Episode Transcript
[00:00:00] Speaker A: Foreign.
[00:00:17] Speaker B: Welcome to the Growth Focus Podcast. I'm Gary Lafferty, your host and founder of the Growth Focus Partnerships where we help MSP owners and B2B tech companies fix the revenue gaps that are quietly costed them growth.
Today's guest is Missy Trumpler, CEO of Agile AI Labs. Two years old, noisy market, and they're building real momentum. And the way they're doing it is worth paying attention to. Their primary growth engine is partnerships with IT service companies. And we get into how they landed their first partners, what made the relationship stick, and how they've structured it so no one is stepping on each other's toes. But here's the context that makes this conversation interesting.
What Agile AI Labs actually solves is technical debt. The hidden cost that sits inside almost every software development team and quietly bleeds time, money and people.
We're talking $2.4 trillion a year in the US alone. And the reason why it's so hard to sell against is because the industry has basically decided to live with it. Bunks ships no matter what requirements, get misread tests, miss the mark. Everybody knows it's happening. Nobody wants to say it out loud.
Missy comes at all of this from outside the industry. 25 years in sustainability consulting, and that outside perspective is exactly what makes her take on growth partnerships and fixing a normalized problem worth hearing. So, as per usual, no fluff. Let's get into it.
Hey Mrs. It's great to have you join us on the Growth Focus podcast for this episode.
Why don't you start off with a quick intro. Why don't you share with us who you are and what is it exactly that you do?
[00:02:09] Speaker A: Okay, my name is Missy Trumpler and I am the CEO of Agile AI Labs.
And what we do is we have a software development platform that assists software development teams throughout the sdlc. So what we started out to do when we created the platform was to solve the technical debt and defect problem.
And that is what we have been working on ever since we launched this program in 2023, as soon as large language models became available. Our founder, Scott Aziz, who is also our technical advisor, that's really what he set out to do. He's been in software development for the last 35 years, and his concept was we have to start dealing with the roots of the problems that are happening in software development. And he saw AI as the opportunity to tackle those problems right from the foundation of software development itself.
[00:03:11] Speaker B: Well, Jamal, I can't wait to get stuck in to this particular conversation, which is, you know, one of the reasons why I was really looking forward to this particular episode. But before we do, you don't come from a technical background. You actually come from sustainability consulting.
Explain how you made that shift and what you believe you bring to the tech world today.
[00:03:35] Speaker A: Oh, that's a good question. I had to sell this to the people I work with too.
Well, my entire career really has been based around sustainability and resiliency.
I've been working with businesses now for 25 years. I hate to date myself, but for that long, working with them on not only their infrastructure, as far as their physical infrastructure, but also their business processes to make them more efficient and also to make them more resilient and looking at it in a disaster recovery mode. Because as we understanding what was coming down the pike as far as climate change and looking at things of that nature, you really needed to start. And I lived in Florida for 30 years, so we, that was kind of the epicenter of where the United States was going to be hit hardest, first by climate change, as you're seeing in Miami and areas there.
So anyway, my job was basically to go into businesses, analyze what their processes were and then address some of the issues that they had. Look at how they're sourcing things, look at how they're operating from energy to water to just bills alone. And honestly the my motto for my company at that time was waste not, want not. Because anytime a penny saved is a penny earned, right? Anytime you can save company money, you are. It's the same thing as them going out and making a sale. So like a school district for example, that I worked with and at for quite some time, I saved them a million dollars a year in operating costs just by looking at the way they were operating in the facility level in not with the teaching. That wasn't my cup of tea. But as far as how they were functioning and managing their spaces, how they were managing their processes, how they were purchasing.
And honestly, there is a tremendous amount of waste in the way we do things. And part of it is because we don't change processes to keep up with the times. A lot of times we just keep doing what we're comfortable with and looking at different software programs to assist with that.
Well, as I was going through those processes, of course we're hearing a lot about AI is coming in and it was becoming pretty evident that things were going to move in that direction.
So I figured, okay, I better start learning about this now. Because when I was dealing with IT teams, IT teams of all teams within companies were probably the most close to the best. Trying to get under the covers in the. It was very difficult and I understand why now that I'm in one and, you know, they're worried about the code sharing, that kind of thing. But that wasn't really what I wanted to discover and uncover. I wanted to understand more about the process itself, like the sdlc.
