15. From Mainframes to AI Agents: William Brown on Transforming Tech and Self
Season 2, Episode 5 of Kinwise Conversations · Hit play or read the transcript
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Lydia Kumar: Today I am honored to be joined by William Bill Brown, a seasoned veteran of the IT world with a 35-year career spanning from data entry clerk to chief architect at IBM. Bill has witnessed and led every major technological shift for the past four decades, from the rise of personal computers and the internet to the intricacies of cloud computing and service-oriented architecture for educators. This episode reveals the powerful combination of soft skills, technical fluency, and lifelong learning that today's students will need and offers practical insights into how AI is reshaping what readiness for the future looks like. His story offers a compelling vision of how technology, guided by intention and equity, can expand opportunity and unlock human potential.
Hi, Bill. Thank you so much for being on the podcast today. I'm really looking forward to diving into your work and your story. You've done so many interesting things with AI throughout your career, and I want to now pause and give you an opportunity to introduce yourself and your story so that anyone listening to our show has a sense of who they're hearing and learning from.
Bill Brown: Okay, well, first of all, thank you so much, Lydia, for having me on. Um, I'm really excited about doing this, uh, and, um, uh, excited to, to, to talk and get to know your audience. So, fantastic. Um, little, a little bit about me. And I'll try and keep it to a little bit, but, um, I've had a 35-year career in IT, um, started, um, where I grew up in, in New York City. Um, and I started as a data entry clerk for the City of New York, uh, the Department of Social Services. Um, and, um, I did that for, uh, a, a few years and then, um, uh, as, uh, the, as I'm really dating myself now, right? So then as the PC started to get more prevalent, um, I started to work more, uh, in and around, um, uh, personal computers. I got into networking, not social networking, it wasn't even a thing back then. Um, but, um, uh, networking computers. And, um, uh, then, you know, I, I started to wire offices for networking. Um, and then, um, I changed jobs and went from Department of Social Services to the Department of Health and a place called the, um, Administrative Tribunal. And what that was was, it was the, the, um, enforcement board for the health department, for restaurants and food prep and, you know, a bunch of other things. Basically, they would have, uh, inspectors go out to restaurants and if they found, uh, a violation, then they would fine them and they would have to come back to our office to, um, sit through a hearing and so on.
Um, when I got there, it was a, it was a completely manual process with a Wang Mini computer, um, that basically was just a big, giant word processor. I looked at this and I, you know, I've always liked to tinker with things and, and learn on my own. I had a little bit of a programming background, um, that I had started on my own. And, um, so then I started to apply that. Um, I wrote a program to take the office that was, um, all manual and automate it. So digital transformation back in 1989. Um, and, um, then put in the network to make that happen as well. And at the end of the day, um, you know, completely changed the processes in that office as well as, um, digitized everything. And, of course, um, our, uh, uh, productivity went up a great deal. Um, so did our accuracy. Um, so that really set the, the, the hook in me, if you will, that this is what I wanted to do. I was able to, uh, do something, create something on my own that affected the jobs of the people around me and made their job more exciting, made them enjoy what they were doing a bit more. Um, so I was very happy with that. Um, so I stayed there for a number of years. Um, and then, um, I, um, uh, uh, moved on from there to, um, Metropolitan Life Insurance Company, uh, which is a big, uh, insurance company in New York, and it's here in North Carolina as well.
Um, but I started there as a systems analyst. Um, I was, um, married at, I'd just gotten married and had a child on the way, and I was like, okay, time to make some money. It took care of a family. Um, and so I, I went there, started as systems analyst, and basically what that meant was, um, I would write up specifications for reports and for applications. Um, it was all of the applications, uh, at that time were all, um, COBOL or, uh, RPG, all mainframe applications, so, which I didn't have a background in, so I had to learn all of that. Um, and, and I did, um, a year from there, I, um, started to program, so I became a COBOL RPG programmer and did that for a number of years. Um, but, you know, I, I had always played around with the PC or client server or, or those kind of, of tools, mostly because I really liked the interface. And around 91, 92, I started playing around with this thing called the worldwide web. And, um, I started writing applications for that in various languages. And, and, um, I, I just really liked the environment. What I really liked about it was the ubiquity of that environment that, um, you could write an application, um, from where you are and have it visible and, and used any place in the world. Um, I thought that was fantastic, um, and something that I had always wanted to do. Um, so I did that for a, a while. Again, taught myself how to program in various languages. Um, I think after about two or three years I was programming in a language that's very popular now, uh, called, um, PHP.
Lydia Kumar: Mm-hmm.
