[00:00:15] Ghazenfer Mansoor: Hello and welcome to Lessons from the Leap. I’m your host Ghazenfer Mansoor. Today we sit down with Will Mapp, a technology leader whose journey spans media product studios and healthcare innovation. We explore how Will went from shaping conversations on First News 570 with iHeartRadio to building Studio Codeworks and eventually taking that studio through acquisition by Qlarant. This conversation is about more than technology, it’s about communication, trust, and turning technology into real business leverage.

We talk about what makes a technology organization valuable, how leaders should think about scaling and acquisitions, where AI truly delivers value today, and why clarity in systems and workflow matter more than hype. If you’re a founder, operator, or leader trying to use technology to create lasting impact, this episode will give you practical insights, honest lessons, and a clear way to think about growth. Will, welcome to the show. Just give us an intro to our audience. Let us know who you are, where you came, what leaps you have taken, and then we’ll go.

[00:01:26] Will Mapp: Okay. All. Well, first thanks for having me on Lessons from the Leap. A little bit about me. Well, I am a long-time technologist. My parents gave me my first computer, a TRS-80 from Radio Shack, when I was seven years old. And I have been in computing ever since. As you alluded to, my journey has taken me all around the world and my career. I have been to Dubai, I have been to Germany and installed systems, I’ve been into the Netherlands and installed systems. Many folks out there probably use my software and don’t even know I’m on the back end.

And really my real mantra is technology for the benefit of all mankind. Like that has been it, you know, that’s why I got into software, that’s why I got into technology. I really want to help people. I think technology and software is a game-changing medium. I also think it’s one of those artistic disciplines as well. Like we typically start with a blank screen, just like a painter has a blank canvas, just like a sculptor has a block of marble, and we have to create something and we have to create something that has customer delight, that’s gonna delight our users as well as be helpful and help them thrive. That’s me in, in a short amount of time. The main thing about me is technology for the benefit of all mankind, that’s on my website, it was on my personal business cards. That’s why I got into high tech. I believe technology is a fantastic equalizer. And we can, we can, we could talk about anything you want. You know, it’s up to you. I’m here for you.

[00:03:10] Ghazenfer Mansoor: Cool. Cool. So, so you, you have spoken on stages, across US, Europe, and you mentioned Dubai Middle East. How do global audiences differ in terms of how they think about technology?

[00:03:25] Will Mapp: So the main thing that I feel that I saw is the idea that technology is really more of a tool in your day-to-day life. We say that here in the United States, but when I was in Dubai and Europe and deploying systems there, it was really like, it was less emphasis on the cool factor and really more on the utility on what is this going to do for our business? What is this gonna do for us to get to point A and point B?

In Dubai, I had a fantastic opportunity to meet leaders from oil companies, and the first thing that they’re, that they’re asking about is, you know, like, where’s this gonna fit? How much it’s gonna cost, and how much can I gain from actually deploying this technology? It was less on features, you know, less on concepts. It was really like, what’s going to get the job done here? and, and that’s what I’ve really found, you know, to be really, eye-opening over here. Even, even now, my dev teams are like, oh, this is this cool thing, you know, check out what we can do with this other widget, you know, we need to upgrade to get this capability, and so that’s, that’s a real major compare and contrast that I’ve seen.

[00:04:39] Ghazenfer Mansoor: Yeah, absolutely. Working in a software development field, like I totally understand, developers always go directly on the most of the time they’re picking up a solution, not the problem the customers are looking for. Hey, this is the problem, how can I solve this? Can it be solved even with technology or are there other ways?

[00:04:58] Will Mapp: Right, right.

[00:04:58] Ghazenfer Mansoor: I think that’s a mindset change. So, you started Studio Codeworks. So what was the reason behind what problem you were trying to solve?

[00:05:11] Will Mapp: Oh man. Oh yeah. So in Studio Codeworks, I really wanted to get into mobile software development. You know, getting away from more of the backend systems and getting into smaller, you know, devices, you know, whether that is IoT devices that are transmitting data from some point in the world. We were heavily coming out of RFID technology and then started moving into, you know, embeddable software as part of that larger cloud of smart devices. That’s where I really had a passion in an area, you know, coming in from RFID and track and trace. And then, you know, over time we started actually building applications on top of wireless. You know, we would start building applications that would wirelessly scan products, going through a factory, near real-time communication.

