From 'Can We Build it' to 'Should We'?

Monisha Saldanha (00:01) Welcome to Colorado Tech People, the podcast where we talk with founders and leaders building companies that shape how we live and work. I'm your host, Monisha Saldanha an executive with 15 years of product management experience. Today's episode is all about the lessons learned inside a startup journey and the insights that could help other people thinking about starting companies of their own. I'm joined by Kyle Wandishin

CEO and founder of Arterial to talk about the hard decisions, mistakes, pivots and breakthroughs that come with building something from the ground up. We'll explore what entrepreneurship really looks like behind the scenes, how technology is changing the startup landscape, and what founders need to know before taking the leap. Welcome, Kyle. Thank you so much for joining me today.

Kyle Wandishin (00:53) Yeah, thank you so much for having me. It's a pleasure to be here.

Monisha Saldanha (00:57) Well, let's dive in. First question for you. What inspired you to start Arterial? And what problem did you believe was important enough to dedicate years of your life to solving?

Kyle Wandishin (01:09) Yeah, absolutely. So this is actually an idea I had probably seven or eight years ago with my dad. It started off as literally bolting a GoPro to the bumper of something like a bus so that as it drove around it would automatically pick up potholes and tell the city where they were. About eighteen months ago, I had just exited a integrations consulting firm that I was doing.

And was talking with my roommate. He kind of took some steps, you know, convinced convinced me that it was was a good idea and immediately booked a whole bunch of meetings with with a few cities so that we could learn a bit more about it, figure out if it's even a real problem, and you know, take a crack at it. So one of our first meetings was with the signage department at the city of Boulder. And it was a hard cutoff, 30 minutes, no more than that.

And about an hour and a half later, we had learned all about the struggles of their jobs and we learned that there's almost constantly someone from that department driving around looking for stolen signs. And they gave us an an incredible, probably the the the best first product validation we could have ever heard, which was build this, don't give it to the school, don't give it to the city, build this, we will buy it, we will pay for it.

Explicitly as as a quote and that was really exciting to to kind of hear. And then deciding that it was, you know, a big enough problem that we we wanted to dedicate so many years to it and really build something out, kinda took an understanding of probably two key things. This is the infrastructure that we all rely on every day. It's in all of our communities. And it relies on some

you know, probably probably on the worst side of of data, it's people driving out to visualize things and going out to fix things that don't exist. And, you know, making making some of these steps can improve can improve that infrastructure for everyone. So I think it's a an amazing thing and and seeing government as human and not monolith, I think it's it's really exciting to to get to help help out at that level and provide these people some data that can make all of their lives easier as well.

Monisha Saldanha (03:30) Wow, what an important problem to solve, so amazing that you stumbled upon it.

Kyle Wandishin (03:37) Yeah. it's good fun. I don't know how we stumbled into it. I would have never imagined, you know, as a as a twenty one year old being passionate about pavement and potholes and pavement distress. But we find ourselves driving around looking at all of all of the different things and you know, pointing out, that's a structural fault and everything like that. It's just it's good fun.

Monisha Saldanha (04:00) Looking

back, what assumptions about startups or entrepreneurship turned out to be completely wrong?

Kyle Wandishin (04:07) That's a good question. I think there was really two that we found. I think I think a lot of things like Instagram and people always make running a company seem as some scary monolithic task that is very daunting and very challenging and requires 30 years of experience in the field. And I think it was very interesting to say that it it really isn't that. It's

It's just a never ending willingness to learn and engage and ask for help and just be willing to genuinely learn about the problem, change your mind, take advice, and kind of build build relationships to solve a real problem in the best way that you can. I think the other one was definitely thinking that age was our biggest weakness. When we started Arterial, I was nineteen and my co founder was twenty.

And we thought it was such a blocker. We built a huge wall of mentors and kind of hid behind them as as credibility for the first for the first few months. And you know, we We did have some experience at the time. Like I'd done all the systems integration stuff and I got into work for a few companies. My co-founder has done some business development consulting for Smart Cities Alliances and and

a lot of data science as well. So it's been like we had we had experience, but we still thought we needed to hide behind a wall of, you know, centuries of experience. And I think we learned that it was actually probably one of our biggest attractors for opportunity. Being young, being willing to learn and talk to so many people has put us in so many rooms and I think we constantly kind of find ourselves as how are we here? And then realizing that we are just asking as many questions as possible and kind of falling into these places. And it's really nice.