Bill Brown: And, um, I got very good at it. As a matter of fact, I used to teach classes in it, in in, um, uh, back in the mid to early nineties, um, and wrote some fairly large systems. Um, I started an ISP business. I was still working for MetLife, but like I told you earlier, I, I don't know how to sit still. Um, and, um, I, I ran that business for about, ooh, 10 years. And it was, uh, uh, providing hosting services to companies, but also providing, uh, web-based applications. Um, so again, did that for a number of years, still working for MetLife. I went from a, a, um, a mainframe programmer to then a client, server programmer. And I was doing a language called PowerBuilder, um, and was having a great time and doing other things like, uh, Paradox and, and other, uh, object-oriented languages. Um, and then I decided that our process for what we were doing was, you know, a little antiquated and, um, uh, there was a lot of latency in it, meaning it took a good deal of time to look up information and provide claims and, and do a number of things. So I put my innovation hat on and I created a client server application, uh, that used the mainframe as the back-end server. Um, and that's where all the data was. Um, so I had to, you know, create the, the protocols to go back and forth. And long story short, we rolled it out throughout, uh, the country. Um, to my surprise, people liked it. And so, um, so that went on, uh, quite well for a while.
Um, and of course then I was asked, uh, if I could do some additional, uh, um, uh, innovation in and around reporting. And, uh, this is about 96, 1996. Um, um, then I got into data warehousing, um, and, um, and building data warehouses, building data marts and then building the applications that, uh, would work off of the data mart and, and, um, data warehouse. And that was, that was, you know, a lot of fun. But, um, I still wanted to program on the internet. I still wanted to, to, um, do that kind of work. And, of course, 96, 97, it was booming. Um, and so, uh, I had a couple of offers for, for, for some companies to move elsewhere. Um, and my kids were little, they were in school. They enjoyed what they were doing. I didn't wanna move out of where I was. Um, so, um, I got an offer from Deloitte Consulting, um, and I, uh, uh, uh, you know, uh, I accepted it and went on, uh, with them to run their, um, internet business in the Northeast of, um, the US. So Upstate New York, uh, Western Mass, Vermont, New Hampshire, Maine, up that way. And that was pretty cool. Uh, I liked that quite a bit, um, but still there was something missing, right? And, uh, as I would, when I was younger, I had a couple of, uh, family members, cousins that, um, worked for IBM, um, back in the early eighties and seventies.
Lydia Kumar: Mm-hmm.
Bill Brown: And I was so impressed by them and what they did and, and, uh, what they were able to be exposed to. Um, and it was always a dream of mine to go there. Right. I thought that that just wasn't achievable for me, that, you know, I'm, I'm not that good. You're not trained. You don't have a degree in computer science. You'll never get hired there. Um, and I'll talk a little bit about my background that, that kinda gives, um, maybe some others can, can, uh, uh, uh, have some affinity to it or, or identify with it. But, um, you know, I, I, I didn't think going to IBM was, was possible so. One day while I was toiling away at work for Deloitte, my wife saw a ad, uh, in the job board for IBM and she applied for me. Um, she sent them my resume. She wrote everything up, didn't tell me anything. two, three weeks later, I get this call and they want to interview me. Okay. Um, I said, yeah, I'm interested. Sure. Um, where are we gonna do this? And they said, we'll send you a plane ticket and a car will meet you at the airport. And I was like, they must have the wrong person.
Lydia Kumar: You were really underselling yourself.
Bill Brown: I wasn't selling myself at all. Um, so I was like, wow, okay, great. I jumped on a plane, flew down to Atlanta, um, uh, limo was waiting for me as I walked out. Guy had a plaque holding up a plaque with my name on it, and I went to the interview and, um, I was honest about what I did and what I didn't do and, you know, uh, my background and so on. And then to my surprise, they offered me a job. Um, I was beside myself with, uh, with surprise and joy. Um, when I got hired by IBMI made a promise to myself again, um, kind of a imposter, uh, syndrome that you hear about, a good deal. But I made a promise to myself, look, I am not going to quit. No matter what happens, I'm not gonna quit. They're gonna have to fire me, they're gonna have to throw me out. Um, and then, 25 years later, they asked me to retire. And through that 25 years, um, I, uh, grew so much. I learned so much. Um, I have traveled the world. Uh, I've worked on every continent, uh, on the face of the planet except for Antarctica and penguins don't hire guys like me. Um, uh, and, and, and really, and lived on three continents. I've lived, uh, in South America, in Africa and in Europe, um, and did some fantastic things when I lived in Europe for about four years as the chief architect, uh, and architectural leader for Central and Eastern Europe.
So I lived in Prague, but my territory was everything from the Czech Republic out to Azerbaijan and everything in between. So Russia, Poland, Ukraine, everything, Baltics to the Balkans and everything in between. Extremely interesting time, um, sometimes extremely difficult. Um, I had some people on the team that I created that, you know, five years before I got there, they were shooting at each other. So, you know, it was, it was, it was an interesting time, especially interesting navigating all of the different, uh, ins and outs of culture. And that taught me a great deal, um, taught me to be extremely resilient. Um, taught me to be, um, innovative but more innovative than just technology, innovative, uh, or innovation. It taught me to be innovative with how I dealt with people. It also taught me that, I need to understand those folks, people that I work with more than they need to understand me. If I understand them, then I'm going to get my message across and, um, I will be able to accomplish my goals. My goal there was to build a 40-country, um, architecture team, um, across all of the regions, as many cultures, as many languages, um, to, um, work as one team, uh, to, uh, provide support for, uh, for that region. And I did. As a matter of fact, that organization is still in existence today.
