on, we've had a couple people, we have uh, I think another guest scheduled for this month, Mia. So that's pretty exciting. But we, yeah, I don't know, we can't get away from uh ignition around all the people that we work with. We keep hearing about you guys all the time. People love your stuff. Uh and and yeah, so with that, I would love to just, I guess we'll, you know, keep our regular format to the show here. And I want to ask you, tell us how the heck you got to be where you're where you are and what you're doing. And as much detail as you want to. It's up to you.

SPEAKER_01 2:38

Well, uh, yeah, well, thank you, thank you, Nikki. And and that's very kind of you to say, um, you know, in terms of approachability and all that, any kind of like, you know, I that's a novelty to me, the fact that people are surprised by that aspect of it. Um, you know, we are very passionate about what we what we do, and I've been doing it every day since for 23 years now. So um, yeah, no, it's just, you know, but it's true at the conference, people always say, like, um, maybe this is something we'll get into later, but like they're they're always shocked by how approachable the whole company is. So I'm very proud of that. But um, yeah, so like I just said, we, you know, I've been doing this

How Inductive Automation Started

SPEAKER_01 3:15

for 23 years. I, you know, inductive automation started back in 2003, born out of a systems integration company. My personal connection was um early on. So Steve Heckman, who who ran a systems integration company for many years, he wanted to make software. He was frustrated with what was out there. He had some ideas, didn't know how to make it, uh, through a series of connections. That's what Carl and I were doing in college to make money. So it was that really that simple. We were hired as contractors to make like a little idea. And then I kind of joke, we just kept showing up, and 23 years later, here we are. Um, so that's really you know, the most simple form of it. We were born uh from the frustrations of a systems integrated. And as I recently said on stage, those frustrations weren't his alone, they were shared by so many people in this industry. Yeah, so we just try to solve problems. And thankfully, being able to grow in an organic way, bootstrapped by that company out of that, let us just keep focusing on solving problems. And and that's what we've been doing ever since. And so very fortunate right now, you know, everything you see about ignition um today, uh, it it it continues that fundamental storyline of just trying to solve problems,

Breaking The OT IT Data Wall

SPEAKER_01 4:27

you know. So uh, what specific problem was it?

SPEAKER_00 4:30

Or or what set of problems?

SPEAKER_01 4:32

Well, there was a few. I mean, the the the number one, the the the original problem was the way that industrial systems were basically closed off from IT systems, right? There was this huge wall. And I like to say kind of in retrospect that it's just that there's like kind of two parallel development paths of technology, right? And deeper than that, now I say, well, there's there's different, there's different engineering requirements on both sides of IT and OT. And that's kind of what led these these two paths. And so, anyhow, you had very specialized software over on the IT on the OT side. And then on the IT side, you know, you have to really think in 2003, it was really after like open source really became a thing, and there were these incredible um, you know, namely SQL databases, relational databases were you know, MySQL and Postgres were open source free SQL databases that were being used all over the IT world, and yet over in the in the industrial world, they weren't existent. And so Steve's, it was very simple. He wanted to connect PLC data into a database, right? And then he had a specific example, just to make this concrete. Uh, you know, he had a customer out here that wanted that. And so he tried to figure out how to make it work with like one of the existing packages at the time. And he he really prided himself on the ability to kind of make anything work, as most systems integrators do. It's kind of the nature of the job. And he goes back to them, and this was like a long-standing customer, and he says, Okay, here's how we're gonna do it, here's how much it's gonna cost. And he had even undercut his hours for that bid because it was expensive. And they thought he was ripping them off, and they kicked him out of the building and they said, never come back. And that just pissed him off so much that uh he said there has to be some other way. And so, yeah, that kind of started the whole thing. Um, so yeah, bridging that gap was the number one problem. And so, by doing that first, we were able to use SQL databases to do things like, I don't know, store recipe data, for example, and that takes it out of the PLC into an external source where you can now have as much memory as you want, uh, storing historical data in that way. Uh, things that just really shouldn't have been too hard, but were, and we made them way more cost effective by using those tools, and we made the conversation a lot easier between the plant floor and IT. You know, back in this, it's there's still a divide, of course, but back then, you know, the fear in the eyes of the plant people when you said let's go talk to IT, they'd be like, no, no, no, no, no, we can't do that. Like, it's not possible. Like, no, let's go talk to them. And they'd say, Okay, here's what we're gonna do. And they'd be like, Yeah, well, what kind of you know, crappy software are you gonna use? And we're like, we're gonna use this system that you that you already own. Like, oh yeah, cool, that sounds great. So that was that was part of it too.

SPEAKER_00 7:03

And so you said that you were built writing software in college. So are you a software engineer by education?

SPEAKER_01 7:09

Absolutely, absolutely. I've been I've been I I found I started programming when I was about 13, and it's just been it's been who I've who I've been. So it's really interesting to it's really been a transition the last few years to, you know, you have to get into this whole thing of like who am I now, you know, in terms of my identity as a as a software engineer. But that's it. I mean, I I often say I've been very fortunate, my life's been very simple, and that I've always known what I like, what I love to do. And uh yeah, I do love it.

SPEAKER_00 7:38

I will say, yeah, for at least from my perspective, just even the ability that you've been able to work at the same place for 23 years and stay, you know, engaged and challenged enough or interested enough. Um at least that that that's how I see it. Like I that I have I struggle with that. Um, but when I graduated from college, everybody was getting laid off everywhere. And then the the main message was just like there is no job security, like that thing doesn't exist anymore. And I was really bummed because I had kind of envisioned like let's I would find a company that I could work at, like have a good career, get really good at something, and like work my way up. That's what I saw like my family, my grandparents do.

SPEAKER_02 8:16

Yeah.

SPEAKER_00 8:17

Um, whereas my dad became an entrepreneur, we ended up moving to different countries, and then he's an electrical engineer that became a CEO. Um, and I was like, okay, is he an engineer now? Is he a business person? Um, I saw him as a business person, and so I ended up going to business school instead of engineering because he was a little bit kind of like my role model.

SPEAKER_02 8:38

Yeah.

SPEAKER_00 8:39

Um, but yeah, did you did you know about industrial automation or was it just kind of like that you got hired for the job and then you stuck around?