Monisha Saldanha (06:08) What

was the hardest early decision you had to make as a founder, and how did you approach it?

Kyle Wandishin (06:15) I think the hardest decision we had to come across as as we were starting is definitely on the lines of any of the complexities of running a real startup, you know financial strategy, what a government competitive bidding process looks like, risk and compliance frameworks that enable us to even work with them. We didn't know how to approach any of these things. And so I think

to me, there's very few decisions that have felt very hard because we have taken an approach of or not necessarily that, but we've taken an approach of really trying to surround ourselves with as many mentors and advisors and friends as possible who have subject matter expertise in all of these things. And we know the gaps in our knowledge. We know what we don't know, but we have

spent a lot of time asking these people who are subject matter experts and they've really helped us inform what what we do for this issue, where we go from here. And, you know, not all advice is good advice, but I do think there is a it's it's a it's really helpful to hear unique perspectives from people's experiences and it can definitely help shape decisions and make them a lot less challenging than they need to be.

Monisha Saldanha (07:43) And did you ever hit a moment where you seriously questioned whether the company would work?

Kyle Wandishin (07:48) Yeah, think I think initially when we were really shaping up who we are and where we are placing ourselves as Arterial I think we found some some fear with competition. I think as we were initially looking for pothole detection and asset detection Sorry, excuse me. We we ran into we ran into a few other companies that were in similar spaces.

There's you know a small a small handful of companies that have been doing this for a few years and they've been detecting and providing it to cities as a map. And so it we we We didn't know where we go from there or what if someone like Google tries to to jump in and decides they really want to do this? We kind of took the approach of trying to 10x our barrier to entry. We spent so much time

Interviewing these cities, the shortcomings of the existing solutions, you know, probably over a thousand hours just hearing from cities that used competitors in the past and stopped using them, or why they still use them. And it has led some to some incredible innovations in our technology that you know we're getting to to throw out some patents for, which is incredible. And we've we've just really built up this this barrier to entry of of competition with us

to really give the cities what they need. So the math will always kind of favor a partnership with us over direct competition.

Monisha Saldanha (09:25) Okay,

and that barrier to entry is the proprietary innovation?

Kyle Wandishin (09:30) Yeah, so it's it's kinda a few a few fronts in there. We We've made some really amazing innovations with depth projection. So being able to determine the exact size and depth and length of a pothole or how high a sign is off the ground and a lot of stuff like that. To be able to do more of these engineering grade inspections. The other side is what comes next once you ha once you have this data? How can you know, a da a data dump of fifty thousand potholes doesn't do anyone good. So

we've taken some next steps to prioritize this information and understand their operational context, being able to help take in their campaigns or considerations from their community that help them fix more and what they need to be fixing, rather than I know there's a thousand issues and I don't know what to do about them.

Yeah.

Monisha Saldanha (10:25) And

How did you decide what not to build? 'Cause that's almost as important as what you have built. How did you decide, you know, what not to build in the early stages of Arterial?

Kyle Wandishin (10:36) Yeah, I think We have been really lucky with our amazing advisory network and been able to really, you know, kind of put put some put some ideas together that and you know, shoot some ideas down for what not to build by asking these people with hundreds of years of experience combined. And I think we we also have a very helpful kind of co founder dynamic.

My co-founder is optimistic and pushes opportunity and brings so many ideas to the table. And I am a a bit of the opposite and we kind of work work through these ideas together and it helps kind of centralize where things fit and it really helps us kind of get to that next step of what do we build, what do we not build, when do we build it, all that kind of stuff.

Monisha Saldanha (11:34) And what's the mistake you made early that ended up teaching you one of the most valuable lessons about startups?

Kyle Wandishin (11:41) I think this kind of comes back to our initial assumption that we we made where age was one of our biggest detractors. We hid behind our walls of mentors and we thought age was such a liability. And by kind of doing that, we realized that we created that dynamic that we were kind of fearing. And you know, We we we made ish age an issue by by doing some of that stuff. And so when we

you know, took a step back and leaned into who we actually are and that we have domain understanding and that we are experts at some of this stuff. Our per our kind of perceived weakness became much more of a strength. And I think the yeah, that was probably one of one of our biggest mistakes in the beginning. Because I think I think we we lost we lost quite a bit of credibility by by creating that dynamic that we were so afraid of.

Monisha Saldanha (12:38) And

How has the startup building process changed over the last few years because of AI and modern tooling?