Now I understand it backwards and forwards.
And yeah, I can see why they kept a lot of things close to the best, because in software development, they're okay with putting out a product and then fixing it after release.
There is not any other industry that I can think of where that's okay. Not any. And it used to frustrate the hell out of me, quite frankly, when I was identifying, you know, certain things to purchase, they'd say, oh, it does this, this and this.
But it wasn't doing this, this and this. It was doing this and this. But they hadn't quite perfected that yet, right.
So when I saw what was happening with AI and this opportunity kind of came in front of me, I said, I really want to work with this company.
And really their driving force was to improve the process as a whole, but also make life better for people in the process because the burnout rates in IT are insane. They really are stakeholders, the internal stakeholders, forget the externals, you know, and for the people that want to just throw the computer out the window when things aren't working the way they want them to, but for the people that are working in IT, their jobs really are 24 7, they're on call all the time in these companies.
So trying to make that better, trying to reduce technical debt, trying to streamline process, that was kind of, for me, that's what I love.
So it seemed like a natural fit. And I've been with them ever since. I was very grateful they took me on, and we've been working through those issues with customers ever since.
[00:08:22] Speaker B: Well, let's talk about that, Ms. I mean, because that's quite a, quite a journey. And, you know, I just want to, before we go further, I just want to really dial it back because you gave us so many nuggets just in that last little Friday.
Break some of that down, you know, the very fact. But I'm going to take the two biggest ones is, is that, you know, as you said, that there is so much wastage and not purposeful wastage in a company. It doesn't really matter what company, you know, we, we, we deal with growth, revenue growth all the time, with clients, and it's not necessarily wastes out here, it's like you said, we don't change processes and if you don't change the processes, there is natural leakage that's happening that you just do not realize because you're so focused on moving forward and filling the bucket, you don't know where the starts and then the hole starts and then that's where the leakage comes on. So I think that was a really good point that you mentioned, you know, as a kickoff from here. But also the fact that you mentioned that with software companies it is the norm to send out stuff that's not ready. It is the, the bar is so low, but it's almost a rush to get the product out there, isn't there? And especially if you're VC backed, PE back, everything.
Yeah, it's a super rush. Run, run faster, there's the ball, just go with it. And it's almost accepted that hey, when we release this, it's going to release, we're going to have a load of bugs go out with it and it's not going to work as we say it was. But hey, that's just the way the industry works. And what spec test does is actually help people reduce that debt, isn't it? You mentioned, you know, what was the debt you called it just now, the technical debt. Technical debt. Can you just give us a very sort of brief 60 second explanation of what is technical debt?
[00:10:02] Speaker A: Okay, so technical debt is, is, can be, can encompass quite a few things. But just at the baseline, if there's a defect or a bug, right? Even in the process of they're going through creating the software itself and they, they find a bug or a defect. Well who's going to hunt down that defect? The requirements gatherers? Because a lot of times it's like, well, the problem started in their requirements. Well, did it or was it in the code? And so the testers are testing, right? From hopefully their interpretation of requirements, the coders are coding from their interpretation of requirements.
So a bug and a defect, you know, you've heard the term garbage in, garbage out, right? So if you've got garbage in as a requirement and those requirements aren't very well developed, then you're going to have bugs, you're going to have defects because. And also the interpretation where the testers are they actually building tests that are testing for what the coders are actually developing, let alone scope creep. So having to hunt down those problems when the tests do fail, that is technical debt, because that can take longer than the development itself. Identifying where that problem started was it in the code, was it coded improperly? Why do we have additional functionality here that we didn't ask for? Where did that come from? Did that come from the coder's interpretation of the requirement? And so there ends up this finger pointing exercise.
And yet it's really just wasting time. That's the way I look at that. Technical debt is a waste of time.
And there was a monetary value that was put that in 2022 by the, it's a consortium of software information and they basically, in the United States alone, that technical debt was adding up to $2.4 trillion a year.
And so think about that and think about the stress of that. Right? Because now you're a requirement gatherer, say the code was misinterpreted. So now you've got to go back and try to have that conversation and go, well, well what was it that, why did you build this? Well, we built that because you said this or you documented this. Well, that's not what I meant by that. And so our whole purpose, our whole purpose for existence, of developing, creating the solution that we've created was to identify that and start with the most solid foundation of a good requirement as humanly as, and now AI driven possible.