SPEAKER_01 8:47

Very much the last, you know, that that point. I I didn't know the industrial automation world at all. I did benefit from growing up near Silicon Valley. So I grew and you know, keep in mind I graduated high school in the year 2000. So I was applying for college in computer science during the height of the dot-com boom. Yeah. Um, and then subsequently the the bubble burst. And so it was kind of funny. I had uh I had a heart, it all worked out for me in the end, obviously, but like I didn't get into the college I wanted to because computer science was the most impacted major.

SPEAKER_02 9:18

Yeah.

SPEAKER_01 9:18

And then the next year the bubble bar bursts, and then everyone can get in. Uh, but anyhow, so my point is there's a lot of entrepreneurship type mentality, and just you know, create and so I benefited from that, but um, but no, the industrial world, not at all. I went to I went to college thinking I was gonna come out of it and go work at you know Microsoft or Google or you know, a big tech company, right? I just assumed that would be my starting point. And so, but doing contract, I had always been entrepreneurial, and I got like I said earlier, doing contract work and making web pages, building computers, making software for companies, just to make money. And so when I met Steve, you know, he's I had no clue about the industrial world. And he goes, you know, he's explaining it. I'm like, well, this sounds very complicated. Like, how are we gonna talk to all these machines and whatnot? And he's like, Oh, don't worry, there's this thing called OPC. If you can talk OPC, you can talk to everything, and and it's it was true. And uh, so that's how it started. And then it turned out to be relatively basic, you know, fundamental concepts, which is also surprising to most people who don't know this world, is that like all of the industrial world runs on relatively, you know, a relatively small set of technological concepts. And so uh, you know, PLCs fundamentally rule, you know, run so much, right? So I it's it was a very fortuitous accident. So I've I've I've often now said, and I tell a lot of new hires, because obviously most people we hire don't know this world, how fortunate it is to end up in this space because it's such a wonderful and fascinating world, um, and

Hiring Software Talent Into OT

SPEAKER_01 10:47

it runs everything.

SPEAKER_00 10:47

So yeah, I uh was just I I moderated a book launch webinar yesterday for a couple of guys from Europe, um, Willem and David. They run this podcast called the OT IT Insider.

SPEAKER_02 11:01

Okay.

SPEAKER_00 11:02

Um and they just published a book. And they uh, you know, we were talking about the difference between like OT and IT and this whole like why are we still having this problem? And a lot of it is it's you know, different systems, different vocabularies, different ways of working. Um, but there's an inherent tension there, and I think that's a good, you know, it for for better or worse, like it's kind of a good thing that there is. Um, but they were saying too, it's like the on the OT side, like the IT side at this point has a different tolerance for risk because if they lose their jobs, they're there are a dime a dozen at this point, people that know regular IT. But if you know OT and you know OT networks and you know OT like this sort of stuff that we do, at this point, you know, you may not have like you know, the world at your feet in terms of salary or benefits or whatever, but you're pretty much guaranteed to be able to stay employed at you know, because it there is a smaller subset of people that know this. And it's always gonna be that there's not gonna be a bubble of manufactured goods. Like that is one of the fundamental things that like our world runs on, is that we need we need foodstuffs, we need like all the things that we manufacture in the world, that's gonna have to continue one way or the other. And I thought that was kind of an interesting point. Um, and I think now also kind of in the age of AI, it's like AI can do a lot of things, but it doesn't have the domain knowledge that is needed to to just go ahead and run everything right on the OT side of things. So I think people with that knowledge and then the ability to do software programming or to do AI programming, like well, it has to it has to interface with the real world too, which has a normal human, uh natural human limitation, you know. Yeah, absolutely. So that's interesting that you said that most of the people that you guys hire don't come from the OT side. So you hire mostly software.

SPEAKER_01 12:53

Yeah, mostly, yeah, exactly. Mostly, you know, a lot of um, you know, people are from computer backgrounds, computer science backgrounds, or you know, you know, in all parts of the company, w whatever they're coming in from is yeah, you typically not the the industrial side.

SPEAKER_00 13:09

Yeah, yeah. And I'm I'm trying to think of um there was a girl that we interviewed last year that came to the con, and her name escapes me at the moment. But uh yeah, she also was like, she had no idea about this world whatsoever before she got a job at inductive automation. And then it's been very cool to like learn about. And I I really feel like, yeah, we need lots of people in this industry and we need to bring them in from different places because there's not a lot of pipelines specifically for what we do.

SPEAKER_01 13:37

It's interesting lately. I've been getting, yeah, a lot of people are asking questions around, you know, how do you get more people in here? How do you train them? How do you, you know, capture the all of the knowledge that's that's there, you know, it's it's interesting that people have been really talking about this a lot lately.

SPEAKER_00 13:54

Yeah. And we do the same thing actually at where where I work at WinTech. Um, all of our like engineers in the office that do support and uh application engineering and stuff like that, we hire computer science uh people, mostly out of college, because it's it's pretty easy to teach them the concepts of OT and like what we do. And then I think also like, I don't know, to me, we've suffered a little bit of a this is how we've always done it mentality in our industry. And so people that come from the traditional backgrounds, they're they're, I don't know, maybe this is a perception, but they have a little bit more like a limited view of like how we should do things and how we can do things. And and I feel like the younger grads like that just know general computer science, like there's so much, so many different ways that we can do all the things that we do.

SPEAKER_01 14:41

Yeah, I mean, and part of it is too, like I like I said, the the different engineering requirements, like in the sense that like the the the plant floor moves slower because it has you know higher, you know, uh far lower tolerance for downtime and risk. I thought the direction you're gonna go with the IT thing was just that you know, if if you know, if a server goes down for a few minutes, it's almost never a big deal, and they, you know, whatever. But like when a line goes down, it's a huge deal. Um, so I think people naturally become a little more conservative on on the uh things they do, and that kind of then cascades down into a lot of things. But yeah, it's it's it's a slow indicator change.

SPEAKER_00 15:20

That is also another, I mean, that's that's a that's a whole another side to that same kind of coin. Like risk tolerance for what? I guess yeah, it totally depends. Um and it makes it obviously you guys are a software company, so you would hire a lot of software engineers. Um, I think I talked to several of them on the bus when I was at ICC. And it was cool to like see developers, the developers be part of the conference. Um, a lot of companies kind of like let their customer-facing people go, and they don't necessarily like mingle everybody.