[00:06:05] Will Mapp: And then we actually got into gaming. We actually built a couple video games as well. Games are a passion of mine. When I was a kid, I used to actually create games on paper and play them, you know, with my friends. And so I’ve always wanted to, you know, pursue that. So we came out with a couple of mobile games that were pretty, pretty cool. Cupcake Diva was one of our notable games that we got some time on TV to talk about. And so that’s, that’s kind of how, why I started Studio.

But at the same time, you know, you, you have to keep the lights on, right. And Studio was still building enterprise-grade software. You know, again, for some major names that you may not have heard of, but we had projects with McKesson and others where a lot of their processing was done by our code. And then on from there, you know, we worked with Qlarant on their flagship product and that led to us being acquired by Qlarant in 2019 and so we went from a boutique set of really focused, highly specific ideas. Then we followed some passion projects that we’ve actually built and had, you know, success in and then the next thing you know, we’re using, you know, machine learning and other software that we’ve actually created in other areas to apply for healthcare, fraud, waste, and abuse and that’s, and that’s how I got where I am today. I would always tell people that acquisition, I’ve never felt more naked in my life than going through that acquisition. But, we had a successful exit and most of my team had transitioned over to Qlarant and it’s worked out pretty well.

[00:07:59] Ghazenfer Mansoor: Congratulations on that. So that was a good success story. So why was Studio Codeworks a strong strategic fit for Qlarant? What capabilities or thinking did you guys bring that Qlarant did not previously have?

[00:08:14] Will Mapp: It was a critical eye on problem solving. If I can say that the one thing that we were able to do really, really well at Studio Codeworks is that we could conceptualize a problem and then “chunk” it into smaller pieces and get to a solution path, you know, fairly quickly. My team would also often just work on abstract concepts and at Qlarant for its flagship product, it really was an abstract concept, like the idea of prioritizing work and using data to prioritize that work. And then once you’ve prioritized that work, what’s the directed graph to actually solve those problems? That’s how we actually tackle fraud, waste, and abuse.

That idea sounds simple, but conceptualizing it can be very, very challenging for many people. So we brought in, you know, this idea of, hey, you know, here’s this crazy problem, you know, what are the real specifics of it? Like what is the root actual issue or challenge in solving this problem? And then we would spiral out of that, and then we would bring, you know, the techniques and we would bring the tools to the fore. And the next thing you know, we have, we have a river, we have risk intelligence, you know, using data, you know, and that risk intelligence helps us find fraud and that risk intelligence can actually tell us how to actually find that fraud. And that whole concept, you know, we’ve patented, you know, at Qlarant and it’s actually really, really cool. It’s actually really, really cool, ideas and concepts at play. The technology is just, you know, a manifestation of that.

[00:10:04] Ghazenfer Mansoor: Cool. So you were doing this for quite some time and now obviously AI also changed a lot in the last few years with generative AI. How, how do you look at AI now versus before and what, do you think people misunderstood about AI today?

[00:10:26] Will Mapp: Yeah, so man, you’re, you’re trying to get me, get me in trouble. So when I talk to people about AI, I think the big misunderstanding is this idea that artificial intelligence has some thinking component. You know, the ability for GenAI to generate, you know, lifelike text or even lifelike images and video, you know, people, people are quick to say, “Hey, this thing must be thinking” or it must be conceptualizing, or it must be doing something. Having worked in AI since 2015, that is not it. We just have a whole lot of data. A whole lot of data, and we’re essentially making predictions, you know, and, and that’s what people really need to keep in mind when it comes to it.

Here’s a story for you. So, a gentleman who is a preacher, he was interfacing with ChatGPT, and you know, he was going back and forth with it. He created a set of system instructions through his experiments to make ChatGPT have integrity in its responses. And so his instructions, you know, basically inform ChatGPT, you know, “you can’t hallucinate, you have to have veracity of your sources.” You have to do all these things. And, in the end, his system instructions were very intriguing, but when it came down to it, things still fall back on the fact that we’re making predictions on lots of data, right?

