Digital Twin Cities, My Town AI

A Welcome to Practice Disrupted, a podcast where we find ways to create new solutions to current challenges while elevating the value of architects. I'm your host, Evelyn Lee, an architect who spans tech as an angel investor, startup advisor, and founder of Practice of Architecture. Whether you're a seasoned architect or just starting in the field, this podcast is your gateway to think differently about the role architects play within our global community. Hello, disruptors. Welcome to this week's episode of Practice Disrupted. Today I'm joined by Nicole Sterling, Mayor Potem of Nederland, Colorado, founder of MyTown AI and co founder of Woman Defining AI. Nicole's path is unlike most as an elected official. She sees firsthand the challenges of small under resourced towns trying to make decisions with fragmented data.

A That experience led her to create MyTownai, an intelligent data hub that helps municipalities consolidate information, run scenario planning, and even build low cost digital twins. Her work shines a light on how artificial intelligence can reshape civic decision making, speeding up planning, enhancing transparency, and opening new opportunities for collaboration between citizens, local governments and architects. In this conversation, we'll explore what it means to found a civic tech startup as a public servant, how my town AI is giving communities of all sizes access to tools once reserved for big cities, and what architects can learn from this shift as we think about our own role in shaping the built environment. Hi Nicole. Welcome back to Practice Disrupted.

B Thank you. It's amazing to be here the first.

A Time I had you and Helen on as a part of Women Defining AI. But now I'm having you on as the founder of my town AI. So what is your elevator pitch for My town AI?

B Yeah, so first I'm a. I'm a public servant. I am an actual elected official. I work in the public sector as a mayor pro tem. And so my town AI was really sort of born out of my own pain of seeing my own town staff just have to work too hard and have to go to too many places to just get the information they needed. And so at its core, MyTown AI is an intelligent data hub for municipal governments. We then layer that data into what we're calling our low cost digital twins so that local governments can do some lightweight simulations. They can actually kind of see the impact of their decisions before they might enact it in a city council meeting or before municipal staff takes action.

A Let's dig a little bit deeper on that. So when you talk about your team going all over the place to find information, like what is that information and data that they're looking for all over the place yeah.

B So the, the very first and most simple use case that I started with because again, this was seeing my own community planner go to three or four different places just to answer the question of what could somebody build on this plot of land? So many people don't realize that many of our under resourced local governments and some of our smaller governments, they go to the zoning map to see what the zone is, then they have to bounce it off a municipal code, so they have to go to a different spot for that. And then they oftentimes have to go to the county website to assess ownership information. Assessment information. And if that website didn't have it, they were going to Zillow to access this information. So just that one simple question of what can I build on a plot of land? Was causing my own team to go to three or four different spots.

A Yeah. And thank you specifically for using that as an example because I feel like architects feel that pain all the time. So that's very architecturally related. Even when they're working with developers or they're working with owners who aren't used to creating new buildings. What does that mean? And what are all the different areas we need to go to get resources?

B Well, yeah, and part of that was also seeing developers come into, I mean, we're a small community, we're not that large, we're only 1500 residents. But we were still seeing situations where developers would come in, they wanted to change the use, let's say, of the building that was there previously. Right. And didn't have all the information in terms of okay, if I do build something new, let's say I go from a mechanic shop to a barcade. And this was an actual real example a barcade. And I didn't know what a barcade was before this incident, but it's a bar plus an arcade. And that was going to require different water use. That was also going to require, you know, upgrading some of the piping underneath.

B The developer was going to need to pay for a new fire hydrant. And it was, you know, would have been great if that developer had had all that information beforehand before realizing that their excursion was going to cost more and just, you know, just require some nuance in the development process.

A So the other interesting thing about you though that I kind of want to bring to light is that you're also a non technical founder, right?

B Yeah, technically, yes.

A So technically you're kind of a non technical founder. So when you had this idea, how did you find the right partner to help you develop it?

B Well, and you Know, my, my other role is the nonprofit Women defining AI. Right. That's what we were on previously. And the learnings out of women defining AI and doing just a lot of experimentation with AI is it's starting to very much blur the lines between what you call technical and non technical. Some of the early prototyping I did on my own, and it was at a certain point where I realized, okay, I have the fluency of what AI can do. I see this gap in the market, in the local government sector, and what I need is a little bit more advanced architecture. And so what I did is I actually pulled in somebody who I knew within Women defining AI. That's Kavita, that's now our CTO and my co founder for My Town AI.