SPEAKER_01 15:52

No, it's uh it's vital that uh we've we've always cared very much that that you know, as in fact, we actively try to figure out new ways to get you know people throughout the company, but especially in dev, you know, to interact with customers and and and and do all of that. So, you know, over the last few years of the conference, you'll notice like uh in a lot of the keynotes, a lot of the different sessions, we've worked so hard to push more and more people out to the front, um, to include more people and and for for lots of reasons. But then we, you know, at the conference we have a section where every different you know group has their own table and people can come up and talk to them and what and all that. And again, um, you know, our job is to solve problems. We don't we don't operate off of theoretical business drivers, you know, we don't sit around and say how you know what's just a way to make more money. Uh obviously we want to make money, but it has to come from solving a problem. And so, like, you must have, you know, not just a couple of us that make those decisions and try to come up with those ideas. I can't do anymore, right? All the time. So it's like we need this whole organization to be equipped for that. So yeah, yeah, we do a lot.

Ignition 8.3 And 2027 Direction

SPEAKER_00 17:01

What are some of the big problems that um you guys have solved in the most recent releases of ignition? Or yeah, um yeah. Is there anything cool you can tell me that you guys have?

SPEAKER_01 17:13

Absolutely. No, absolutely, absolutely. So, you know, uh the biggest milestone recently, well, of course, here just shortly ago, we announced Ignition 2027 and talked a lot about that, and I'll get there. But that really builds on the foundation of Ignition 8.3. So, first of all, note that we're changing the numbering scheme. But Ignition 8.3, which is what we talked about, we launched last year, just 12 months ago at our conference last year. We kind of like to describe it as like the completion of a trilogy, right? Like, and without getting sidetracked on numbering, there were there was Ignition 88 and then 8.1, 8.3. Um, we skipped 8.2. Anyhow, it doesn't matter. And but the vision was to create a platform to take Ignition and evolve the platform into being this incredibly modern and open system that was very compatible with like IT standard infrastructure technologies. So Ignition Already, when it was launched in 2010, was really the first mainstream platform-independent SCADA platform. So there were other specialty things out there, but I say mainstream because you know, just generally available, download it, you know, run it. We were the first to implement OPCUA in Java and then write our own device drivers in order to do that. So it really was the first, like just download it and run it, and you can platform independent. Well, now, you know, a couple years ago, we really looked at it and said the next version of platform independence is infrastructure independence. So the way the IT world is going in terms of you know containerization and orchestration and automated deployments and all of that, that's where we need to be the leader in. And so that's what we did with 8.3. That was a and so that's a big um challenge to overcome in terms of unlocking the next generation, the current generation of modern IT uh systems to the OT world. It does seem quite techy for some people and a little overwhelming, but I promise you that you know there's something for everyone in Ignition, and that's just a fundamental thing that will continue to be important going forward. So then this year with 2027, we have now continued to build on that foundation. And um a lot of that it does start to intertwine with AI because part of what we did with the infrastructure was to be completely open. All of the configuration is stored in open files and all of that, originally for the purpose of being compatible with source control. But how amazing that at the same time AI comes in, generative AI, and it's like if you're gonna use those tools, what do you need? You need data and you need open, you know, openness and accessibility, and that's what ignition provides. So this year we just took that further, uh, and we can get into that if you want, but uh yeah, that's that's a good example.

SPEAKER_00 19:59

Yeah, let's get into that.

AI Hype Versus Production Reality

SPEAKER_00 20:01

Of course, I don't I feel like every conversation is about AI these days, and so I don't want to like just talk about it.

SPEAKER_01 20:07

Are you tired of it?

SPEAKER_00 20:08

Only that.

SPEAKER_01 20:09

Are you tired of it?

SPEAKER_00 20:10

Yes, and no. I've been talking about AI for over a decade. I actually before, so I used to work in industrial automation and I ended up working um through a series of, I don't know, happy accidents or or just opportunities that came my way. I ended up working for an enterprise AI company um using machine learning and AI in forecasting and and demand planning and supply chain, um, mainly for movie studios of all things. And I started talking about AI at that time at conferences and how business applications, like we developed a natural language processing engine so that you could talk to your data in plain English instead of having to learn how to write SQL queries and stuff like that. And my theory at the time is that that would evolve and eventually we would be able to talk to most of our software in plain English. Um, I don't want to call myself I I hate making predictions, but you know, I was kind of right, right?

SPEAKER_01 21:06

It just I'm happy to give you credit for it. It's fine. You can take credit. It's um, but it's happened very quickly, hasn't it? Like in terms of, you know, not you know, I mean, I think I think for people who are behind the scenes, maybe there's a little frustration that, like, hey, we've been talking about this work on this for a long time, but the level of the level of progress and mass adoption, I mean, there's no doubt this these large language models, generative AI has been.

SPEAKER_00 21:29

Yeah, so generative AI was not a thing at the time. It was natural language processing, it was kind of the area that we called, and it was token, you know, different ways of doing it. We we hadn't nobody had come out with Gen AI yet, or large language models. Um, and so it was all in art, it was like architecting different types of models. You may use a neural network for this, and then you use, you know, traditional machine learning for other parts of that stack. And for every problem, you really had to architect a specific model or set of models, train those models, weight those models, and then constantly. Constantly update and train them, retrain them. Like you have to supervise them very much. And um yeah, Gen AI has definitely just taken like a huge leap in terms of how fast it has gotten good. But one of my frustrations with talking about AI now is that everybody just I mean, what is even AI, right? Like it's it's a big term and it encompasses a lot of things. And I feel like most people now, when you say AI, they refer to generative AI to LLMs, these foundational models that these big tech companies are are developing at a breakneck speed and like they keep getting better and they keep surprising me. But I had also observed, I feel like at that time, that you know, Moore's Law brought us to this place where all of a sudden we could start getting some results from AI. We had had, you know, AI progress in the past that looked promising, and then a winter and stuff never really came of it, not a lot of value was created. And it took, you know, chips getting powerful enough and cheap enough, and us to be able to combine things like use multiple GPUs at the same time, high performance computing, right? Um and I was like, so understanding that that like Moore's law is a an exponential thing.