And GenAI, like ChatGPT, is designed to generate something, you know, it’s designed to generate something. And his motivation was that, you know, since these systems are mimicking human behavior, how can you construct this thing in such a way that as it’s mimicking human behavior, you know, it kind of has scruples, right? It kind of has this idea, “I’m gonna think before I say something.” And that doesn’t really happen, you know, with these technologies, it’s not a thought process. It’s consuming data, consuming your information and data, then it’s executing a number of functions against a big bucket of data that it has at its disposal, and then it’s going to generate some output from that. Even if it’s off, it’s designed to make up something, right? And I think that’s the fallibility of us as humans when we see the performance of these things and think it has to be doing something in there, right? It has to be thinking or coming up with something in there. And that’s just not the case, right?

I think where we can really take the technology if we really think about it, is use it purely for its designed and generative purposes, right? I kind of think of ChatGPT and those tools as a speech center in your brain, right? It knows how to talk, right? what comes out of its mouth, that’s where we can do a better job of informing it and making sure that what comes out of its mouth is valid, that it has veracity, that we know the provenance of that from a specifically business point of view. That’s my thought.

[00:13:52] Ghazenfer Mansoor: Oh, that’s a good point. So, you could use it as more of your thought partner as well where you’re running the ideas against and it’s giving you—right? So, are you using AI in your development processes as well as your team? Is there anything different from how you were coding before versus now?

[00:14:14] Will Mapp: I think now we use more automation when we code today. Like our team always used code that generates code. Like we’ve, we’ve always done that for a long time. Especially if you’re an old school visual studio programmer, you, you know, you’ve used code that generates code. However, we don’t integrate, you know, “vibe coding” techniques in our processes today. We just had a sprint demo today, and one of our developers was complaining because ChatGPT is giving me the wrong answers on this, and I have to go back to Stack Overflow. I had to find the problem, I had to solve the problem on Stack Overflow because ChatGPT was just hallucinating. Right? And so we haven’t, we haven’t integrated it directly from our coding, but our tooling is mostly automated. Like our pipelines, our DevOps pipeline is mostly automated, right? And I’m pretty sure that there’s some ideas and quote-unquote thinking behind that.

As far as our products, we are integrating GenAI in our products, but mostly on the side of guiding the user towards making good decisions. You know, we’re not just having them prompt the system for just anything. We’re actually allowing them to condense and understand and distill the information better. ‘Cause we deal with a lot of raw data often. And now GenAI can actually help one of our users, you know, really understand the data that they’re looking at and why it’s important.

[00:15:52] Ghazenfer Mansoor: Cool. So if an organization is looking to explore AI to bring into their process, what do you see typically? What kind of mistakes organizations make when they introduce AI without fixing their workflows first, or do you have any recommendation for those organizations?

[00:16:13] Will Mapp: I know it’s gonna sound cliché, but the first part is really asking, you know, or crafting good problem statements, like really understanding the problem at hand before throwing in the technology. I get asked all the time, you know, “can we use AI to complete an entire workflow?” You know, “this workflow takes all this time. Can I just throw AI at it and I don’t have to worry about it?” And the answer to that is typically no. Like, let’s understand what your bottlenecks are. And oftentimes when I’ve talked through a problem, you know, especially with a small business person, you know, that’s something that’s taken their time—it’s like we discover the bottleneck as we’re talking it through, and maybe you just need someone else, and oftentimes that bottleneck isn’t technical at all, and so that bottleneck, you know, that you’re looking for a technology silver bullet… it’s really getting down to those basic principles of really what is it I’m having issues with, or what am I having problems with? And like, can I actually understand why I’m having these problems?

Now, however, you know, once you discover those problems, I think AI can be embedded in certain aspects of your workflow. If you’re writing proposals or have any type of data products or deliverables that require text, I think AI is doing a phenomenal job of even taking structured record data and then summarizing it, right. Being able to get a paragraph out of a few records—AI is doing a really fantastic job at that. If you have to consume information and you’re looking for pertinent or specific details, AI is also a fantastic job for that. I would just say, and be careful with the fact that not all problems are language problems. However, you know, that’s kind of how we’ve gotten in with GenAI, especially with ChatGPT, is that we wanna consider everything a language problem. We wanna turn an accounting problem into a language problem, right? And that may not be, you know, the best solution path or gateway that’s there.

[00:18:28] Ghazenfer Mansoor: Thank you. Yeah, no, no, that, that’s a good point. And one of the things I also say that, as you were talking earlier in terms of describing the problem, I think AI is… I think the people who are better product managers are pushing the edge. You have to articulate the problem really well. If you can explain what it is, then you can get a much better response from AI, because otherwise AI not only hallucinates, but also guesses a lot. So that guessing is the one, obviously that’s the reason behind all of that.