Um, like I said, uh, while I was there, they also made me, um, the, uh, chief architect and CTO for cloud computing, uh, for the growth markets. So they used to call them the BRIC countries, um, Brazil, um, Russia, India, and China. Mm-hmm. Um, and my responsibility was to move the team and, um, move our customers to considering cloud. This is, 2013, 2012, so quite early on and that was extremely interesting as well. Um, 2014, right after Ukraine was invaded for the first time, um, I decided we had enough and um, um, we came home. So I was there with my, uh, three kids and my wife and they had a great time. My three kids, um, went to school there as well. My oldest only spent a year there 'cause he was in, in, um, uh, university here. But they had a great time. It opened up the world for them, um, and something that they carry on with, um, or, or carry with them until this day. Um, you know, good thing about going someplace else and living someplace else where you are different is you as you have to assimilate, right? You have to be able to fit in and, um, all of your preconceived notions about how people are and what they do and how they think they melt away. And you realize that there's much more similarities between you and them than there are differences. Um, so it makes the world a lot smaller and makes you a, I think a global citizen. Um, so that, that was fantastic. Um, great experience for them was sometimes quite difficult for me. Um, I've got stories that will curl your hair, but, um, too long to talk about those now.
Um, when I came back to the US, um, I, uh, you know, got back into a, wanted to get back into a role in cloud computing and in, um, uh, in application development 'cause what I was doing in, in Europe was mostly around infrastructure. Um, so I came back, um, at the time, um, there were a couple of hot trends going on. Uh, before I left, I was the, before I left to go to Europe. And I, my role in IBM was a CTO for, uh, something called SOA, which is service-oriented architecture. Uh, my role, I wrote a book on the topic. I've taught, uh, taught it for about 10 years at University of California, San Diego, the Rady School of Business, uh, MBA class. Um, I've got about 16 patents in that, um, and delivered it literally around the world, um, to Walmart, Citigroup, Bank of America, uh, Lloyd's of London, you, you name it. I delivered it to a number of, of folks. And when I came back, when I went to Europe, it was a complete shift from what I was doing and a shift into something else, uh, which also taught me to be resilient. Um, it taught me to take risks. Now this is a bigger risk than I had imagined, but, um, through the, through those risks, you find a way to, to, uh, make yourself successful and to stretch yourself. Right. Um, and, and then learn more.
Um, when I came back from Europe, I got back into application development, um, and, and got back into customer-facing work. Um, and they asked me to run a practice for, um, uh, for cloud, for cloud computing, but for cloud application development. And so I did, um, I, uh, introduced or started to introduce the team to something called APIs, um, developed that quite, um, made that, uh, quite a robust, uh, undertaking then did microservices 'cause they fit together, which is really what SOA was supposed to be in the beginning. Um, and all of that led to, um, the start of my journey into AI. I know you were wondering, when is he going to get to AI? So, that started my journey into AI. And what I saw with AI was, um, uh, I had the same kind of light bulbs go off that I had when I started working and building internet applications. Um, you know, my thought was, wow, look at the possibilities here. Look at the utility here. Um, especially if I look at and use AI as another component in application development. Um, so 2015 or so, I, I, um, was running a global team, started training everybody up in, in, um, in artificial intelligence. This is kind of before we were calling it generative AI. Um, uh, so, you know, started to do a good deal with that, got people trained and really started to, to point them to, um, let's use this and how we develop customer-facing applications. Um, uh, and, and yeah, we, we, we did that for a while. We made that successful. Um, as things developed, of course, generative AI started to come to the fore around 2018, 2019. And, um, uh, we were really ramping things up there. Um, but IBM being IBM, you know, they at, at, at times they take a little bit longer to embrace, uh, new technology. And it that, that's wise that it, it's risky to make that kind of change. Um, uh, so, um, you know, we were starting to do things but not as much. Um, I think at the time I was, uh, running a large project as a CTO for Boeing. Um, and I had started to, uh, introduce, um, some portions of AI there in their transformation from, uh, all on-prem applications to, um, to the cloud and the consolidation of their data centers.