SPEAKER_02 23:14

Yeah, yeah.

SPEAKER_00 23:14

And if we're at this point where we're starting to hit that exponential curve, like we do not have mental models for how fast stuff develops once we hit the exponential part of the curve. So we can make all the predictions that we want, but like if we have zero historical precedence for any of the predictions we're trying to make, like where are they even coming from? And how like predictions are never accurate, but I like I feel like directionally, like we just we have no clue how fast things can go because it's never happened before in the history of mankind in this in this sense, right? Technologically.

SPEAKER_01 23:49

It's it's happened in the sense of everything we've already experienced. And I think you're right. Because I'm glad you mentioned Moore's Law, because I think about that a lot in terms of how this is just a progression of the, you know, it's like this progress is not linear, it is exponential, it it compounds, you know. Yeah, and so and then yeah, like I'm smiling because I think you know, we could get into a very philosophical discussion because I think you know, a lot of what I talk about on the side personally is just the way that humans aren't prepared for progress at the speed, but that's a different thing. In regards to, you know, the way we talk about it and and what what what we're doing with it right now, you know, what we have recently been kind of talking about is that like as a fundamental concept of tech of computing, you know, computers are have always been essentially calculators. That's what the word comes from, right? They're calculating things, and you put something in, you get something out. And you know, we've had various revolutions of of different stages, you know, the the graphical UIs and then the networking era and all this stuff. And and right now it's kind of like a next stage of being able, like computers have never really been able to infer what you mean out of things, right?

SPEAKER_00 25:00

So very, very explicit instruction. Yeah.

SPEAKER_01 25:02

So now we're gonna place where they can actually, there's this element of inference.

Catalyst And Building Much Faster

SPEAKER_01 25:07

And so um, you know, as it pertains to ignition, you know, what we showed at our conference, we introduced this concept called ignition catalyst, which is tools inside of the software to really help you to do all the you know the things that uh have been, you know, writing scripts, writing database queries, all these all these little things. You can you it's more of like a building UIs that look a certain way, you know. Instead of having to be so explicit with specific code that is correct, you can kind of tell it what you want to do, and it's able to infer and to help guide you towards a path of getting it done correctly in a way that can be tested and can be, you know, you know, deployed correctly and whatnot. And that might sound very much like what everyone else claims to be doing, but but you know, you have to also keep in mind that behind the scenes, ignition is still the most open platform out there. So if you want to go all out with all this crazy stuff, you you certainly can. Um but the way I what I keep trying to point out to people is that you know, so much of what we see and the and all the noise and all that, this is really an interesting phenomenon right now because in terms of technological revolutions, I don't know there's been so many that have touched so many people so quickly, right? Yeah, right. Even the introduction of personal computing and stuff took a long time to get to people, right? Here, everybody, everybody has interacted with AI in some way. So everyone's played with ChatGPT or whatever and gotten an amazing answer, and they're like, wow, I can do that. But there's still a long distance between, you know, getting to really well-engineered complex systems. And so the um, a lot of the noise is there's a lot of amazing early adopter things going on, you know, all the innovative people that are doing things in our space, right? Keep in mind, most of the people using our software, most of the people building systems are very conservative, very, you know, have high compliance requirements, lots of requirements in our industry. So it's like our mission, inductive automation, the way we've always thought about it, we've always thought about it in terms of taking amazing technology, all the bleeding edge technology, not adopting bleeding edge, but but waiting until it can take it and make it available to a normal systems integrator, make them feel comfortable and confident using it, right? So Catalyst is really about that. It's about taking, you know, these tools, this this concept of inference now and making it like so that you can use it very easily and very responsibly, right? So that's the that's the first step.

SPEAKER_00 27:36

So and I actually know somebody that has uh done a lot of ignition building with Claude, right? So like you can also and I'm seeing this just from like my industry perspective in a lot of different ways, like everybody's gonna build AI into their tools one way or another. Um and I think that part is is in our industry conservative and it should be. Like, don't throw some AI into your tool that isn't, you know, doesn't kind of stand that. I was gonna say stand the test of time, but that's not the right term at all. I'm not that not what I'm talking about.

SPEAKER_01 28:13

But like it's that fits into some concept of responsible development, right? I I think there is an element of like it's so amazing, you know, what you can get out of it right now. But what I've observed, and it this happens in terms of you know, all usages of it. It's like uh I loved I I I think Jeff Winter today put a poll on LinkedIn and it was like something about like you know, usage of AI, and it's like I don't, you know, like I don't use it or I I do use it, but I judge you, and then like, or like we all I it was something like that. I love the like like I use it, but I also judge your usage of it, right? Yeah, like my the reason is right, because we all we all sense that if somebody sends us something that's obviously written by AI, we say, okay, cool, like you almost ignore the content, maybe it's great, but that person's being a little intellectually lazy, right? And so there's something there, right? And so if I'm talking about an email like that, what do you think about a control system, right? Like, like intellectual, I don't want to maybe it's mean to call it intellectual laziness, but nonetheless, like the the propensity to accept whatever you're given, it's pretty it's a pretty strong human trait. We want to be lazy. So like it generates something, looks good, cool, ship it. Like we gotta do a little better than that right now.

SPEAKER_00 29:24

I think also, and I forget what uh what is that, the Dunning Kruger effect, the less you know, the more certain you are of what you think you know. And then the more you know, the more you start to realize how much you don't know. And I think AI is a lot like that, people that have very little experience with it and it sounds and looks so sure of itself and so you know, on the surface, like let's say you vibe code an app, it'll look really good, probably. Like, you know, if you do a good job, right? But like putting it into production is an entirely different scenario. Um, and if you don't know enough about the mechanics, like a full stack engineer, about putting something into production and connecting it to databases and all the different ways that it can break and you know, stuff like that, right? Like you're gonna get caught on the back end of like you think you're 80% done, but you're gonna spend a significant amount of resources on that last 20%, making sure that it's actually robust. Um I think a lot of people kind of at the beginning of their AI journey don't understand how far away they are actually from getting something really useful from AI. Of course, it depends completely on the application. But that's why I say too that I think, you know, the vendors in our space we're not gonna be the bleeding edge because it's really important that whatever we put out is is very easy. It should be easy for people that are not like AI experts to use and and they should there should be some guardrails around them, not just creating dumb stuff that won't work or or can produce or can be dangerous or or whatever. But at the same time, there are like this small number of probably very large organizations in the manufacturing space that are on the bleeding edge and they are willing to use that kind of stuff. And then I love the idea, it's like, hey, then you bring your expertise, your risk tolerance, and your frontier model of choice if you want to, right? And and ignition being open enough that if you wanted to use something like a Claude to help you write code to develop in ignition, you can, right?