[00:19:07] Will Mapp: Yeah, absolutely.

[00:19:08] Ghazenfer Mansoor: So, on the software and the scaling topic. What breaks first, when companies try to scale too fast, and that’s always the case. Like there are too many things coming from the top, from the board. “We want this, we want this, we want this.” And they try to scale, or they’re even getting the customers faster than they can handle. So what are the mistakes that you have seen? Like what breaks?

[00:19:32] Will Mapp: I can, I can tell you the mistakes I’ve made. I can tell you the mistakes I’ve made.

[00:19:38] Ghazenfer Mansoor: That’ll make it easier.

[00:19:39] Will Mapp: So, so at Studio, we had gotten on a really great run. And we were a small team, we were probably, you know, 15 people max, you know, at our largest size as a boutique software company. And we were in a position where I was like, “okay, here’s a, here’s a new project, you know, they wanna pay money, you know, we can add this to our portfolio, let’s go ahead and tackle it.” And what I didn’t have at that time was a solid foundation and structure to be able to grow into that. As we were growing and being able to take on more customers, you know, the systems that we had in place were great for five, you know, seven people, but we didn’t have a proper, really solid intake to be able to onboard and then handle another customer and then find the resources to get them on quickly.

And so what wound up happening is that we would onboard the wrong resources for a project because, you know, we just didn’t have enough of a structure and foundation to be able to interview properly, you know, interview thoroughly. And in some cases what happened is I threw money at the problem, you know, to try to solve it and fix it. And that of course never works. So, it’s one of those things where you should always build a foundation and structure for where you want to go and not where you are. Like that is, that is like the key thing that I have learned that I bring into my current role is making sure that, you know, our team has enough foundation and structure. Like do we have enough resources? Do we have enough people? Do we have enough, you know, non-people resources? Like do we have enough things to handle our project management? You know, can we even handle the support model if we onboard another customer?

So my questions go into like, you know, “if we wanna do this, then we also need this to be able to back ourselves up.” If you are a company that is scaling fast, you have to look two, three, maybe five steps down the road, you know, to start building your foundation and your structure for that. That’s like the number one thing that I would tell anyone—beyond just surrounding yourself, which is also cliché, making sure you surround yourself with the right people—is that you also have a stable foundation and an infrastructure to be able to support where you want to go. So yeah, I just put myself out there. I’m pretty sure someone’s gonna say something, but that’s what I would give to anyone who’s building a business and they’re starting to find success. Just making sure you have the infrastructure and foundation.

[00:22:35] Ghazenfer Mansoor: Cool. Thanks for sharing. That’s really valuable. So, I’m just gonna switch the gear to… so tell us more about the first news 570 on iHeartRadio. And how did being on that radio change the way you communicate complex ideas?

[00:22:52] Will Mapp: Oh man. Oh, so this is all right. So it was really fun. I found myself on briefcase radio one day and I was talking about technology and someone in the room worked for Fox News Radio and I was getting asked about technology and business technology specifically, and how businesses can actually take advantage of technology. And I didn’t use any jargon. I used no jargon. I explained things in a very, you know, “step one, step two, step three, here’s what you should keep in mind,” all those things. And she thought I did a fantastic job of doing that and at the time, Fox News Radio wanted to actually have a technology segment for all of its affiliates.

And this lady from Fox News Radio was like, “Hey, look, you know, we want to do this. Would you be interested in being an analyst for us?” And we would actually work with our affiliates and you would do a tour, you know, a few times throughout the year, almost once a quarter about new technology and that sort of thing. And so, one of the stations during a radio tour was First News 570 down in Asheville, North Carolina and the next thing you know, we hit it off on the air. We’re telling jokes, we’re cracking jokes. We’re talking about all the silliness that comes with technology. And from that, you know, it turned into a weekly segment. It became one of the most popular segments, you know, for that station. They would air it, you know, during promos during the week and in traffic alerts they would air parts of that segment for people to hear.