[00:12:44] Speaker B: And so yeah, it's obviously a very well received solution to a problem that not necessarily people weren't aware of. They were very aware of it, but they just thought we don't need to deal with it. Which has really allowed us to move on to our next subject, which is growth. You're a two year old company, you're in a very, very noisy market.
Walk us through how you've actually been winning business.
What's the primary growth engine for you right now?
[00:13:11] Speaker A: For us, honestly, IT's partnerships with IT services companies. We work with a lot of them.
That all by itself has been quite a learning experience and we're very fortunate to have the partners that we have.
But needless to say, there's a lot of support that goes on with our partners. And one of the things that truly tells us that we have a successful platform is that they use it internally as well as selling it to their customers. So if they're using it internally, first of all, that's a great feedback loop for us, you know, because we try to take that information that they're providing us, hey, we're working on this, we're doing this, we kind of need you to do that or we'd like to see this.
And so that is, we've stayed in the lockstep with what's coming out in AI because you have to stay current with all of that information.
But in addition, our customers are almost steering the ship in how we are going forth and increasing the capabilities of the platform.
Like for example, we first started requirements to test and we started heavily focusing on the requirements pieces piece because the test automation piece was really getting saturated.
There's a lot of companies in there now. There really aren't a lot of test automation companies that work with the requirements the way our platform does. There is really.
I haven't seen a platform yet, maybe ChatGPT, but that's totally insecure and it doesn't have the kind of guard railing that we do for specific projects.
So our partnerships, yes, we have direct sales and that's great too because that allows for that one on one relationship.
But now that we've been in these partnerships for as long as we have, they trust us to know that we're going to work with your customer. But you are the main line to that customer. We're just here to support your success because your success is our success.
Right, and the customer's success is everyone's success.
[00:15:21] Speaker B: Yeah, exactly. And I think this is the key thing when it comes to working with great partners. You know that there are plenty of people listening here, plenty of people watching this and go, you know, I've tried partnerships, they don't just seem to work. I just, or you know, I know that's something I should be doing, but I just can't seem to find a way to do it. It works really well with you. It seems to be clicking really, really well. How did you land your first serious few partners and what made it stick? What insights can you share?
Who are listening are thinking that's really what I should be doing.
[00:15:53] Speaker A: Well, we are very fortunate in the fact that most of the team, you know, has all been in the IT services, has been in it, right. For years.
Decades actually. We're all AARP card carrying members at this point, so decades.
So they have historical relationships and things of that nature and have worked at various companies through the years either in consulting positions or direct.
And so there were those relationships to build upon and then showing them what the platform does and them recognizing immediately like this is a game changer and particularly with AI at this point because I just do want to share that one of the things our platform does is it creates almost like a wrap of governance, that AI is completely, completely lacking that guard railing. But also we share every piece of information that our AI is doing. We have no black box Everything is transparent. So you see it. So it's auditable, fully traceable. Well, that matters to our partners as well because they want to be able to click a button and fully trace everything that the AI has done, because they need that for their customers. When you're dealing with the banking system, insurance systems, they need fully auditable, fully traceable information.
So that was a big part of it was seeing what the platform offered. But then the support piece, you know, because you go in and you're, you know, when they're selling a customer, because customers are clamoring for AI tools, but they don't want just any AI tool, they want an AI tool that's trusted and tried. Well, that's not an easy thing to do when the industry really is only two and a half years old.
Unless you're like the big five.
And that's fine, but the big five, there are security issues there, there's just some, you know, there's some problems that come with that too.
And with AI hallucinating and also we've seen in different instances that AI covers its own, but that's a problem when you're dealing with some of the initial creators.
So our platform becomes like a third party governance tool that assists the partners with the customers as well. And that level of transparency. So I think that's a big piece of it. But it did take time for them to gain our trust to see we're not going anywhere. You know, we weren't folding after six months. That was a big piece. Right. You know, they had to see that we were going to make it, that we were going to keep plodding along and keep innovating. Scott, our founder, as I was telling you about him, he's constantly, his eye is on innovation at all times and what is the next piece. And then our customers help to fill in what is not just the next piece on the innovation side, but what's the most important piece on the functionality and practical side.