Um, what I did with AI was to, um, collect information on their various data centers and how they processed so that we could consolidate them all in a, um, optimal environment, um, uh, on the cloud. So needed to understand how the applications worked and in particularly how they performed and what data they produced, um, so that we could, uh, get and develop metrics. And that's what it was mostly about at that point. Um, I did that for about a year until February, 2020, and we all know what happened then. Um, as a matter of fact, when it was announced that this is a pandemic, um, I was in either in Seattle or in um, uh, San Diego. Both were hotspots. Um, and, um, we just decided to shut everything, like everybody else. We shut everything down. And so, um, so that, that was the end of that. I finished up the project remotely and, um, then they assigned me to do the same thing I did globally, but, uh, now for North America. Um, but not a lot of work, um, because we're smack dab in the middle of the, um, uh, uh, pandemic. So a good deal of training and teaching of a team to bring them up to speed. Um, the biggest thing for me was let's get a glimpse into the future and what we need to prepare for in the future, and let's start to make the, the team, the, the folks that do the, the real work, um, uh, capable of surviving, thriving in this new world. Um, so we did, and we did a number of, uh, uh, uh, projects there that were more internal, but some that, uh, were outwardly facing. And that's kind of when we started to use some generative AI capability. We started with IoT, which is Internet of Things to collect information on various devices, temperatures, all kinds of stuff. Um, and then used AI to trend that information and look for patterns that would, um, help us to predict outcomes for both applications and for systems. Um, we had others that were able to use some of what we were do doing there in financial services as well to, again, predict shifts and changes in, in markets and commodities. Now, if I was smart, 'cause I'm not smart, I would've used a good deal of that information to, um, uh, to invest in a number of things, but eh, I didn't. Um, but, um, it was a great learning experience, um, and um, and I learned a great deal for, uh, from it.
Um, 2024, um, is when, um, you know, we, everybody starts to recover from COVID and people are trying to get back to normal. Um, I, I, in that four years, I had hired about 150 people and now the company's downsizing. So I probably had to, fire about 75, 80 people. Um, and not for cause. So that, that's always difficult, right?
Lydia Kumar: Mm-hmm.
Bill Brown: It's just, you know, we don't have the work for you, especially for these folks. I knew them all. I hired them. I in, uh, interviewed them. I placed them in their jobs. I trained them. Um, I knew they were good or I wouldn't have hired them and to let them go because we didn't have the sales was, was, was hard, um, but did what I needed to do. Um, and I could see the writing on the wall, right? Um, eventually the bell is going to toll for me. And, um, in April of 2024, that, but Bell told I had a, I was asked, asked to retire. Um, and so I did, uh, my last day with IBM after 25 years was, uh, May 1st, 20, uh, 24. My first day with my new company was May 1st, 2024. That new company was a, um, venture capital company in, uh, Silicon Valley where I was the CIO. And it was very interesting work at first. Um, but, um, like I said before, I don't know how to sit still. I am, don't know what the word retirement means. Um, and, um, uh, so, of course, I went out right away to find something. Um, and I did, which was this venture capital company. Uh, and it was fun. It was interesting, uh, for a while, but, um, there was some differences of opinion, um, in how we were, uh, progressing and what we were doing. And one day I woke up and I looked myself in the mirror and I said, what are you doing? You're doing the same thing that you've done for the last 30 years. Why are you doing this again? What do you want to do? And I said, well, I don't want to do this. And I left that position and I took about two months to, um, to kind of re-evaluate where I, where I was and what made sense for me, what, um, would make me happy. Right? Um, I always loved doing my own thing and running my own business. Um, but I also wanted to be able to make an impact. Um, and so, um, so I made a decision to start my own company, uh, and to start my own projects. Um, but I put some caveats in on that, which was, um, uh, anything that I get involved in has to help people, has to expand the greater good, if you will. It has to be sustainable. And it has to be profitable. If it's not profitable, it can't be sustainable. So anything that I get involved in, um, has to meet those three criteria. Um, if not, I, I don't get involved in it.
Um, so fast forward from July, August of last year to now, um, started two companies. One was a consulting company. It's called, um, Application Engineering Services. We do, um, all kinds of AI, all generative AI, all based on, um, uh, an application focus. Um, we, of course we do digital transformations. We modernize existing systems. We, um, uh, help, uh, uh, companies, um, uh, ingest and, uh, thrive in new technologies. And, um, that's been very successful. Um, I also met a number of, um, very interesting people. Um, uh, a mutual friend of ours, Jim was one of them. And, um, and I, I, I realized the power of, um, people's lifetime experience and how that is always surprising. Um, and so I talked to a couple of these folks about some of my ideas, um, and they helped me bring these to fruition. So started a product company as well. And right now I've got on 2, 3, 4 products that we're working on. All AI driven, all AI centric, um, but not, uh, AI or Generative AI from the chat, GPT type it in and a prompt, um, uh, perspective, um, in a, from the, the future of AI, which is integrated within the way we build systems.
Lydia Kumar: Mm-hmm.
Bill Brown: So we build a lot of, uh, AI agents, um, we build a good deal of, of what they call CPS. Um, uh, which are model content, uh, protocol that, uh, enables me to use AI as another data source or another intelligent, um, uh, application that I can route to a number of other things. Um, basically what it's been able to do is take all of my past experience and combine it into this one thing, and it is an extremely exciting time for me. I am an, I haven't been this happy since I have my first child. Um, I, I'm really, really enjoying this time. Um, I'm enjoying being able to work on what I want. Making sure that it meets those three criteria. I am really enjoying the people that I'm working with. Um, a lot of the stress that I had throughout my career has kind of just melted away and, um, it's, it's really been a fantastic time. So you asked me for a brief intro and here I went on for almost, uh, 30 minutes. I apologize. Let me stop and let you ask questions.