Kyle Wandishin (12:46) Yeah, I think the biggest change is gonna be team leverage. I think the push of AI and easy and accessible automation for so many people has removed a bit of a bottleneck for how many people can do how much. And I think it Particularly for startups, it enables you to, you know, kind of 10x

how it feels like you have 10x the amount of people by automating so many smaller everyday things. You can do automated code reviews or you can, you know, take take lead generation for example, being able to use tools like Claude or Chat GPT to be able to pull a lot of this information that's out there, run it against some of these systems, and create these pipelines that used to take

teams to kind of uphold. And you can you can just have anyone build that very quickly. And I think that it's really a matter of you know, really exponentially increasing our execution capacity. I think the question really used to be can we build it? And it is enabling people to focus a bit more on are we building the right thing? How do we build it? Some of these niche or not niche, but

you know, more specialized things because the actual building of it can can move a lot faster now.

Monisha Saldanha (14:21) And are there things that your team can do with AI that previously would have required significantly more people or capital?

Kyle Wandishin (14:28) Yeah, I think All across a lot of my side of things, product, operations, data, we're able to operate as a team of many more people. you know, Feels like over twenty despite us being a team of five today. And we've been able to really leverage research capabilities for our product. Being able to

kind of pull trends across many papers. Being able to pull out new ideas and research has enabled pieces of our I guess initial research for some of our depth projection approaches. Which you know, would have been a many, many year project in in the past. I think from the operations side, we're able to leverage automation and AI for a lot of the entry level

tooling in the operations side. We're able to leverage some of the smaller services that people are creating very quickly to put together documentation and a lot of these kind of tools that typically would take a whole lot of time and and slow down that building process. And I think it's just it's It's really enabling so much more and it's it's exciting.

Monisha Saldanha (15:51) Yeah, it really is exciting times and things are changing so quickly. What parts of product development or operations still require strong human judgment despite advances in AI?

Kyle Wandishin (16:04) I think the biggest thing to me here is gonna be

relationships. I think building a company and you know, doing that product development, doing any of the operation side, it understands it it needs such a deep understanding of the customer, the investor, the partner, the employee. You need to understand them and human complexity and what they're telling you, what they're not telling you, and use that to influence how you're doing a lot of that downstream.

I think that judgment is very human. And I think that that should really remain as a kind of human component because I think that it creates the best solutions to problems. To me, it feels like the the wrong way to word it, but I feel like I take a slightly reverse AI approach. I think a lot of people put AI in a lot of positions because it can go there, and I think that it's

very often important to prove that it's the right kind of point for there. Is it a dynamic task? Is it something that needs to structure this information that is good quality and trusted and put it into this form? Or do we need a human to kind of generate that deeper understanding before we can do something like that? I just think with dynamic context and shifting priorities, I think I think the the human complexity of that is is what really

Where where where that sits.

Monisha Saldanha (17:43) That makes sense. And how do you think founders should balance speed enabled by AI with the need to deeply understand customer problems?

Kyle Wandishin (17:53) Yeah, I think I think this definitely can come down a few ways. I think the speed that's enabled by

Sorry, I misunderstood that. That's that's my bad. Do we wanna repeat that one?

Monisha Saldanha (18:09) We can edit it out, don't

worry. Yeah, just start again.

Kyle Wandishin (18:13) Okay.

Monisha Saldanha (18:18) Do you want me ask the question again?

Kyle Wandishin (18:20) sorry, yeah.

Monisha Saldanha (18:23) Okay. How do you think founders should balance speed enabled by AI with the need to deeply understand customer problems?

Kyle Wandishin (18:31) Yeah, I think The speed that's enabled by AI is super helpful and super amazing. And I think This comes back to kind of that ability to move the question from can we build it to how do we build it? What comes next? I think the The key piece is still a hundred percent that deeply understanding customer problems. I think More time needs to be spent on that with this shift.

I think The more time you are able to put into the understanding the problem, understanding what they want a solution to look like, how your tool can actually solve that solution becomes far more crucial because that speed to build is just exponentially going up and that can catch up with the specifics that you want to support that you find in this cust that in these customer meetings.

Monisha Saldanha (19:27) And

What technologies or shifts do you think are most underrated right now for early stage founders?