And that's. We have our operations officer. She was corporate risk in the big banks, in the big four.
So she's a perfect person that has eyes on all of this. That basically says we have to be careful here, we have to look at this here. So we've got a really great team that brings different perspectives to the table and that also helps to support our partner customers, our partner resellers.
[00:19:30] Speaker B: But I think there's a, you know, you mentioned earlier there about, you know, that the, one of the key things that you guys have there is the fact that the partners are actually utilizing your system, you know, before they're going out selling. And an old sales mentor of mine, 30 odd years ago, remember them saying, you know, if you don't own a set of knives, how can you go out and sell the set of knives? You've got to be able to utilize it first, know what works, what doesn't work. And I think that's a great thing. When you're looking for partnerships within the business.
They use what you do, do they use what you have? If not, it's going to be really difficult for that partner to go out there and sing the praises of it if they're not actually just using it rather than just off your brochure or your website or what the sales, the self promotion stuff that you give them. I think, you know, if there is one nugget that people are listening to here are watching, it is go back to your partners. If partnerships hasn't worked before or you want them to work better, see if they can actually utilize what your product or service is. It'll make it so much better.
But you also use direct sales. You use direct sales. You also use partnership channels. You're running both sides of those.
Do you see any tension there?
What tends to work best on both sides of those for you?
[00:20:47] Speaker A: No, we're very careful about that. First of all, we have no interest in stepping on our, our partner's toes. None. We, like I said, their success is our success. If a customer comes to us directly, which happens, you know, quite a bit, word of mouth is getting out there, well then we work with that customer. If we find out, we do ask them ahead of time, are there IT services companies that you're already working with because number one, that could be an avenue for us to partner with them. And they have a much larger customer base than we do these IT services companies that have been in business for a long time.
So you have to kind of shift the way you're looking at things. And if we also see that a customer would benefit from working with an IT services company that we know is doing a good job for their customers or they've really honed in, say they work a lot with insurance companies and this insurance company is kind of needs a gap filled that we can help with and we'll recommend the partner to them too. So it works, you know, that it works in all ways. You know, we're going to adjust to whatever the customer wants, that's the fact. But without ever stepping on our partner, you know, reseller. That's yeah, that, that's just bad for business. You can't be doing that.
[00:22:11] Speaker B: You cannot do that.
Yeah. Do you know, I'm honestly surprised the amount of people do, Adam. So when I say this, everyone listening or even yourself, Ms. Is going to go, really? Does that really happen? But yeah, they do try and compete with their, with their partners. They're not, they're thinking with a partner's client, is that. And this is my client. They're two different things. When actually they're not. They're. They're. They can be and work in great cohesion with each other if they're handled right. You know, you've measured several times. That works, that works, that works. And I love it. Especially on a show like this. We're talking about, you know, inspiration for tech leaders and founders out there on growing their business.
But we all know that not everything works. This is real life. This is real business. And there's stuff that just doesn't work.
You've said, and I've said this many, many times. You know, getting your message out there through the noise today is one of the hardest things to do right now. No matter how long you've been in business, two years or 20 years, the added problem your company has is you're selling against the problem. The market has just normalized. Bugs are just accepted in the industry. They don't even see that as a problem anymore. How do you get buyers to feel the pain of something that they've actually, I don't know how else to put it, Decided. They decided they're just going to live with it.
[00:23:33] Speaker A: I'm going to disagree with you there, though.
They feel the pain, let me tell you. They feel the pain of the technical debt. Not necessarily because they themselves are paying for the cost.
But that stress, that burnout that I was talking about, that is the pain of technical debt. That is the pain of having bugs and defects flow through to production or not make it to production, but slow down the release process. Right. Because your customer gets pissed if you're not able, you know, oh, you know, sorry, we found this defect or that defect, really, they're not experiencing pain from that. Yeah, they are. And that's reputational pain. It's burnout because the amount of time that they're spending on things that really are the come right from the fundamentals of where you should be starting from in the first place. And if you don't have the fundamentals, right, if you don't get those requirements and acceptance criteria right, then again, you're going garbage in, garbage out. And I will tell you, there is not a company that we have talked to, not a customer in the two and a half years that after most of them don't start out with it right up front because they don't want to reveal it because they feel honestly it's something, it's kind of like ashamed about it. But they, within 20 minutes of that conversation they're telling us, yeah, we have a problem with our requirements and our acceptance criteria.