B But it's still having that fluency and that understanding of these AI architectures. And even though if you don't, you know, many of our team members on the engineering side are software developers, but we're also training them to automate their roles to essentially, you know, create the AI agents that would make their jobs obsolete. And the reason why we want them to do that, though, is to then go and focus on other things. Right. The high level, the architectures, the efficiencies and everything. But even though, you know, you could technically call me a non technical founder, having that fluency is still super helpful, I think, especially in this generative AI race everyone is going after.

A Yes. And I think we could have a whole separate conversation in addition to the WDIA podcast episode that we have about the importance of reskilling right now to cover that. I know there's a few architects listening right now that saying, she's using architecture wrong. So just because of my audience. So when you talk about architecture, and I don't think architects fully understand this, but when you allude to architecture, can you help them kind of understand what architecture you're talking to or about?

B Yeah, and so architecture from like an AI standpoint, Like the back end.

A Yeah, architecture from an AI and technology standpoint. Because I imagine, one, that there are a few listeners that just like, check that out completely, because they're like, here's a tech person talking about architecture. But two, I think I would love for architects to understand a little bit more about why they use the term architecture and tech.

B Yeah, yeah, we're on the back end of these AI, any type of software solution or application. You are essentially creating the scaffolding. And we do, we call it an architecture because we are building, we are having to modify, we're having to create the foundations and the environment through which our software applications work. And so, yeah, then I think that's, it's interesting too when you start to kind of think about the nomenclature of why we call software engineers engineers. That was probably came out of building engineers and actually creating physical products, but now we create sort of these non tangible, these software programs.

A Thank you for taking that tangent with me. Back to my town AI, though. You mentioned at the top of the episode about how my town AI can actually potentially run scenarios about decision making processes. Can you talk a little bit more about what type of scenarios MyTown AI could potentially assist with?

B Yeah, and a lot of this had to do with my own awareness as a municipality government leader and also knowing how the digital twin industry, it's. I mean, it's very, very expensive to create a digital twin. And I think that's because our understanding of what a digital twin should be is skewed. And while you can run a drone or a car with a camera down every street and take these very photorealistic, you know, this photomemory of your town as a government employee and as a government servant, that's not necessary. I need to know where certain things are, such as roads and buildings. And then from there I want to be able to run some lightweight simulations. One of them that's very common within local government are zoning changes. Well, zoning changes can have a lot of impact into the future if you change one zone to another thing.

B And this was an exact situation where my own planning commission was being pressured because of the needs for affordable housing. And I talked to a lot of towns across all of the United States. And this pressure is real, from our smallest communities of 300 people up to our largest metropolitan cities. And so our planning commission was being pressured to change our one parcel of industrial light industrial zoning to high density residential. And in good fashion, our planning commission, they debated it, but then they kicked it to a consultant to ultimately advise them on, which is, you know, another thing that's a common practice. And at the same time I was developing MyTown AI and I was super curious. I was just like, what, what would my town AI say? Because, you know, in many, many regards I see my town AI is helping point to our municipal data and empowering us with brainstorming and, and ideas that maybe we wouldn't come up with on our own, which is why we oftentimes pull in consultants. And so I ran the same scenario through my town AI and it gave the exact answer as our consultant, which is to provide a mixed use Right.

B Which it's a very simple example. And you kind of think about it and you're like, well, duh, why wouldn't you just say mixed use from the beginning? That's obvious. You can capture the sales tax, you can capture the property taxes, but we're so conditioned in local government and just paralyzed that our knee jerk reaction is to bring in that consultant. And again, I always tell folks like, I love our consultants. I'm not trying to get rid of them, but I am trying to empower local governments to look at their data, to brainstorm with their data, because usually the answer is right in front of them.

A So the interesting thing about that, I also feel like now a few architects slash nonprofit developers are like, my town AI is taking my job.

B Which is.

A Specifically why I wanted to bring you and my town AI on to practice disrupted. Because I think these are areas where architects have historically actually done and provided some services for towns. But they're also, frankly, tools that architects can, in partnership with mayors and others, utilize themselves for their own type of scenario planning. Even though I know that they're not your primary audience here for the software, they will be.