Lydia Kumar: Well, you know, one thing, when you were telling your story, I thought about digital transformation being so key to, to all of it. Um, when that first story about that one computer you had for the, the health system and how you were able to take that technology and revolutionize the experience for the people around you and how that, as, as you talk through all these different experiences that you had in your life, I kept thinking about that one story and how you were able to, whether it was building a a system or building a team, you're really focused on how do I transform this, this thing that I'm working on to make it work more effectively? And how do I take the, take whatever ex that exists and allow it to operate at its fullest potential? And so that was something that really resonated throughout, um, throughout that story of your life. Yeah.
Bill Brown: Yeah. It, it, it is the thing that's always set the hook for me as well. Right. How can I make it more efficient, make it better, but more importantly, how can I make the experience better for the people that have to work with these things day in and day out? Um, because that will expand their knowledge, that will expand their interests, which will in hopefully provide some additional happiness.
Lydia Kumar: Absolutely. Do you feel like there's things with generative, with AI as a technology, do you think that technology in particular has changed how you see digital transformation? I know you've, you've had a long career and so you've seen, you've seen many types of digital transformations over time. Do you feel like this is different or do you feel like it's the same as the transformations that you've, you've led or experienced in the past?
Bill Brown: No, this is, uh, completely different AI, generative AI, uh, of which we're just in its infancy. So let me stop there and let that sink in, uh, sink in for everybody, um, is a real game changer. Everything else that came before were, um, we're large steps forward in efficiency and, and, um, in computing, but, um, AI is a giant step, um, kind of, well, it's bigger than the shift to the internet, um, but sort of like that kind of game changer where the internet, as long as you had the knowledge and the training kind of, of, um, uh, lowered the bar of entry, right? So anybody could participate. As long as you had the, the knowledge or could learn it, and on the internet you could learn so much on your own, um, as long as you were open to learn it. Right. Um, and so a lot of the barriers for people to be employed and for people to be successful, um, diminished quite a bit. Um, AI's doing the exact same thing and, um, it, it, it is, as long as you understand it and it's not rocket science, it's, it is not something hard to understand. If a guy like me from Southeast Queens, New York could, could get it, anybody could get it. Um, but then, um, when you couple that with your innate imagination and innovation, you can do some, some quite impactful things. So yes, this is a, a real game changer and, um, like I said, we're in its infancy. I know a lot of people fear this, um, like, what was the name of the movie series, the Terminator, right? We're all gonna go, um, be in the singularity. That's not gonna happen. Um, we will always need human intervention within AI. Um, AI and AI systems, generative AI. Some people, uh, talk to as smart or intelligent. Um, and yeah, we call it artificial intelligence. The artificial piece is, I am simulating intelligence, but those systems will never have the intelligence that a human being has. Um, because they're not going to be self-aware, they're not going to be precedent. Uh, they, they, they can't innovate and put together the different variables that a human can, which is also, um, a testament to the diversity of, of, uh, mankind. Well, I'm getting all philosophical about don't mean to do that.
Lydia Kumar: I feel like, uh, that's one thing I love on the show is that I think, uh, artificial intelligence is something that can feel very technical and inaccessible for people. But these questions of like, what does it mean to be human? Or how do we bring our diverse experiences together? Like what makes us different from a machine? I think all of those questions are, are really resonant with a wide audience and people are eager to think and talk about those things.
Bill Brown: Yep. Very true. Um, that was...
Lydia Kumar: Part of this, some, a lot of our listeners on the show are in the education sector. And so one thing, whenever I talk to someone who is, is outside of education and, and in the broader workforce, I'm curious about what you see as the skills that schools need to be focusing on now for, for the future that you see emerging with AI.
Bill Brown: Okay. Um, I have some, uh, pretty well-defined opinions on this. Okay. Um, so you can read into that opinionated, um, first and foremost, so I'll, I'll give you the harsh opinions first. If you are in school, grade school, middle school, high school, university, and you are not learning about AI, you are missing the boat. So do whatever you can to learn about it. Now, there are unlimited resources for you to do this on your own. Um, take the 10, 15 minutes, half an hour out of your day to focus on that, on learning something about this, just learning what it's about, kind of how it works, um, and, um, that will, uh, put you in a much better position to be successful. Um, we are in the midst of a complete, uh, labor workforce and career shift, and that's driven by, uh, Gen AI and AI. Everything that we do today, every job, every profession, um, will be impacted by this. Um, and you've got two choices. You can be afraid and hide in the corner, um, and wait for the inevitable to happen. Or you can do what I think is a smart thing, is to learn as much as you can about this and then participate. When you do that, um, you are going to be heads and shoulders above others that have chosen not to do it. Um, and so, um, from an education perspective, this is something that we absolutely have to enforce, force, let me change that word, force. Something that we absolutely have to encourage everybody to do, especially young folks, right? Um, and not to be intimidated by, by this. Um, I, I grew up in, in, in, um, Southeast Queens, New York, and, you know, Jamaica, Queens, New York, not the best of neighborhoods, um, got worse over, over time.