Uh huh. We know that's okay. Yeah, that's why we're here. That's what we're here to help you fix. And this is so common, it's not anything to be. And a lot of them, in a lot of the platforms, this is another problem that we're solving is there's legacy platforms, right, where all of that information, the documentation is lost or it's historically gone from somebody who left the company.
Well, how do you, what do you do about that? You're having to, you're working on a system that you're not even sure what the specifications for that system are.
And basically we, you know, we have customers that are using our platform now to recreate those requirements and be able to update those platforms and that software based on requirements that have been developed. We don't reverse engineer, but the platform can help them reverse engineer. And this is a huge problem. Huge. And going from legacy systems like Mainframe over to a cloud based system, where are those requirements coming from? You think they're all filed in this lovely little, you know, place for, oh, we can just access this and rebuild from here?
No. And that if you don't think that's stressful and you don't think they recognize those problems, they're dealing with them every day. And that is why honestly this industry, as much as it's kept close to the vest, it's too bad it's not a little bit more secret, missy.
[00:26:47] Speaker B: It's almost like it's the industry's dirty little secret. We'll keep it, we're ashamed of it, but we're going to keep it because we don't want that to go out, you know, and if it's almost like if everyone does know it, that's, everyone knows that's what the problem is.
[00:26:59] Speaker A: But it's like from there and it's nobody's fault. That's the thing. It's just, that's just the way it is, the way it's progressed over the years. It's no one's specific fault. And that's the thing is they feel responsible and it's not their fault.
[00:27:13] Speaker B: Well, let's talk about another problem because obviously, you know, AI, you're in AI. We can't have a, you know, a tech based podcast without you and talk about AI and where it's going. AI coding. And you've mentioned this, I've mentioned this many, many times. Garbage in, garbage out.
AI coding tools are, you know, effectively accelerating the exact problem you were built to solve, right? They've got all these things. There's, in your opinion, is that a gift for your growth story or does it make the market harder to educate against?
[00:27:47] Speaker A: I think eventually, or as we go forward, it's going to be a gift for us. But I hate to look at it as a gift because it's capitalizing on something that's really a little bit scary right now, to be totally honest.
Putting too much emphasis on AI's capabilities without the human in the loop, without constant supervision is a little, it's not even a little scary. It's scary.
So one of the things, it is a gift to us in that our platform, as far as I know at this moment, is the only platform that literally follows a requirement through the entire sdlc. We don't do the coding, we can integrate with every single coding tool but through an MCP server.
But our platform creates the requirements with the human. Right? That's what we do. We work through that to create a really robust user storing acceptance criteria. And then we create prompts for the coding tools from those user stories in a specific project. Your uploads, which are all very specific architectural information and BRDs and code samples, and then you upload that into the platform and we create those prompts, the guard railing around all of that. Our platform is now heading towards 6,000 hours of development. We were at 5,000 hours about three months ago, four months ago.
So we are constantly putting in edge cases, negative cases. We're always doing that to make sure that AI being run through our tool. If anybody's using AI solutions to feed into our tool, we're trying to make sure it won't hallucinate, it will not give you bunk information. It's not going to go rogue when it's coding and you know, code to.
We just learned, I think two weeks ago that I think it was AWS itself that had a coding problem with their sales area where literally it deleted a bunch of things and then recreated it. So our platform will not.
It's so specific to what needs to be prompted for the AI coding tool that the AI coding tool has a very specific method map to follow.
And that information that's going into the coding prompts is exactly the same, with exactly the same interpretation as the test cases that are created. So, you know that it's not garbage in, garbage out. It's, you know, golden nugget in, golden nugget out, golden nugget out that's actually has a through line that goes, and transparency and traceability that goes all the way through the process.