SPEAKER_01 31:20

Yeah, absolutely, absolutely. Uh and and you know, I think what you described there, uh I I've thought about it for years, this, you know, this the standard adoption curve where you know you have like the it's like a standard, you know, distribution bell curve, right? Yeah. And you have the innovators, the early adopters, early leaders, late leaders, laggards, right? And our business, part of why I started thinking about this years ago is because our business exists because we were able to speak to those innovators and early adopters, the one, the one in five percent people, right? Who are willing to take a risk on us, for example, whatever. And now our job as a company has been to mature and move into the middle, right? Uh, so with what you just described there, it's like it's the exact same thing over again. And I would you remember when you were speaking, it reminded me of something else. You know, we have this very informal motto. We've always said, and it came from Steve, he's like, it should be easy, fun, and affordable. Easy, fun, and affordable, right? Again, remember, we were systems integrators to begin with. And so we were trying to create things that made it fun, which means why is it fun? It's fun because you can do things quickly, right? That's what we've always tried to do with Ingedition. So today, you know, at this year at the conference at the Build-A-Thon, which is this like fun thing we do where we have different systems integrators kind of compete. And we've done this for years now in different forms, but typically we give them three days, and they, you know, and our partners at Opto22 usually make some really amazing little mini plant in a box, right? Um, one year it was a car wash, a convenience store. This year it was like a whole model data center with like all these different things, right?

SPEAKER_02 32:50

Oh, yeah.

SPEAKER_01 32:50

It was pretty incredible what they did. Uh, so it's a real physical thing, and it's about the size of a desk, and it has all these little subsystems and whatnot. And those teams each get you know a couple days to build a system around it. Well, this year we let them use the alpha version of Ignition 2027 with Catalyst, right? They were both done in not three days, but in five hours. Like for the first time ever, like we go to check in on them and they're not there. And they're like out getting coffee and like what's going on, and they're like, oh, we're done. Or like, like, like we're gonna come back and do some more. But like, and then they showed it on stage and then they built on stage and added more, and it was like the speed is incredible. But the point is, it's fun, it's fun for everyone to be able to make their dreams come true, and that's what we've always tried to do. So I'm getting a little off in the weeds now, but the easy, fun, and affordable is what is the good side of all of this, and I and I that is true to what we've always tried to do, but yeah, absolutely, the early adopters can go crazy, you know, pushing the boundaries of what's possible. And to that end, I just continue to reiterate that you know, our foundation that we've built is still ahead of anyone else in terms of being open and you know accessible in that way. So knock the, you know, they can knock themselves out, yeah.

SPEAKER_00 33:59

Yeah, do you still call it SCADA? Should it be?

SPEAKER_01 34:03

We we uh well yeah, yes and and probably no, right? Like uh this is an interesting thing that we debate about all the time because um, you know SCADA, supervisory control and data acquisition, I maintain sounds pretty good in terms of its definition for you know, more or less what we do. Now, obviously, it's associated with so many historical constructs, what that means, some that differ between industries. Uh, we've always dealt with that. And so, you know, we we we kick around calling it different things, but at some point you also you always have to anchor yourself to people, something people understand, right? And so our our new track is kind of like last year we called it like kind of made the pitch that this is kind of a new paradigm of SCADA, in that like um SCADA from the sense of like an ISA like level hierarchy is a certain level. Our software certainly breaks out of that vertically, and it fits probably more into like the the industry 4.0, you know, the like the real like German spec from years ago, like concept of uh you know, the side kind of advisory system type thing. It the point is, yeah, I mean we we often find SCADA to be too restrictive for ignition, but at this point, I would rather people discover that on their own, and they do all the time when they come up to me excited and they're like, Why do you call it SCADA? It's so much more. I'm like, I'm glad you're excited, right?

SPEAKER_00 35:29

Like you discover something, but yeah, so yeah, on the commercial side, I mean, do you want to try to be in a new a new category inventor or associate yourself with a category that's already known because that's what people look for, they expect that they need that, and then they get to be pleasantly surprised and you know, kind of discover that there's there's so much more there.

SPEAKER_01 35:51

We sell from the bottom up and we sell by solving problems, and we always have. And so, not to be too mean from the top down, but the point is is that we don't just to get we don't go into a boardroom and and and and give some flashy presentation and just get checks for tens of millions of dollars. We convince people from the plant floor upward that this solves problems and should be used, and then we have to sometimes push, you know, push it up to help them get it up to enterprise, be like, wow, look at what's going on here. Um, so my point is that when you sell like that, it almost doesn't matter what you call it because everybody has a problem they want to solve, and you just have to find the heart of what that problem is, and then you have to solve it for them. And only when that's done will they start to think of what they can do next. So that's that's how it is for us.

Why Inductive University Is Free

SPEAKER_00 36:37

I was um, yeah, and and I love that. That was one of the things that drew me too when I found out about Ignition. Um, it was because people were always recommending inductive university as a place. Because Ali and I get asked all the time, whether whether we're the right people to ask, I don't think so. But, you know, just by wherever we sit or whatever, people ask us, like, hey, I want to get into this. How do I, what, what should I study? How do I get, you know, how do I get more training? Where what should I do to like advance in my career? And one of the easiest things has always been to say, like, oh, go learn ignition, because you can do it no matter who you are, where you are, whether or not you have any funds, like whether you're in college or early career professional, like you can always go and do that. And it's also like there really are not a lot of other opportunities to actually learn our industry without having to have an employer that sponsors you to go to an expensive training or whatever, right? Like, yeah, what made you guys decide to do that? Like, I know when when I first kind of got into the software world and stuff like that, I was looking at like I don't at the time, like Slack and um Atlassian, like there were certain companies that took the opposite route of like they were like, okay, let's do a freemium model, let's do a, you know, go to the individual developers first, and then we can go into these accounts once we have a lot of users. Like, did you guys think about it that way? Or was it just the roots of your company kind of started that way?