B So eventually we will have enough of these towns, their zoning, their goals, their strategic plans, and how they want to capture, you know, granting dollars or whatever that developers will want to access that information. They'll want to kind of scan across the towns and see where's the most opportunity, what's going to align my goals, what town should I, should I, should I consider based off what I want to build in this and the town's goals as well. Right. And there's, there's an opportunity to provide an ROI on both sides. You know, what's the potential ROI to the town, but also what's the potential ROI back to the developer? Because listen, local governments, we want, we want that meaningful development. We want good partners. And so to be able to, you know, kind of pull this local government data together in a way that's meaningful to outside parties like developers and even architects. That is absolutely something that we want to do in the future.

A So let's explore that opportunity because you're talking about all the different towns. And before we hit record on this episode, you gave me a pretty interesting statistic about the number of towns that are 10,000 or less people. Can you talk to us a little bit more about that and the impact that my town can have even just working with towns of that scale?

B Yeah, this was the wildest statistic that I came across when I was researching, you know, this opportunity and, and really, I didn't even. I didn't. I stumbled into the opportunity because I had asked my own town administrator at the time, like, hey, I think that we should kind of upskill the team and give them some AI skills and everything. And, and she said, great, can you find me a consultant? Can you find me, can you bring me in a consultant to help me do this? Yeah. And I, and I said, sure, sure, no problem. But, you know, I kept getting, you know, just blocked because the ones, sure, there's the McKenzie's and the Deloitte's of the world, but we're a small town, we're a municipality. But I was also recognizing another trend which is, you know, something that we also noticed in women defining AI, that until you put some of these AI workflows in front of people, it's hard for them to go and experiment. And so those were kind of two of those insights.

B But the other insight was just the sheer number. So 95% of all towns in the United States are actually considered small towns. That means they're under 50,000 people, 83% are under 10,000 people. So a majority of our towns are just sort of forgotten and left behind with these advanced AI tools, or just advanced tools in general. You know, and that statistic was just absolutely one appalling and shocking to me. And that's why, you know, sort of initially we're like, we're gonna, we're gonna go after all the small towns. We're gonna help all the small towns get these AI tools. But then, you know, there were more.

B There were middle and large towns that were also reaching out, saying, well, they were just kind of ignoring the whole small town messaging. They're like, yeah, but we need this too. And they need it in different ways. They, they need maybe sometimes more of a specialized model. Like we're talking to a few larger towns that are like, I need to solve affordable housing or I need to solve economic development. And they want, they want their own specific instance around that to. Whereas our smaller towns, they don't have the luxury of, you know, having a lot of volume of a thing, which is where a lot of software developers actually do for government is. They, they're the single app, you know, the killer app, which is a single use of one thing.

B And a majority of our small towns just can't, they can't do that. They have, don't have the volume to justify the cost. And they need this integrated data because they're wearing multiple hats. And so that's where, you know, Being able to service those smaller towns, there's more under resourced local governments and actually creating software that was going to work for them ultimately creates great software for everyone.

A So I have a question about, I mean, obviously there's always the data set that the towns themselves can use, but I feel like in scenario planning, right, you also want to bring in other data sets around anticipated growth as a for instance. So what other, what other data sets are you bringing to the table when it comes to helping them with that?

B Yeah, and this was, this was something I also experienced. So I sit on our Denver Regional Council of Governments here in Colorado and it's basically a cog, or what we call a council of governments. You know, every state has kind of an entity like that and our COG has amazing data, but it's so siloed and it's so fractioned. And if I want climate data I have to go over here and if I want transportation data, I have to go over here. And oh, by the way, it's mostly geared for like our bigger cities. And so that was one of the, you know, the insights also is just what are those other data sets? The demographic piece, you know, like growth. You know, a lot of this data is public data. That's, that's the, that's the mind blowing thing.

B It's a mind blowing thing is our local governments, you know, we're starting with, with some basics of things that you can find on their website to pull in and, and start to do some of the scenario planning. Right. I did a test yesterday on, you know, just some of our very low cost digital twin. And I said, hey, look at this roundabout, it's in Nederland. And I said, what can we do to make it safer? And you know, and those are some of the scenario planning that we want to do or not just the zoning changes. But, you know, let's talk about climate change. You know, what's, what's specific about my longitude and latitude that I should be preparing my infrastructure for the future economic development. You know, I, my early conversations was with an economic development specialist director in one of the larger cities.