And it’s turned into, I think seven years now, where every Thursday morning, now at 7:43, you know, prime time I’m talking about technology, right? I’m sharing the latest news in tech. Everything from consumer gadgets. We talked about CES, the consumer electronics show last week, and how I think the Galaxy Z Trifold reminds me of Westworld, if you ever saw that show but also, you know, we talk about the negative things in technology. We’ve talked a lot about AI and its impact on the environment. We’ve talked about AI and its impact on jobs, right?

And that segment is so popular that in the last several years I’ve gone to Asheville, you know, for a day to spend down there to do the show live and there’s typically a gathering of people who listen, you know, to Mark Starling’s show. He’s the host and DJ of that new show. And these people actually know me and they tune in to listen to me talk about technology in a segment. So it turned out to be this really great thing and it’s a lot of fun. And actually, if you’re in the Mid-Atlantic, we’re about to get this Arctic blast. I’m turning into a part-time weather news reporter because they wanted to know how things are up here in DC regarding the weather? They’re expecting ice and we’re expecting two feet of snow. So now, you know, Saturday I’m gonna hop on and actually give a dispatch from Washington, DC. So it’s a lot of fun and it’s really been exciting. And I’m really happy to do it and I’m glad people get something out of it.

[00:26:18] Ghazenfer Mansoor: Okay, so, you have a book coming, Seven Brief Lessons on Computing. Tell us more about that book.

[00:26:28] Will Mapp: So from First News 570, and then my mother still doesn’t know what I do for real, and people ask me general questions about technology all the time. I had this idea of just writing a book that would be easily, easily consumable. And if you ever, like if you ever held your phone up and you looked at the screen and you wondered what was going on in there, this is actually the book for you. It was written specifically for you, like if you wanted to understand computers, why we used them, and how we got from beads to binary.

It is really a great book. We start the book off with a story. We follow a trade, two traders on the Silk Road, one’s from Greece, and he is bringing in olive oil and all this stuff. And then we have another trader who’s entire and they’re trading in silks, they’re trading in olive oil, they’re trading in pottery. You know, they’re trading in animal skins and they’re going back and forth, you know, their apprentices are running around, you know, loading stuff up. The guy from Tyre is using an abax (the counting board that is the foundation of the abacus) you know, he’s swinging beads back and forth, doing his tallies. The guy from Greece has a piece of soapstone, and he’s just making hashes on animal hide to do their transaction. They close everything down. They’re sitting, you know, in a bazaar. And the guy from Greece asked this guy, he was like, “you know, man, it’s like you were just whipping through those numbers so fast. It’s like, what is this device that you’re using?” and the guy’s like, “oh, that, that’s an abax.”

And so we actually talk about human beings who have always wanted to compute and compare, you know, we’ve always wanted to count things, you know, “what is greater, what is less?” right? That’s, we’ve always wanted to do that since the dawn of time, and we always used a device to do that, whether it’s a soapstone and an animal hide, or a computer, or the first computer, an abacus. And we walk you all the way through from counting systems, and we talk about the Pascal machine, right? We talk about Lady Ada, and then we get into digital computing, then we finalize with AI and quantum computing and in the end we also close with a story where we fast forward to the present and we have someone who’s in the market.

I was in a market in the United Arab Emirates and it was fantastic. I was in a market in Dubai and if you wanna see trading firsthand, go to the market in Dubai. But you have a guy in a market, he is buying silk commodities in the open market. You have a Greek trader in New York on the trading floor, and they’re going back and forth and they’re essentially doing the same exact thing, except now we have all these computers running models on one side, executing trades on the other side. But we’re doing the exact same thing that we did 3,000 years ago. That’s the foundation of the book, and so it’s very easy to read.

I gotta give a shout out to Carlo Rovelli, the renowned physicist. I asked if I could borrow his title from his book Seven Brief Lessons on Physics. So mine is called Seven Brief Lessons on Computing. So thank you to him. The publisher thought it was an easy read. The copy editor, the lady who did the copy editing for the book, she was like, “I never knew so much about computers, but I learned so much now.” And she was editing the copy. So if you want a fast read and you’re curious about computers and computing devices, this is the book for you. You can finish it in a day, especially if it’s gonna snow like this weekend, you can read it and you’ll be done and you’ll come out learning a lot.

[00:30:27] Ghazenfer Mansoor: Yeah, absolutely. I’ll check that out. And we will include the link to the book information in our, in the podcast details for our readers. So we’re gonna just do a little bit fast, lightning round. Just quick answers. One belief about technology you have changed your mind on?