SPEAKER_01 38:02

And it's very, very simple. And and the only place I get caught up on is why it's so hard for other people to comprehend, which is that, you know, we make software, we want people to use it. Um, you know, our approach, okay, there's a fundamentally different approach to how we were selling it. You could download it off the website, you could install it in three minutes. These were all, you know, the deeper frustrations you asked originally about like what was the main frustration of Steve's, right? There were probably I he he wrote them out. There's probably a hundred frustrations, right? And it's like, I can't just download it, I can't just install it, I can't just learn it, I can't just use it, right? Like I, you know, these are all barriers, right? So we solved all of them. And three minute install, that was his shtick, right? Like, if we ever did something and it took longer than three minutes, he would time it. And he's like, no, you have to change it. Like, so so um, so like the the two-hour trial demo, and you could just reset it as many times as you want, which meant and the designers included, the design studios included, we don't pay extra for that or charge extra. So you and it a systems integrator, who which is who we are, can go build an entire system and not have to pay us until the customer is ready to commission it, right? That was an integrator frustration. So, anyhow, when you're doing that approach, fundamentally, it's not rocket science to think that the more people who know how to use it, the better off you are, right? That's it. So, so we just wanted knowledge transfer, it is important. And so we created Inductive University, and we never really thought of charging for it. We more knowledge is better, the more people who use our software, the better. And now today, I mean, you're you're right. I and actually, my favorite story to tell comes from your conference from OT Skatacon. Um, when I was there a couple years ago, I was sitting kind of in the back, and they're you know, everyone's doing all these different presentations, and uh I was quite flattered because any presentation that involves software typically was ignition, right? Okay, cool. But the audience doesn't necessarily all know ignition, they're there for all sorts of subjects. There's talks on robotics and this and that and everything. That's the whole point of the conference to learn a lot. And there were these two uh two guys in front of me, and and at one point one guy leans over and goes, Yeah, that's ignition. That's that's what we're thinking about using. He goes, but you know, even better than that, they have this online university where you can learn everything for free. And I thought, that's even better than that, you know, like that was what they were impressed by. And uh so that was very uh, you know, that's very flattering, very heartwarming to me. And and I think that, you know, today I'm I'm very proud that as we've moved into a quite prominent place in the industry, now today people are finding jobs because as university students they were learning on their side, or even not in even not in university. They just learn on their own. They're able to go get a job at a systems integrator, and we've been able to create this economy in essence where ignition knowledge is valuable and people are getting jobs because of it. So it's wonderful, yeah.

SPEAKER_00 40:52

My engineering manager just sent me a Reddit thread last week um while I was on vacation about it, it was a controls engine, a younger controls engineer asking, he's like, I use this, I use that. What can I do to make myself more marketable and to move up? And what should I learn? And like the number one recommendation in the thread was to go learn ignition. Um, so I think that you know, you've been doing this long enough. And and I think a lot of people or a lot of companies, they don't like they think quarter to quarter or whatever. And initiatives like this are ones that don't produce immediate returns. Like it takes a while for that word of mouth, for that community, that that economy to kind of build around it. Um I think that's I mean, yeah, I understand the commercial reasons why a lot of different types of companies can't do that or don't want to. Um, but fundamentally to me, it seems like the right way to do it. It just makes sense. Like you just said, if you want to, if you want people to know about your product and use it, they need to know how to use it and they need to have access to it.

SPEAKER_01 41:56

Uh yeah, I mean, I don't I don't consider that some grand trade secret. If I'm if I'm giving anybody an idea, then it's fine. But yeah, it is that. I mean, I understand though, you know, I mean, historically, businesses have commercialized their different channels in different ways. And so, you know, of course, if you are very, you know, if your if your commercial model is around your developer ecosystem, I remember back when I was a teenager getting started with development, it was frustrating because so many development networks, you always had to be part of this developer network to get the inside tools, right? Whether it was in you know Microsoft's world or Java or you know, whatever, like Java's might be a little bit more open, but unless, you know, I think about the Cisco world in terms of like networking at the time or Oracle, whatever. And luckily they all had different like you know, you know, student programs. I remember like as like a 15-year-old sending my a copy of my student ID to Microsoft and able to get, but the point was it's like it's a gate, right? It's really quite a big gate. And uh, and I think that's just another thing, you know. I mean, in terms of frustrations, you know, Steve had his from the industrial world, but Carl and I had ours from the from the IT world, from the programming world, that was one of them. You know, we I why should we have to like you know fax in a student ID in order to get a development, you know, a cheap version of a development studio, like a compiler, you know? So anyhow, uh yeah, it's been an interesting journey.

Independence And Long Term Thinking

SPEAKER_00 43:20

Do you think that if you guys hadn't been bootstrapped that you would have done it the same way?

SPEAKER_01 43:24

Like if you had Oh, who could say? Who could say? No, I mean, probably not, because I mean you know, to your point, you know, motivations come from lots of places, um, and money is the biggest motivator of all. So when you have an investor who's who wants to exit in five or seven years, then I'll you know, things get shifted for us. Um we all we have first of all, you know, early on, it was quite a point of difference. In 2006 or so, when we were really starting to try to sell more broadly, and then certainly by 2010, when Ignition became a thing, we rebranded all the software into Ignition and had this package. You know, the systems integration world had been basically just seriously affected by all these acquisitions that happened. All these platforms that people like have been acquired and put into portfolios where they just didn't get as much attention as they probably could have. And uh so I remember I think it was the first ICC in 2013, and Steve was on stage and he said, you know, and we're not selling out. And he didn't even mean that. He just said it like as a fact, we're not selling out. He didn't expect that the whole crowd would like stand up and start applauding, right? And we're behind the scenes saying, Oh my, you know, oh my gosh, like this is like a like I didn't realize it was such a thing. So that's that set our mentality. And I mean, you know, I don't know, I not to get too much into it, but but we're very fortunate and we appreciate now very much our our independence. And and I, you know, I sat on stage at ICC this year, having really thought about this, I I try to always boil things down to the simplest, you know, fundamental messages possible for the company. And it really came down to three things. Like our the three things are you know, responsibility, empowerment, and long-term vision. Um, and I can't get any better than that in terms of what we need to do. You know, we have a responsibility to our customers, we empower them and employees, and we do it over a long term, right? With long-term vision. And so I'm very yeah, proud of all that.

