BizTech Superhero

Joshua McNary [00:00:00]:
Welcome to the BizTech superhero, the podcast that empowers you to unleash the technology superpowers within your business. I'm your host, Joshua McNary. I'm joined today by today's superhero, Eric Engelmann, general partner at ISA Ventures and partner at Novi to talk about using AI inside his startup venture studio. Eric, welcome to the show.

Eric Engelmann [00:00:21]:
Thanks, Josh. Excited to be here.

Joshua McNary [00:00:22]:
So, Eric, for folks just meeting you for the first time, could you share a little bit about who you are and what you do?

Eric Engelmann [00:00:28]:
Sure. I'm a startup founder. I started my first company at age 24 called Geonetric. It's a web applications business in health care. And, fifteen years into that, I started a nonprofit and a startup accelerator program in 2014, and then, ISA Ventures in 2020 and Novi in 2023. All of those things have in common that, I get to play with technology and business operations and strategy and leadership and mash all that together, and it's a really fun blending of stuff.

Joshua McNary [00:00:57]:
That's a lot of stuff.

Eric Engelmann [00:00:58]:
It is.

Joshua McNary [00:00:59]:
So right now, your main gigs are ISA Ventures and Novi. Right? So tell us a little bit more about those entities. Sure.

Eric Engelmann [00:01:06]:
I yeah. Sure. ISA Ventures is a venture capital fund, and so we, we're mostly through deploying that capital at this point, in the fund's history, but it's a VC firm. We invest in Iowa companies. And so we have 40 companies, and I get to work with those founders and the technology and leadership problems that they have. So it's, really interesting because they are all over the place, different industry, different stages, and whatnot. Novi is a little bit different. It's a venture studio, and it's, very new.

Eric Engelmann [00:01:33]:
It's still in its sort of stand up phases right now. I have two business partners on that project. And, but it works with one startup per year. The idea Okay. It will work in health care software. So in terms of, like, the the the contrast is that it's much deeper involvement with the company. Sure. Company with someone as opposed to just an investor.

Joshua McNary [00:01:53]:
Gotcha. Cool. So kind of the big picture and the and the focus that you get from where you're able to work with one company.

Eric Engelmann [00:02:01]:
Exactly. It's a it's a it's got some similarities to venture capital, but it's, that hands on the steering wheel and getting gritty of things that's kind of exciting and things like, you know, how does technology fit in here and being able to influence that and maybe even help do this is, is exciting.

Joshua McNary [00:02:15]:
Great. And you're you're a technologist at heart. You've been doing this a long time. That's when we first met years ago when you were running Geonetric and, doing all the tech things there. So, I'm happy to have you here to be able to talk about technology and how you're using it inside of your various ventures, particularly Novi at this time, to make things go. So why don't you start out by telling us a bit about how you're incorporating technology in in recent times, recent months, recent year. And I know we wanna talk about artificial intelligence as that is the buzzword for good reason, here in the last number of years around technology. So just wanna kick us off talking about what you've been doing and what's been interesting to you in technology and Novi?

Eric Engelmann [00:02:56]:
Absolutely. I mean, as a as a technology guy at heart, you know, I always try to figure out ways to let technology deliver value for whatever the best objective is that we want. And, you know, I think there's actually a really good contrast with, you know, what we were able to do with ISA Ventures versus what Novi is doing now at the very precipice of AI becoming way more powerful. You know, we were trying to manage 40 some odd investments and all the information flow around those with financial data and qualitative data from all those companies of our investments in them. And, basically, we built this monstrosity of Google Sheets and Google Docs very, you know, programmer ish, you know, basically pushing Google suite to its limits. Mhmm. Anyway, it worked, but it's a little rickety.

Joshua McNary [00:03:37]:
A lot of formulas. A lot of formulas in those sheets.