[00:30:47] Speaker B: So that's, that is such a good thing to hear, you know, when everyone, everyone nods with the garbage in, garbage out, because everyone knows that's what, that's what's really happening and they're fearful of it. But it's so refreshing to hear, you know, that that is a problem that can be solved. It can be solved with the right processes in place. And you know, it's not, doesn't have to be the norm and it could really save you time on that. So, missy, one last thing. You know, for those listening and those watching here, one actionable thing from you. If there's an MSP owner or an IT services leader out there listening or watching right now, we're approaching a brand new quarter.
What would your advice be? You know, I mean, the momentum of your company's growth has been tremendous. You know, given the short space of time that you guys have been around. If you were to give one piece of advice to, like I said, a founder or a leader for the next quarter, what would it be and why?
[00:31:43] Speaker A: Well, first of all, listen, you got to listen to your customers because as I told, like I was explaining 20 minutes into a conversation where they finally start to open up about what's happening.
Number one, they're giving you feedback because they want to succeed. Any feedback that a potential customer is giving you, don't just shrug it off like, well, they don't really understand what's happening here.
Chances are they're going to be the ones that are applying what you're creating, right, what you're developing.
So yes, they are in tune with what's happening because they know and it's pretty much what's happening at one company is happening at another.
It's not that different from space to space. Yes, there are little different nuances or toppings, as it were, functionalities, but the bottom line is there's a through line usually to the problems as well, that's definitely listening to your customers and be willing to pivot. You have to be able to pivot, stay very current on what's coming out in AI because that's also moving very quickly and keep humans in the loop. You've got to keep humans. We're going to regret it.
Humanity as a whole is going to regret it if we don't do that.
But companies are going to regret it and be open to changing your process.
Because that's the thing with AI and that's where companies are finding their most success stories out of AI is not that they're plugging it into a process that was already okay working for them, but if you're willing to take AI and maximize its potential and capability by switching up your processes a little bit, it can take you to places you never thought you could go. Because it's giving you information.
That's all it's for. Don't use it to think for you use it as a tool to accelerate the knowledge. Being able to gather knowledge faster and then implement it.
[00:33:49] Speaker B: I love that.
I'm a great believer in implementing the knowledge. Knowledge is not power until you implement that knowledge. I love that. What a fantastic place to wrap this episode up. So miss, if people want to learn more about what you do, perhaps work with you, what is the best way to get a hold of you?
[00:34:07] Speaker A: Well, you can get a hold of us through our website. We do have like a contact page. Just click on it, send me an email, Send us an email and one of us will respond to you. We're very quick about responding. You can keep up on what we're doing. We post on LinkedIn on a regular basis to share what's going on, white papers, things of that nature.
Agile ailabs.com, the name of the company is Agile AI Labs. We have a YouTube page.
I just posted a video or had a video posted yesterday that's only two minutes long. That gives you the whole arc of what spec to test AI does with spec to code now in tandem. And we have a couple of new features that are coming down the pike in the next couple of months that we're also really excited about. So you can reach out to us anytime. We're always happy to hear from our customers and our potential customers and I'll make service partners.
[00:35:03] Speaker B: Okay. Yes.
I want to make sure that those your all your links are my get my team to put them all in the show notes so that they can just get to you easy without having to go around and searching with the Internet. They can just go from there. So all that remains me to say is Missy, thank you very much for your time today. It's been an absolute pleasure, pleasure having you. Thank you for sharing your insight and your times with us. It's been fantastic.
[00:35:26] Speaker A: Good luck everybody.
Good to meet you, Gary. Thank you. Bye.
[00:35:30] Speaker B: Bye.
There's one thing that Missy said that I keep coming back to over and over and over again as I re listened to the conversation. She talked about how companies come into a conversation and for the first 20 minutes they guarded careful, not giving too much away and then something shifts and then they admit it. Yeah, we've got a problem with our requirements. We know. We've known for a while.
That's not a software problem, that's a revenue problem. And honestly, it's not that different from what I see on the commercial side of businesses every single day. The issue isn't that people don't know the leak is there, is that no one's made it feel safe or urgent enough to actually go looking for it. That's exactly what the revenue leak audit is. A free 30 minute call. No pitch, no deck. Just a focused conversation about where your business is losing revenue after the lead comes in. Pricing processes, follow ups, handoffs. Wherever the gap is, we'll find it. Booking link is in the show notes. Thanks for listening. Send this to someone who's building or selling in the tech space and they'll get it. See you next time.