SPEAKER_00 45:30

As you should be. I think these days, especially, I mean, uh in our industry too, you have a ton of like PE consolidation, right? I just my company, we deal with somebody that uh we've been doing business with for years, and we've had a very personal relationship. And then now they're owned by a PE firm. And so you can tell, like we still have the same people that we deal with, but the way that they have to deal with us has changed because the pressures on them has like everything has changed about their business in terms of how they have to act, what they have to, how much margin they have to squeeze out of things, like how they can handle relationships. And I, you know, I don't mean to like soapbox, oh, it's it's bad, right? Like the world capitalism is what it is, and like there's a lot of different like business models and stuff. But I have this kind of, you know, if everything, if we could operate the way that I would love for it to be, it would be this like, you know, people with this pure vision, right? The engineer that solved their problem, and they were able to bootstrap off of their customers believing in them. And like that just sounds like such so the ideal story. And then to stay independent and not sell out, like it's it's it I think it's harder and harder these days, right? Because everyone wants to just take a bunch of money and retire into the sunset, yeah, yeah, yeah, of course.

SPEAKER_01 46:43

I mean, there's lots of elements to the story, and I don't really and I try to take care to not I'm not trying to, if somebody sells their company to a PE firm and all that, I mean, yeah, I'm not trying to give them a hard time. And and if somebody takes venture capital, whatever, that's not a problem either. I mean, the reality is this system has led to incredible, you know, innovation and growth. But um, but I will say I'm a little bit, it is a little bit annoying how the world, the tech world has consolidated itself down into basically you know, one core model now. This idea of you know, you know, funded startup and then and then evolving into PE and whatnot. And yeah, it's it that world is focused on nothing besides hyper optimization, right? And and and it gets us back into some uh you know other subjects, but with AI and whatnot, but like yeah, this this focus on on hyper optimization misses uh some important points in life. And uh so for us, you know, again, um where things will go, what we'll what we'll do, you know, everything changes, everything evolves, you know, the way we grow, it's you know, we continue to grow, we've grown, you know, every year significantly, and that means everything's always changing. And it's like our customer base changes and our you know, the people that we made that first promise to a long time ago have retired and whatnot. So the world's always evolving. Who knows what happens. But as for right now, as for me and my role and what I'm doing, I I'm enjoying so much uh you know where we're at and and and the momentum we have and this in independence we have, you know. So uh yeah.

SPEAKER_00 48:23

Yeah, that's really cool. And I think our, you know, as much as things may change very, very rapidly over the next couple of years or maybe even the next few months. Um I'm a little bit more conservative, I think, on like the rapid change of how quickly everything is gonna change. Um, I remember having a podcast with somebody, I was a guest on a podcast like three, four years ago when ChatGPT was new. And he was just insisting that like everything about the way that we work is about to be revolutionized in the next six months. And I was like, nah, dude, like I'm not with you on that. And and the other thing is it's like, yeah, our industry is slow moving for a reason, and I think it's gonna continue to be for some time. Um, and so whether like we're gonna see this like probably crazy cool new things on like one end of the spectrum, but the long tail of our customers and our industry is still gonna operate in a in a lot of the same ways. I think we'll see like great systems integrators and engineers are gonna find the ways to use these tools to be more efficient. They can get more done, they can have more fun doing it, they can maybe either make a better profit or charge a little bit less doing it, right? Like those sorts of things. But I, yeah, I don't know.

SPEAKER_01 49:28

I think the model, yeah, I mean, there's a lot to be said about you know what this means for integrators in terms of being able, like I just said with the Ike, like for example, when the build-a-thon teams go from three days to five hours, right? But what I'd like to point out to the integrators is that you know, the value to the end user is still the same, you know. It's so if we can adjust to like solution-oriented pricing or or the you know, conceptualize you know the value you're delivering, I think you'll be okay. And and then, yes, to your point about how rapidly things change, you know, I mean, it's like it's like when I started this, you know, people are like, well, how I'm making this decision for the next 20 years. How do I know you're gonna be here for 20 years? And I'm just thinking, like, this is ridiculous. Like, no software lasts for 20 years, right? Like, and so we've been working to like shorten that mentality because that's not reasonable. You know, no one's gonna sit on something for that long. You but but that's what has happened in the past, right? Like, I'm not saying that's wrong. I mean, that's what they were used to, making technology decisions for 20 years. Well, that's getting quicker and quicker, right? Um, with that said, this industrial world, I'm kind of smiling when you're saying all this because you know, if you want something to happen quickly, you know, this is what I've been pushing

Legacy Upgrades And Cybersecurity Risk

SPEAKER_01 50:34

on. If we want something to happen quickly, what we ought to be pushing on is upgrading all this legacy stuff that's up there, out there. And not just because it serves my interests, it certainly does. And I want everyone to choose ignition to do that. But from a security point of view, uh, from an infrastructure point of view, I firmly believe it's vital for the world. And um, you know, the way that AI is is, you know, the real impact it's having on you, you know, discovering vulnerabilities and exploits and whatnot. And you hear these scary things about it escaping the sandbox and all that. I'm not so worried about, okay, whatever. I'm not worried about that. I'm just saying the reality is like it can think a lot faster, it can you can find things a lot faster. And, you know, having these systems where you're like, well, it's fine because they're still running. Um, we're gonna enter a period of I'm uh, you know, anyhow, I'm just I'm I'm nervous in the next couple of years, the level of disruption that can happen because of these tools, but thankfully it's counterbalanced by the level of you know productivity, how quickly we can also adapt to it. So, you know, so that's that's my shtick lately.