Kyle Wandishin (19:33) I think There's two that I always get very excited about. And I think they're they're vector embeddings and graph neural networks. I think particularly on vector embeddings. It is an incredible push to be able to hold so much information and do so much analysis on that information that, you know, typically we'd see in the past as

unstructured and messy and disconnected. And I think The the abilities that it bring will touch every field. I think that It enables you to be able to understand raw and messy images, text, files, all of this stuff that's been so historically disconnected and run so much more analysis on it that can

you know, really provide assistance to everyone across, you know, so many so many industries. But

Monisha Saldanha (20:40) Yeah, so What could it mean in infrastructure?

Kyle Wandishin (20:43) Yeah, I mean for for infrastructure, for example, we've taken a really big approach of it to connect all of our information from our imagery and our geospatial context, such as, you know, the speed limit, the traffic density, if it's on a snowplow route. All of this kind of information to help the city understand the impact of each issue that they're finding.

And be able to kind of enable the most optimal use of every maintenance dollar with strict prioritization and so many other pieces of context that have historically been so disconnected. For systems integrations and other kind of industries like that, it could mean automatically mapping data lineage across all of these different fragmented pieces of technology. And I think The kind of key piece is the relationship layer.

These vectors and graphs enable relationships to be drawn that we couldn't figure out before. And it is such a kind of fundamental piece of of moving forward.

Monisha Saldanha (21:53) And shifting gears a bit, let's talk a little bit about Colorado. How has building Arterial in Colorado shaped your experience as a founder?

Kyle Wandishin (22:03) I think it has been exceptionally beneficial. I think Colorado is one of the best places to start a company because there is such an emphasis on community and people and relationships. I think, you know, somewhere The difference between somewhere like here and San Francisco is that what I've seen here is that people genuinely want to see ideas and technology succeed and

through that desire, they will offer help at a rate that I have never seen anywhere else in the world. All over Colorado, in every program that we take a look at

the same idea is kind of echoed everywhere, and it's that kind of give give first mentality, or, you know, just giving a help for the sake of giving help to help bring something to life. I think however you wanna say it, the people in Colorado really just wanna help bring ideas to life, and I think that that's been a a huge help to us.

Monisha Saldanha (23:04) And so far in your journey as a founder, have you sought outside funding or have you been self funding?

Kyle Wandishin (23:13) Yeah, currently we've been exclusively bootstrapped. We are currently raising though from outside funding which has been very exciting. Yeah.

Monisha Saldanha (23:27) And and when you say you've been bootstrapped, so it has the funding come from your own sources or has it come from the contracts with the cities that you're working for?

Kyle Wandishin (23:39) Yeah, so It's been a bit of both. it's been it's been a bit of both. We've put some personal funds in as well as been able to to leverage quite a bit of the cash from our from our initial contracts to really move things forward.

Monisha Saldanha (23:53) Yeah, and where are your initial contracts?

Kyle Wandishin (23:57) They're with a few smaller cities here in Colorado, which has been very exciting. I think we are we aren't necessarily allowed to announce all of them publicly, which is why I don't know how to answer that.

Monisha Saldanha (24:08) Okay. Cool. Are there any that are public or no? Are they?

Kyle Wandishin (24:15) I

Will I'll I'll say I I I can say I can say City of Boulder, they've been a huge help.

Monisha Saldanha (24:23) Mm.

Kyle Wandishin (24:24) but I'll I'll double check on the the contract before we put that in the podcast.

Monisha Saldanha (24:28) Okay, that's cool. No, it's okay, we don't need to mention it. How do you think about hiring and building culture in an early stage startup environment?

Kyle Wandishin (24:37) Yeah, I think The biggest thing that we look for when hiring is an eagerness to learn and an ability to kind of self teach. I think so many of these tools with AI and automation are taking away a lot of that drudgery of entry level work. And so I think The the the bar and the request

requirements for what you really need in a startup is definitely changing. It's no longer have they have they done X in the past, and it's more so can they pivot and learn what they don't know so that they can make these decisions and move things along and and really kind of create. I think That ability to self-teach, the eagerness to learn

means that you'll be able to to do anything and really pivot and bring things to life rather than if you've just done it in the past.

Monisha Saldanha (25:41) Cool. And Has AI and automation affected what type of work people are expecting to do?

Kyle Wandishin (25:49) Yeah. I I think It enables people to step back and be more of a technical project manager or you know, take on that more kind of managerial role where they're not they're not the one sitting there doing every line of code. They're trying to explain how something else can do that. Or they're just trying to architect, make the decisions that involve the human complexity

rather than the line by line implementation. And I think that it's a big shift in the skill set required for each role as well with that.

Monisha Saldanha (26:30) What

advice would you give to someone in Colorado thinking about taking the leap into starting a company?