B And he said, you know, the thing that's so interesting to me, Nicole, is that these cities have this sort of like follow mentality where if they, let's say, you know, a town gets their big box entity, whatever it is, you know, big box company, the town next to them thinks that, oh, I got to go get my big box entity. But really that may not be the right solution. The right solution may be that they need to come up and they start to cultivate relationships with suppliers for that big box entity rather than getting their own big box entity. Right. And this is little things that just get.

A Yes, yes. And because it sounds aren't necessarily that far from one another to cultivate those relationships.

B Well, and they're not that far away from each other. But yet the strategy or our gut reaction as to what we should do is not maybe you know, backed by the science or it's not backed by really good strategy. And so, you know, one of my long term goals for this is because I see it all the time on city council meetings and it doesn't matter what the group is, you know, your group of folks that you're trying to solve problems with is you fall into really poor decision making, you fall into your biases, you fall into these illogical rationings of ideas. And so, you know, as much as I want this to be a, let's point to our data and let's pull in some amazing external data sets, I also want it to be a platform for just good decision making because we don't get trained on that all the time.

A Absolutely. So just kind of understanding like what information is the AI model pulling to help give you ideas about what could create a safer outcome.

B Yeah. So because this is highly produced, there are things I can't, I don't want to articulate. But yeah, I mean we are going at this Digital twin in a completely different way.

A You mentioned the roundabout, but you know, could this platform be used during early site analysis or feasibility studies and you pointed a little bit to that, but to support more community aligned proposals.

B Yes. And this is, you know, eventually once we sort of get to the development face or you know, developer facing as in like building. This is absolutely that because I want developers, I want citizens to be able, you know, because there's, there is also a citizen facing piece of this as well. Where. And I'll get to that in just a moment. But yeah, to be able to do these site plannings a little bit more quickly or whatnot. One of the features that we are currently testing, it's not live yet, but if I have my low cost digital twin, I can come in and I can upload a development plan and within minutes, you know, get a reading as to whether or not this is going to meet code. Right.

B Like we've already tested that, that's, that's absolutely feasible. And especially in a lot of our under resourced towns there is usually a planner of one, maybe two. And so to be able to have some of that offloading and you know, the reducing of friction, that is absolutely one of those areas. But even before that. Right. Just sometimes it's just the questions, the back and forth over weeks of what can I build here? What does the code say? To put that in natural language so that people can understand it a little bit more. Because no, no citizen I have not met. Well, I've met one who actually likes to read municipal code.

B But she's, she's a savant, she's beyond, you know, the common, the common folks. But yeah, it's absolutely, you know, to make that more accessible so that folks can plan that can understand and then once it comes time to submit those plans to have technology helping you along the way just reduces the friction and hopefully speeds some things up. In local government.

A There'S a lot of concern about the hallucinations of AI models and stuff. So how do you get over or what are the biggest barriers that you see from elected officials that are not necessarily on the AI bandwagon when it comes to adopting a tool like MyTown AI short of bringing on the consultant and making the comparison of the consultant outcome versus the, the tool outcome.

B Yeah, that's a. Yeah. Maybe we should have a beat the consultants sort of, you know, competition. No, so we, because we already do, we always do that. We already do that behind the scenes they have to try to beat me in, you know, new features that come out and I test them. Right. Because I'm the subject matter expert. But anyway, you know, listen, it's just like any other industry.

B There are some folks that are going to be willing and open and because they know that technology is going to help their under resourced communities and especially their staff and so they're going to be open to it. If they're not open to it, I'm not there to try to convince them. Like that's just, I'm not going to do it. The we are seeing across the board, not just in local government but in other industries as well, that it does help with productivity and you know, you know, again, you know where I want to really help the local government is in compressing these decision cycles, making decisions quicker, faster, more efficient. I want to reduce friction and sometimes. And also, you know, what I can see local government being able to do with these advanced AI tools is sort of just, is to relocate talent. Right. So it's not getting rid of talent.