SPEAKER_00 51:40

Yeah, I think all of us are kind of just along for the ride at this point, trying to figure out and make make the best of it. But yeah, I have the cyber security considerations at the same time. And yeah, I mean, people are running 20-year-old stuff out there, people are running hundred-year-old equipment out there. I mean, that's absolutely I and I still talk to uh I I was talking to end users earlier this year that were like, hey, still when we evaluate and buy, let's say, a machine or line for our plant, like we do still expect to run this for the next 20 years. What we want to do is harder certainly, yeah. Is is the upgrade path, obsolescence planning, like we no longer want to see a machine that has something that is about to be obsolete or like that we don't you have to plan for that. I want to buy a machine and I want to run it for the next 20 years. It doesn't mean it has to exist in its current state for the next 20 years. It's it's like understanding how do we make sure that this machine, at least like the core of it and the the the mechanics and things like that, right? Like there need to last. But I think that they're all now in this phase, like we do not want to wait 20 years until the PLC is so bad that like we can't upgrade everything because otherwise everything is gonna break. Like they do want to think about this, but at the same time, they want the crux of it to last.

SPEAKER_01 52:59

And so there's yeah, and everything I was talking about was in regards to software, but you're 100% right. It's yeah, it's it's yes, uh, you know, these systems, these these and that's the thing, and that's that's part of the thing, is that you know, this whole world right now runs on systems that have been, you know, accumulated over decades or more, like you said. Uh so that can't change overnight. There's nothing that's disrupting manufacturing in that way. And I I try to tell our customers, you know, who are on the nervous side of the fence, you know, to I, you know, it it's people like you, it's this crowd, it's us who are gonna decide and gonna figure out how to make this happen. No, nothing's gonna swoop in and make these machines all of a sudden magically, you know, upgrade. So I think yes, there's a lot to do over the next period of time.

SPEAKER_00 53:47

And there's definitely a lot of appetite, I think, from the manufacturers for AI, but there's also it's like it's like paired with a lot of conservatism about certain things, like the you know, the deterministic control of the machinery itself and the cybersecurity considerations and um well people have been struggling with the I mean, you know, part of what we've been doing, you know, over the last 20 years is helping to get data out.

SPEAKER_01 54:10

Okay, cool. Now you have to make sense of that data, and how many sessions have we ever done about how to best display data and how to best, you know, alarm rationalization, all that kind of stuff. So think about the opportunity. That's great because these machines are great at you know, all these tools now can can churn through data, right? Can search things. So I'm excited about the prospects of that, you know, making sense out of all that. So they should want that.

SPEAKER_00 54:29

Um yeah, uh, we also we have a demo for PAC Expo this year um with Wintech. Uh it's an A it's an AI demo for an AI like generated visualizations. Um and like we had an intern make the demo in like a week or something, because again, like he didn't need to spend all this time training and learning. Like normally it would it would take us a couple months and a couple more experienced team members to put together a demo like that. Um, so

ICC And Where To Connect

SPEAKER_00 54:58

it's pretty exciting. So with that, we're we're almost out of time here. Um, and you know, kind of our end question is usually just you know, tell us what you want the audience to what are the CTAs or takeaways, or you know, where should people find Colby? Should they find Colby? Should they just follow Ignition? Go to inductive university. Do you have any upcoming events? I know ICC just happened. ICC is a yearly thing, so if you are at all involved with uh Ignition, then I highly recommend going to the conference. Um, I loved it. I had a really great experience. I hear, I continue to hear that it's a really great um event. So I wasn't able to go this year, but I I was just at the ISA uh ISA summit and expo in Florida um a week ago and ran into Jeff Winter and um Ricardo Santos, one of my kind of uh one of the uh speakers from OT Skatacon this year as well. He was at ICC. Uh Vlad Romanov, like was just coming from ICC, and everybody was just buzzing about how great it was. So um that's gonna be my pitch. Like, go to ICC. If you're at all involved with ignition, if you can get your company to get you there, uh you're gonna have a great time and it'll be really valuable. And yeah, our friends from Opto 22, Dan White, like their team always um does a really cool job. So I can't pitch that enough. But what, if anything, do you have um to the case?

SPEAKER_01 56:22

Well, I support that message. I mean, it's called the community conference for a reason. People are always amazed at how sincere that word community is. Uh, it's a great group of people, and it's either, you know, you're there for you're mostly there for ignition, but if not, there's still a lot of people from all over the industry that are worth talking to. And so now that we're in you know a new venue compared to a few years ago, we can expand it to any size. So whoever wants to sign up, come come on down. Um, otherwise, yeah, no, we have various events of the year, we do various discovery days and whatnot. This next year we're looking at some additional events in other parts of the world. But um, but yeah, otherwise, if you're if you're new to the if this is all new to you in any way, then certainly IU is a great place to start. Uh, feel free to reach out. You know, we're very easy to talk to. Um, the the approachability is, you know, hopefully not just in person, but it's something we try to express through everything we do at the company. So uh yeah, feel free to contact us.

SPEAKER_00 57:13

Um you guys also have a new podcast.

SPEAKER_01 57:16

Yeah, the ignited podcast with Travis and Tom uh Burke. Uh, it's really cool. Um, so Travis Cox is we call him our chief technology evangelist because there's nobody on this planet who can hype up ignition like him. Uh Thomas Burke, very well known from you know his long stint as a president of the OPC Foundation. Back when we got started, and back when I was told OPC is the key to how we get to everything. It was really a lot of his work that had had made that possible. So I'm so glad now that we get to work together. And it's a great podcast. Yeah, it's it's a lot of fun. And they're very energetic. I don't know, I don't know how Travis does it, but he's it is he's fun to listen to.

SPEAKER_00 57:55

And to our audience, hopefully it'll be this season. I'm guessing probably next year, just because like everybody's so crazy busy. I hear you guys have a backlog of guests for that podcast, just like we do. Um, but we did meet at Automate this year, and uh we were pretty excited to do some collabs. So I'm sure that we will have some sort of crossover episode, um, maybe do an event together or something next year, not making any promises. But you know, yeah, I think there's a lot of lot of fun opportunities ahead. And check out that podcast, guys, if you haven't listened to it. And yeah, I think that uh concludes our time here. So thank you so much, Hope. I really appreciate you coming up.

SPEAKER_01 58:35

Thank you.

SPEAKER_00 58:37

Thank you for listening to Automation Ladies. If you like our content and you want to stay in touch, please connect with us on LinkedIn, follow the show page, subscribe to our YouTube channel, and you can send us a message or a copy on our website, automationladies.io. We look forward to getting to know you.