Kyle Wandishin (26:36) Yeah, I think The biggest advice comes back to community and eagerness. I think This is something that realistically anyone can do when you are willing to learn, willing to change, and eager to grow. I don't think that it is a good idea to treat age or experience as a real deterrent that can slow you down or make you feel like you aren't able to do this. And

The other thing is surround yourself with advice and community and mentors. People make the world work and you know, where you can. Build on the shoulders of giants. In Colorado they all want to help. And building relationships with people is such an incredible way to to to move and to grow and to build anything.

Monisha Saldanha (27:29) Good advice. And What's been the most rewarding moment so far in building Arterial?

Kyle Wandishin (27:36) I think that constantly changes. I think that Founding Arterial has been the most beneficial thing I've ever done. I think the experience brings opportunity after opportunity after opportunity into my life faster than I could have ever expected. And has you know, I I I feel like I'm constantly looking around at how

I'm I'm in these situations and we get to go to conferences and we get to present there and we get to share our work with, you know, people who whose work I've seen for years. and all of these kind of things that just they're so rewarding to get to see that by putting in work and learning and meeting people that you can you can kind of find yourself in any room and it's just it's very rewarding to to constantly be finding myself in that situation.

Monisha Saldanha (28:29) Yeah, That does sound very rewarding.

Kyle Wandishin (28:32) Yeah.

Monisha Saldanha (28:33) Can you share an example of a customer interaction that changed how you thought about the company or product?

Kyle Wandishin (28:40) I think there are far too many of those. We tr have tried to have customers build as much of the product as possible by telling us what their workflows look like today and the exact pieces that they'd want to change. I think Some of our friends at at one of the municipalities here in Colorado were some of our earliest drivers for this and shared a lot of insights into

concerns and constraints from their kind of government side, things that we definitely wouldn't have known on our own. And they pushed us to build so many things right from day one. They pushed accessibility with our web platforms, making sure the screen readers can use it, adding cybersecurity, making sure that we're meeting so many of these kind of niche frameworks that

you know, going into it I I had only really needed the check of approval for with with some integrations and all of these kind of best practices that are best practices in most industries and required from day one in government was incredibly helpful and definitely pushed us to build best practices in from day one. And we have everything on security and accessibility and just making sure that we can work with anyone.

Monisha Saldanha (30:08) And

How has entrepreneurship changed you personally as a leader, decision maker, or person?

Kyle Wandishin (30:16) I think There's been a lot of lessons I've learned from it, but I think one of the bigger ones is that people are what makes the world work. I think I have come to deeply understand the power of relationships, building friendships with people, finding mentors, finding advisor advisors, and being able to ask for help.

And know when you need to ask for help. And then also offering help everywhere you can are I think changes I've I've noticed. I think There's a big compounding effect to offering and accepting as much help as you can that enables so much more success and makes it almost inevitable with enough support and enough help in both directions.

Monisha Saldanha (31:12) Well, this has been a really great conversation. I have one last question for you. What is one book every builder should read and why?

Kyle Wandishin (31:23) Vic.

Circling back to some of my answers before, I do think that with automation and AI, the question changes from can we build it to should we? Are we building it right? Are we building the right thing? And on that, I think one of the books that that really comes to my mind is A Whole New Mind by Dan Pink. I think there are some things that AI can't replicate, such as human judgment,

creativity, and a lot of the human complexity of what are they telling you versus what are they not telling you? What's their face saying? These things that we all kind of understand, but systems like that never will. And I think

that human piece is so important and you know, seeing this book's probably two thousand and eleven or two thousand and nine or something, but it it has some of the hints of of this effect and I think now more than ever with AI and automation, it just has become so much more important to understand that that is the important side. And the people that will really succeed over the next few decades are I think the people who can really emphasize, see the patterns across disciplines and

you know, handle that human complexity.

Monisha Saldanha (32:46) Fantastic. Well thank you so much, Kyle. Thank you for joining me today.

Kyle Wandishin (32:51) Yeah, of course. It was a pleasure to be here and thank you so much for having me on.

Monisha Saldanha (32:56) And I'd like to thank our listeners for listening to this episode of Colorado Tech People. If Kyle's startup lessons resonated with you, consider sharing this episode with the founder, builder, or someone thinking about starting their own company. Don't forget to subscribe so you can hear more conversations with the entrepreneurs shaping Colorado's innovation ecosystem. Until next time, keep building, keep learning, and don't be afraid to take the leap.