B And you know, like I firmly believe that AI should be an accessory and it's a tool just like everything else. Just like Your Excel just like your word, but what it'll help is kind of redistribute that talent a little bit more efficiently so that if I've got my community planner that doesn't have to rely and can have on a third party and can use AI to assess development proposals, one, we're not paying that third party over 40,000 a year for a little itty bitty town like Nederland. And two, she can get a first draft of whether or not it meets code and she can be spending that time that otherwise she might review that and actually building the relationships with developers and citizens. Right. So it's about. And you don't have that insight unless you work in local government. And so it's about reallocating those cognitive abilities in different ways just to make the system sort of more efficient and more helpful and better, better outcomes for the citizens.

A I want to circle back to what you're saying relative to citizens. You would hope that so many decisions that the town makes. Right. Are based on community driven consensus too. So how does platforms like My town AI evolve civic participation within the process. And this is, I think especially important for underrepresented voices that are currently within our cities, 100%.

B There's a couple of things in my mind and things that we're super excited to build out in My town AI. So what's interesting is the same data that we're sort of pulling in to help internal operations to be more efficient. You can pivot that and citizens can use it because they need to understand municipal code, they need access to it. Right. And then one of the things that generative AI is also very good at is translations. And so you realize that you're just opening up accessibility to more citizens, you know, to maybe somebody that has a specific dialect, wouldn't be able to interact with municipal services can now do that. But there's also just this, this friction that happens in local government. I've experienced it myself.

B I, you know, I sit on our board of trustees, our city council, and I can't tell you how many times citizens have said, where's the update on that? And we're like, we posted it, we.

A Communicated it 20 different ways to you.

B Yeah, it's still like we still get hammered that we're not being transparent enough or we haven't done the update. And so, and so then, you know, what, what, what, what is a local. What else can a local government do? Well, the interesting thing is that, you know, we started to pull in board meeting recordings into my town and so you know, in the future we'll be able to say okay, a citizen comes onto my town, hey, alert me every time short term rentals are mentioned in a board meeting or alert me every time this development on 100 East 1st street is mentioned in a board meeting. And so it's just, you know, it's like once we point to our data it just unlocks all these things that we'll be able to do. And one of those is let's just give them the information. Let's, let's not wait for them, you know, to, to, to be upset because we haven't pushed it in the, in the exact way. Let's let them decide how they want to receive that. That's one way.

B And then the second way is that once, you know, as we are pushing or pulling those digital, these low cost digital twins together, it creates a different way for place making, for citizens. Place making. Meaning they get to decide and sort of get to get to have a hand in the different place their city or their town. Right. They can kind of co create. And so I think of a, of a future where I'm sitting on city council and we are getting submissions from my town AI of citizen ideas of how a certain site should look using AI. Like because again all you have to do is ask it a question or you have to just put it into a prompt. You know, imagine a park at this location with Mexican American arts structures or whatever it might be.

B Right. It allows for more that diverse participation in ways that you know, many governments don't get to have.

A Are you simultaneously then building out like the government official decision making platform as well as the more front facing what does the citizen get access to?

B Yes, because interestingly it works for both sides. The, the information, the data, it pivots. Right. What are what our internal folks need in terms of they might ask different questions. They're not necessarily. But that's, that's the beauty of pointing to this data is that I ask the system very different questions as a merit pro tem versus my town manager versus our community planner versus our finance director. And that's okay though because we all kind of need a slice of it. And the same is true for citizens as well.

B They just are going to ask different questions and prompt it in different ways.

A So I do want to acknowledge that there's a lot of people looking at the ethical development and you even talked about the bias that people have, but also the bias that tend to go into AI models these days. And there's a long history I'm talking to my architectural planning and historian friends of what redlining means and what that meant to how cities are zoned. How does my town AI begin to kind of one, I feel like it actually needs to digest the zoning as is redline, but also acknowledge shifts in terms of where we want to see things in the future.