[00:30:45] Will Mapp: Oh man, I didn’t know you were gonna get this deep. So, I have always been a believer that technology is a democratic equalizer, right? I have always believed that. Where I come from—I come from a town of one stoplight, you know, people are poor—and I’ve found myself in technology. But by itself, it is not the equalizer. You need access to the tech, and you need an open mind. Even though I live in Washington, DC, I’m in between Baltimore several times. I’m still surprised that people still don’t have access to technology—like real “I’m going to use this device to create, make something, or even do something that I’m doing.” I’m still very surprised with that. So I’ve shifted my mind on it just being an equalizer. It’s an equalizer once you’re able to exploit the technology, you know? And that’s how I’ve crafted and changed my thinking a little bit.

[00:32:01] Ghazenfer Mansoor: Thank you.

[00:32:01] Will Mapp: Yep.

[00:32:03] Ghazenfer Mansoor: Habit or practice you rely on daily?

[00:32:07] Will Mapp: Oh, journaling. Even though…

[00:32:10] Ghazenfer Mansoor: That’s amazing. That’s the best thing.

[00:32:13] Will Mapp: Yeah. Journaling.

[00:32:14] Ghazenfer Mansoor: Best advice you have ever received?

[00:32:17] Will Mapp: Best advice I’ve ever received: make your bed every day.

[00:32:22] Ghazenfer Mansoor: That’s awesome. Do you read books? And do you have any favorites?

[00:32:27] Will Mapp: So right now, so in fiction—in fiction, Dungeon Crawler Carl, the series is fantastic. If you’re into D&D it’s a fantastic book series that I just finished up recently. Also, Stephen King’s The Gunslinger is one of my favorites of all time. Nonfiction, I am all over the place. I read physics. I’m a big fan of Carlo Rovelli. I have read all of Carlo Rovelli’s books about physics. I’m very curious about physics. A friend of mine gave me a copy of StoryBrand 2.0. So I’m currently reading that now because one of my challenges is sales. That’s always been one of my challenges, so I’m actually trying to fix that and solve that challenge now.

[00:33:20] Ghazenfer Mansoor: Cool. Biggest misconception leaders have about scaling technology?

[00:33:25] Will Mapp: Oh, man. The biggest misconception is you can’t throw a computer at a scaling problem. There’s a notion that “I don’t have enough GPUs, I don’t have enough memory.” Working on large-scale projects, what I’ve learned most of the time is that the issue is that you don’t understand where the bottlenecks are. If you fix those bottlenecks, you can use a calculator to get your job done.

[00:33:59] Ghazenfer Mansoor: Cool. Cool, cool. Yeah, thanks a lot. Thanks Will for sharing all these nuggets. Where can people connect with you? People who want to follow your work, where can they learn about Qlarant? And do you have a personal website, LinkedIn? What do we share with our audience?

[00:34:19] Will Mapp: So you can follow Qlarant at qlarant.com and you can also follow them on LinkedIn. I’m also on LinkedIn and you can see me there. Just look for William Mapp. If you’re interested in my weekly top tech stories of the week, you can go to willmapp.com. Every Wednesday night there will be at least three stories that we will be sharing for that. The book comes out February 27th, so once it starts to get online you can buy it from Barnes and Noble on Amazon. Once that happens, you can just find me there as well.

[00:34:57] Ghazenfer Mansoor: We will release this one after that date, okay. To make sure we include the link from you.

[00:35:03] Will Mapp: Awesome.

[00:35:04] Ghazenfer Mansoor: Last before we go, when people think of Will Mapp in five years, what do you hope they say?

[00:35:11] Will Mapp: Oh, man. I would like people to say that Will helped me understand my problem and find a solution to solve it. Like that’s… to me that is winning. Like, that’s why I got into this. I like people, I want to help people win, you know, and that’s what I want people to say is that Will helped me win. He helped me understand this thing and he pointed me in the right direction. That’s all I want to hear.

[00:35:41] Ghazenfer Mansoor: Awesome. Thanks a lot, Will. It was a pleasure talking to you on Lessons from the Leap. Thank you.

[00:35:48] Will Mapp: No, thank you. This has been fun. And you—you’ve put me on the couch for a little bit with some of your questions.

[00:35:56] Ghazenfer Mansoor: You did great.

[00:35:58] Will Mapp: Cool.