And, um, you know, everybody, there was, I shouldn't say everybody, but a prevail, uh, prevailing sentiment was you're not going to, to, uh, amount to much. Um, you know, you, the expectations for you should be lower because of where you came from and your economic position and the, um, resources available to you. Um, and I, like about a lot of other people brought into that lie. And that's just what it is. It's a lie. Um, what I do, how far I go is completely up to me and how I, um, execute, how I go after what I want. Of course, that means I need to understand what I want, um, need to have a, have exposure to what the larger world was, right? Because you don't know what you don't know, and until you know something, you don't know what to go after. Um, so that exposure is, is, um, extremely important. And then having the, the, the confidence to put, push back on that lie that says, you know, you can't do this 'cause you come from an inner city. You can't do this because you come from the Appalachian Mountains. You can't do this because whatever the roadblock is that, um, have been put on you, it, it, it, it, it's a lie. Forget that. Put your best foot forward, um, and, and walk in that direction from an AI perspective and from an education perspective. Um, AI and generative AI is the most powerful thing that I've seen since the beginning of the internet and the ubiquity of information, um, to help people, um, transform themselves and their skills.
I believe in that so much that one of my products is an AI-centric training and teaching tool that, uh, provides a coach, that can teach any topic, um, to anybody one-on-one. So imagine having a personal coach that you can talk to 24 hours a day, seven days a week, that doesn't judge you, that, um, does it, that will answer all of your questions. Even if you ask the same question 30 times will help you understand what you're asking and challenge you to move forward with exercises and ways to practice it and so on. Um, I think that turbocharges education, both from um, elementary school to middle school to high school to university, but also in the workforce where people need to be able to transform what they do today, whatever it is to meet the needs of the future. So from an AI perspective, absolutely critical from an education perspective. Um, this is something that we need to embrace as much as possible. So hence why I developed the, um, uh, developed the tool. And we are working with a couple of, uh, community colleges, uh, in, um, uh, in North Carolina and, um, couple of other colleges like with the Native Americans as well, and want to continue to grow that now go into, um, the private sector to transform, um, uh, help people, uh, redefine their careers and their jobs, um, and be productive again, most importantly, um, to give people that confidence that they can do it 'cause they can. If I could do these things, anybody could do it.
Lydia Kumar: I feel like education and access is a big part, like something that you're passionate about as you've told a little bit about your story, and you don't only have a product, but you've also, you're also teaching a course. Do you wanna talk a little bit about the course that you, you're, um, pro your offering?
Bill Brown: Yeah, thank you. And, um, we'll, uh, offer a link to it as well. Um, it's on Maven, which is, you know, a, a teaching platform for, for uh, uh, almost like a TED Talks. Um, but more from an education perspective. Um, I am teaching a class in the, in building AI systems, um, using the tried and true architectural methods that all systems have been built on since they've been building systems, um, because it's the same. Um, AI, generative AI is another input into this. So, um, I am teaching this class with a very good friend of mine, um, and a mentor of mine, um, from back in IBM. I've known him since, uh, 2005. Um, you know, for me, everybody needs a, a mentor, uh, needs a number of mentors. Um, but, uh, and I've had a number over the years. Um, but, but this particular guy has, um, really turned the lights on for me in a number of areas. I said before, you don't know what you don't know, right? And you don't know that you don't know what you don't know until somebody shows you what's available on how big the world is. So this guy did that for me. And of course my responsibility is to do that for other people as well, and I try to continue to do that.
The course is, um, teaching how to build AI systems. Um, and, um, the, I think we've got seven types now of different AI systems and applications. There's agentic AI, there's AI that uses, uh, AI agents and MCPs, kind of like a router and, and so on. There's a composable AI. There's, um, like the ChatGPTs, there's AI for multiple different, um, uh, purposes, education, medical, um, finance, so on and so forth. And each one of them, um, should be built differently. So we've developed some patterns for how to build each of those systems, and we'll be teaching those patterns. Uh, the, the friend that I mentioned and, and kind of gushed about a little bit, um, is, um, former IBM fellow. Um, I was an IBM distinguished engineer. Um, IBM Fellows, the highest technical position you can get at IBM. Um, he, he left there, went to, uh, United Healthcare, Optum as a fellow there, and a senior VP left there and went to Google. Um, same type of position in, um, uh, at ho at, uh, Optum and at Google. His focus was on healthcare, AI and healthcare and developing, uh, AI systems in and around healthcare. Very interesting guy. He speaks all over, um, Stanford, MIT, Princeton, Harvard, every place. Um, it name is Kerry Holly. Um, so he and I are teaching that. Um, I'm honored to be teaching with him, um, and I hope he's honored to be teaching with me.