B Yeah, that's actually a great question because I think a lot does get wrapped up into zoning, whether there's bias or, and that can just be even just bias of who you have on, you know, city council and, you know, the history of what that zone has gone through throughout the years. And my, my long term, what I really want to accomplish is that we get to a place where the public sector can have its own model, its own, call it a medium sized language model, a small language model, a large language model, whatever you want to call it. And that, that does have citizen input into it. You know, some of the weights and measures are geared towards citizen thriving. And so what does that mean if you build in the logic around citizen thriving? Well, what that really means is that it doesn't matter what your political party is. It doesn't matter what your political party is. You're a leader of a municipal government, of a local government. You must index around community thriving and what is going to be the best outcome for your citizens.

B What's, what's the. And so, and that's why kind of pulling back what I had mentioned earlier around critical decision making, you know, what if some of these models were actually built in with like, okay, here is some really good critical decision making to think about. When you're doing the zoning, I see the zone bumps up against X, Y and Z zone. And by the way, 80% of this zone is, you know, living under, you know, the thresholds for poverty or over poverty or whatever it might be. But until we kind of pull this intelligence together, we don't, sometimes we don't, we're not aware of it or we need, we need something like, you know, the, the someone to point that out to us. And where I see the opportunity is that technology can help us get a little bit more of those data points to make those best decisions for community thriving.

A I want to pivot a little bit and talk about the business itself. So how long have ago did you start? I want to say within the last year. But how long ago did my town AI get started? And you're providing your own wonderful use case within Netherlands. But how many other municipalities or little towns are you working with now?

B Well, and that's the Thing we didn't just stop at the little towns. It was basically, I mean, we've got our first fire district, who wants to get on the system. And again, you kind of think about it, it's very similar use case, different content, but it's the AI plus the digital twin piece of it that they want access to. And so what we realized was we have the ability to service more than just the local governments, but we were currently deploying our free trial. So we have several towns signed up for that. Over 40 of them range from our very itty bitty 300 people to like I said, fire districts that service millions of people. So it's wide range of folks. And then it was this time last year that I was actually researching it and talking with people.

A I feel like that's like a really. When you talk about like how fast technology is moving and like the adoption rate, I think this is kind of a good use case on the government side about how a very small team can begin to deliver on a much bigger scale.

B Well, yeah, and I think it's also, you know, I had to remind myself it's. We, we haven't. I officially actually incorporated the company on my son's birthday, June 3rd of 2024. So we haven't even been incorporated for a full year. I have to remind myself of that. And yet we have folks signed up. We have hopefully our first paying customers like in just a bit. But yes, it's, it did happen with a small team.

B But I think it's also helpful that I do have that title of mere pro tem. I see the pain, I understand it, I see the opportunity to. There is a lot happening right now at the federal government level. And you know, irregardless of your politics, there is decentralization happening, meaning that where our local governments have relied on the federal government before in the past may not be our immediate future. And so the antidote to that, in my opinion, the antidote to that is to empower our local governments. Empower them with their data, empower them with these advanced tool sets, empower them with the ability to go and find creative financing, solutioning, whether that is through grants the government doesn't already or because this was, this was a revelation that one of the my own communities, you know, count the county next to us, had contacted me and it was their director of finance. And I was like, what's the director of finance reaching out to me for my town AI that's weird. And I get on the call with them and he said, well, yeah, I'm the director of finance, but I'm also overseeing grants.

B And correct me if I'm wrong, but we're pointing to all this data. I can use it to write grants more efficiently. I was like, yeah, exactly. And so regardless, local governments have to kind of have a mindset shift. They need to start thinking, how am I going to make the most out of what's happening and empower and still deliver amazing citizen services, but then also empower us to do the thing that perhaps we relied on someone else to do in the past.

A And I really love the fact that others are creating their own use cases once they understand kind of what, like, how my town AI is delivering and structuring things. So obviously you're like, why you were. I mean, you said you were like, why is the director of finance contacting me?

B Well, and we learned that in women defining AI, Right. We gave them a very small core set of things to get them started. And then it was domain expertise. That's what we pivoted on. We said domain expertise will be one of the most critical pieces here in this generative AI era because they'll be able to then see all the other use cases that they could unravel on their own. And that's what we're seeing. And so that's the fun part.

A I mean, you're talking about fire districts, but for a lot of my work when I was working in architecture practice, it was through K through 12, it was with school districts. And I was just like, there are so many different school districts that are trying to understand how to make the most of their bond funding, for instance, and where to spend the money and where is it most impactful, and taking into consideration deteriorating conditions of their buildings, but also how the census data is changing and involving where people are living and moving to and the age and demographics of these individuals. So I was going to say that was something that my company used to deliver as, like a software, as a service keeper of that data. So there's like, it's so much different opportunity out there with my town AI.

B Yeah. One of my projects as my duties as mayor pro tem recently was pursuing a. A local ski mountain. And that led me down the path of using my town AI to think through even the capital stacks that could be available to me as a municipal government. Right. In order to make that acquisition. And, and so especially around financing and bonds, that is, that is something that actually I get asked about a lot in for our local government leaders is, you know, just even, you know, I just Had a request of knowing the most recent bond rates. Hey, can we pipe that into my town AI so that I can move money from, you know, because we have these local government investment accounts at the state level and they wanted to move money here and there in order to capture, you know, some of the best rates.

B And I was just like, oh, wow. But again, it just kind of goes back to your point of folks realizing, oh, but it's the data hub and what data can I pull in that is going to be most meaningful for me and my day to day work? Yes, the opportunities are endless in that regard. Yeah.

A So big picture question, how do you see AI evolving in the public sector in the next. I want to say, since we just went through how quickly you spun out, we usually ask people, 5, 10, 15 years, I almost want to say like 2, 3, 5 years instead of the usual long term. And then what role would you hope that my town AI kind of plays in that evolution?

B So the public sector is historically known for being risk averse, not innovative at all. There is turnover. Here's another statistic that I think is just amazing. 88% or that's the closest I could find. Like 88% of all of our local governments are led by volunteer boards. So I am a volunteer as a merit pro tem. I do not get paid for that. Well, that's not true.

B I get paid like $150 per month.

A But you know, like a very small stipend that's the same within the city of Lafayette. Actually. They could probably make use of my towning. I unfortunately don't know anyone within my city to put it in front of.

B But yeah, so 88% of our local boards are led by volunteers. Local government is hard, it's regulated, it's complicated. And, and we're not exactly hiring data scientists or AI engineers to make the most of our data.

A Well, especially I feel like, and I mean, Denver's becoming more of a tech hub. In California. Those tech people are going and working for tech companies are not turning around and saying, I want to go and work for my local city.

B And so we also have a recruitment issue. Like nobody thinks, ah, I'm gonna go work in local governments, you know, or yes, that's gonna be amazing. It's got a little, it's got, you know, it's got a PR issue as well. And so here, here is my hope and what I hope to bring to public sector and specifically local government is I'm already starting to see little, little twinkles of this and that. Like what we saw in women defining AI, you give, start to give folks the tools. They start to go, ah, oh, oh, wait, well, can we do this? Wait, wait, wait. Can we do this? And with everything that's happening at the federal level and that, we need to kind of put more of the empowerment at the local government level. I want to see local governments become the next wave of innovation.

B If you think about it just that a very small disruption, very small disruption at the local government level has the potential to make huge waves because it is so stifled and it has been for so long. But the more I talk to these local government leaders, the more that they are ready. And somebody had put it to me several months ago when I was first starting this, they said, you're onto something because local governments don't want to get left behind in this AI era like they were left behind in the Internet era. And that still has wounds, which, like.

A Which still shows up every time I visit my local county government website, honestly.

B Right. I mean, we still don't have some towns that have broadband. I mean, but interestingly enough, I don't need you to access the Internet in order to run an LLM on your local machine. Right. There are, there are things that we can kind of get around. So my hope is that these just this very small disruptions, these very small glimmers of hope and like, oh, you know what else we could do? You know what, how else we could reduce friction? You know how else we could just sort of make faster decisions? Those little ripples are actually going to be magnitudes greater than what we thought. And my hope is that the public sector will see that they can be just as competitive as the private sector because they are the domain experts and they can, they should own their own innovation.

A Hi, Disruptors. Thank you for joining us today on an episode of Practice Disrupted. If you like the content for today's show, you can find all of our past episodes over on practice of architecture. Architecture.com podcast. Be a part of the conversation by joining me, our speakers and other disruptors in our community@practiceofarchitecture.com community. Our social media handle is practiceofarch. That's practice of Arch. We'd love to hear from you, so feel free to drop us a DM and say hello.

A Tune in next week for a new conversation on change in the profession.