Lydia Kumar: It's so cool that you've been able to, you've had this really long career where you've kind of collected these experiences and built relationships with people that you've been able to execute and kind of expand the impact that you can have in a way that feels, uh, true to true to your values and who you wanna be, which is, is a really, must be a rewarding experience to be able to have right now.
Bill Brown: It is, as I said, I am having a great time, having a great time. I haven't had this much fun in a long time.
Lydia Kumar: That's amazing. Um, and what, like, what a gift that you're able to give to those around you and, and for yourself as well. Um, okay. I am gonna ask you my last question of the show. And I think, you know, AI sparks a lot of big ideas and questions for people. And so I'm curious for you when you, what idea or question about AI, all diff seven different types is really sitting with you right now, and is that sparking hope, concern, curiosity? Like, what are you, what are you thinking about?
Bill Brown: Wow. Um, there's so many different angles to that question. Can I take it from a concern? Perspective and a positive perspective.
Lydia Kumar: Yes, absolutely.
Bill Brown: I'll do the positive first, because everything should be positive and I, I firmly believe here, I'm gonna get philosophical again, that everything in this universe and on this earth bends toward the good. Yeah, you're gonna run into some bumps along the way. They might be big bumps, but eventually it bends towards the good because, that's what's sustainable, right? Uh, the other stuff isn't sustainable, so I'm not gonna do the positive first. I'm gonna do the negative first. What I'm concerned about is, um, a small number of people harvesting and, um, capturing the use of this technology for their own, selfish needs, using it to manipulate and control others. Unfortunately we've seen that, and we will continue to see that, right. Um, we we're going to see, and what we're seeing now is people, uh, enabling themselves to amass great wealth, through the use of this tool and how they apply it. That I think leads to, um, um, a, a number of problems that just aren't sustainable, right? Um, it, it doesn't advance all of us as a whole. So that, that's an issue. Um, I, I think, um, in order to, to do that, some people will continue to, uh, cloak this in fear, um, and, um, try and keep people away from it so that, um, they don't learn what it is. Um, you know, knowledge, uh, dissipates fear, right? And so when you know about something, you, you, you don't fear it anymore. Um, so, so that's, um, that's my biggest concern, that this will be corralled by a, a small few and used just for their benefit, not for the benefit of everybody else. And when that happens, it will not only not be used for the benefit of everybody else, it will be used for the detriment of everybody else. And that's very concerning.
Um, the positive piece is, um, right now we have a window open. Where a good deal of this information and the opportunity to learn about it is wide open. You just have to reach out and grab it. And so many people can do that. If they do that, then they will dissipate the fear among yours, if you will, that want to control this and, and make it their own. Um, this will lead to, um, all of us advancing using this new technology. And so now to get a bit more specific on the positive, um, I, I see huge advances in education. Um, I see huge advances in, um, leveling the playing field across the world, um, which will lead to, um, a more ubiquitous society that leads to less scarcity, less desperation, all of those good things. Um, because people then are empowered, um, I see this happening in healthcare and education, um, in, in finance, um, in agriculture and the things that we need to do to sustain ourselves in a small little planet and small little corner of the universe. Um, we will find the ways to, um, use AI and the next big, big wave, which is super supercomputing or, or quantum computing.
Lydia Kumar: Mm-hmm.
Bill Brown: To solve the most intricate and puzzling problems that we face today. Like, um, climate change and destruction of our environment and how we can deal with that, um, hunger and disease. All of these things that have always crippled, um, mankind, we can start to identify those things, work the problem and solve them. I know big, lofty ideas, but if you, if you just think about where we are at the turn of the, um, 19th century into the 20th century and where we are today, I mean, the possibilities are endless. Um, again, we just need the motivation to go out and make it happen and the, the, the confidence, the wherewithal of each individual to go out and educate themselves and play, uh, their part again, back to education, I think. Huge opportunity to use AI. It's why I'm building this product and this company. I'm doing something similar with AI and education in around sports, um, and how amateur athletes can better themselves in whatever they do, um, and create ecosystems of support. Um, again, I can go on forever. The, the, the future in this is very bright, but our responsibility, each and every one of us, our responsibility is to go out and learn this, um, get familiar with it. It is not hard. It is not rocket science. Any AI system is built on data. That data comes from various sources that you and I supply. We need to make sure that that data is accurate and non-biased. Um, because one of the dangers in AI is if you tell a small little lie here, it gets propagated over all of the AI systems and the world very quickly. So have responsibility in what you do. Um, use AI in an ethical manner. Help people help the greater good, sustainable, and profitable.
Lydia Kumar: Well, thank you so much for sharing that perspective and helping, I think everyone see the importance of participation in this new technology. Um, because everyone's participation creates a safer and, um, a, a safer and more democratic approach to how the technology is used. So really appreciate all of that perspective. And for your story. You have so many experiences watching technology change and evolve. And so your strong, uh, conviction that this technology, this is a different kind of technological innovation, I think is, is really something because you've seen, uh, you saw the internet come into being, you've seen, uh, per, you know, cell phones and personal computers and all of these different things throughout your life. And so, um, seeing AI as more revolutionary than those other technologies is, is, is telling. And I think probably a lot of people feel that way, but not everyone has the same perspective that you do. So thank you for sharing it.
Bill Brown: Thank you for having me. I've, I've enjoyed this. Talked about my favorite topic, which is me. Just kidding. Just kidding. But thank you very much. This has been very, a lot of fun.
Lydia Kumar: That was such a powerful conversation with Bill Brown, a true testament to the idea that technology is only as transformative as the people who wield it. I was particularly struck by his deeply, I was particularly struck by his deeply personal story from his roots in Queens, New York to his global work at IBM, and how his passion for making systems more efficient and experiences more human has been the through line in his remarkable career. His vision for AI as a tool for leveling the playing field and empowering individuals rather than a force for control, is both inspiring and a critical call to action for all of us. To dive deeper into today's topics with Bill, I put everything for you in one place. Just head over to the resource page for this episode at kinwise.org/podcast. There you'll find the full transcript, links to Bill's Company and his Maven course, and a list of resources inspired by our conversation for the school and district leaders listening. If Bill's insights have you thinking about how to build a real AI strategy for your teachers, I invite you to learn more about the KinWise Educator PD pilot program. We partner with districts to select a topic that's meaningful for your teachers, and together we build a community of practice that continues to support them long after our work together is done. You can learn more about our approach at kinwise.org/pilot. Finally, if you found value in this podcast, the best way to support the show is to subscribe. Leave a quick review or share the episode with a friend. It makes a huge difference. Until next time, stay curious, stay grounded, and stay KinWise.
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Connect & Resources
Connect with Bill Brown
LinkedIn – William A. “Bill” BrownWatch the Course
🎓 Elevate AI Architect Skills (co-taught with Kerrie Holley)
Learn the AIscape Framework, architectural decision-making, and system design patterns for AI.
Watch on Maven (Free)Learn More About Bill's Work
Founder & CEO, Application Engineering Services
— AI-powered product development
— Digital transformation consulting
— Enterprise architecture and governance strategy
— Email at aes@3pp.com to learn more.
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1. Learn a Core AI Concept, Then Teach It
I’m a 6th-grade science teacher in Oregon. I’m preparing a mini-lesson on how AI makes predictions as part of our data & systems unit. I have 28 students, including two ELs and one student on an IEP for executive functioning.
Goals: Students should understand what machine learning is and how it differs from traditional programming.
Assessment plan: Formative—students will complete a quick “explain it back” activity.
Tech access: Students have Chromebooks and access to Google Docs.Please explain machine learning in simple terms I can understand, then help me design a 10-minute interactive mini-lesson I can deliver using visuals or examples relevant to middle schoolers.
2. Identify AI Skills for Students
I’m a high school career-tech teacher in Georgia working with 10th–12th graders. I’m designing a unit on future-ready tech skills, and I want to introduce AI literacy in a meaningful way.
Class size: 35 students, mixed tech proficiency.
Goals: Students should gain exposure to foundational AI concepts and begin building fluency with tools they’ll encounter in the workplace.
Assessment plan: Project-based with peer feedback.
Tech access: Full lab access with laptops and internet.Please list 3 essential AI literacy skills and suggest one short, age-appropriate project idea for each. Align with ISTE standards if possible.
3. Practice Prompting, Then Guide Students
I’m a middle school social studies teacher in North Carolina, new to using AI tools. I want to grow my confidence writing prompts for lesson planning and student support.
Grade level: 8th grade
Goals: Learn to write clear, purposeful prompts—and design student exercises that teach the same skill.
Assessment: Informal teacher journaling and a class exit ticket.
Tech: Students use ChatGPT in a monitored lab setting.Please walk me through three prompt-writing exercises for teachers. Then, help me turn each one into a classroom-friendly activity to build student prompt fluency.
4. Design a Student Project Using AI
I teach 10th-grade English in Illinois, and I want to create a project where students explore media bias using AI tools.
Class size: 24 students, including four reading below grade level and one newcomer EL student.
Goals: Students will compare how AI and humans interpret tone and bias in news headlines.
Assessment plan: Rubric-based project and reflection essay.
Tech access: Students have full laptop access and can use ChatGPT and Canva.Please help me design a scaffolded project outline with clear objectives, responsible use guidance, and a rubric.
5. Facilitate an Ethics Discussion
I’m a 9th-grade advisory teacher in California preparing a 30-minute lesson to introduce students to AI ethics.
Class size: 32 students, very diverse backgrounds.
Goals: Spark critical thinking and reflection on how AI affects student data, fairness, and decision-making.
Assessment: Verbal participation and a one-question reflective exit ticket.
Tech access: Minimal—we’ll do this in discussion format.Please suggest 2–3 ethical dilemmas that are relatable for high school students, and provide open-ended discussion questions to support a balanced classroom conversation.