Eric Engelmann [00:03:39]:
Yeah. And if anything doesn't fit a very prescribed structure, woah. It's work. Right? I mean, I get a way to go back in and fix it. And, you know, three years later, going back to that monster formula kind of pain. Whereas Novi is standing up right at the time when AI is is everywhere and moving very, very quickly, and it's dealing with the similar kind of thing, right, where Novi is looking at ideas to decide when and where do we invest. But as part of that, like, we have the ability to use AI from the get go. So this idea that we can build a venture studio that answers these questions using AI is an exciting opportunity.

Eric Engelmann [00:04:13]:
And and I think it highlights maybe one of the, like, programmer worldview and AI worldview. Like, code is deterministic. Like, it's I ask it a question, it will give me the same answer back. Whereas AI is sort of like, well, it's probably like this, and here's why I think it's like that. And it can answer questions no programmer can ask. And, like, that sort of, maybe just understanding what that means as a business owner and where you can add that value then is opens up a whole new range of of possibilities that we just never could have done, five years ago.

Joshua McNary [00:04:45]:
Yes. That that that fuzzy or flexible way of thinking about a prompt in AI is very different than the way we thought about it. The rule based structured approach that we may have thought as technologists or just as business people using technology in the past. Yep. Well, so with regards to the AI first centric nature of Novi, because that's one thing that we're seeing in in the marketplace right now is a lot of companies, whether they're tech firms or otherwise, are trying to slap AI marketing or actual technology onto what they're already doing. But you've got this opportunity here with this firm to to really be AI native. So explain maybe a little bit about how you're approaching that spreadsheet or the equivalent of it in your current organization. How are you doing in AI? Let's give us a little more, in the weeds of, like, what what we're doing to actually be an AI first company and how how you're actually doing it.

Eric Engelmann [00:05:38]:
Yeah. Yeah. Happy to do that. And, I mean, it's one of those things where everybody is right now figuring that out on the fly. And I think the the place where most people start with AI is that it's sort of like your your parlor trick sidekick thing. It's a little like like a chat window, like a Google window where you open it up and you ask it a question, and it gives you an answer to a question. And then as a human, you process that and you stick it wherever you would stick it. Right? It's like it's not in the workflow.

Eric Engelmann [00:06:03]:
It's adjacent to your workflow. It's like a a really smart little friend hanging out on your desk every day.

Joshua McNary [00:06:08]:
Right. It's your intern. It's your it's your sidekick. It's your yeah. It's it's it's Clippy on steroids from, from the old days on Windows. Right? But it's actually doing things versus just, repeating repeat repetitive, prompts.

Eric Engelmann [00:06:22]:
We're we're dating ourselves with the Clippy reference.

Joshua McNary [00:06:24]:
Yeah. There's some people who are saying this, they have no idea what we're talking about, but look it up,

Eric Engelmann [00:06:29]:
folks. The the ability to say, alright. But I can I can take information, and I can give it to an AI and have it do something with that information and then stick it somewhere without me having to key it in and then rekey it is like the minimalist first step of, like, I can wire AI into an existing workflow and have it do something? Right? And, like, the ability to then take that and build on that and chain them over time into adding value, is a big deal. I don't know if you ever got into, like, lean movement stuff, you know, in the late nineties or whatever, eighties, nineties. That was a big thing. This thing called the value stream mapping where you'd say, well, here are the apps in my process, and, like, you're the ones where a human has to step out and go do a thing and then put it back. And you would try to as many steps as, like, the idea was to lean process. Like, it's exactly the same same thing, but when you think about what AI is to do for you in that context, like, you can often remove lots of steps.

Eric Engelmann [00:07:27]:
So Right. Right. To, like, go through, like, a very like, the first main one we did with Novi if that's helpful and kind of step Go ahead. Shoot. Podcast. Sure. So, our thinking first was we wanna do this old school sneaker net version first. Like, we're building this brand new business that's you know, we have information and ideas of how we wanna do it, but, you know, the plan never survives first contacts with reality.

Eric Engelmann [00:07:50]:
And so very, very inexpensively the first time. Right? Novi, goes out and requests ideas from people that they see businesses, and we take in those ideas. We put them through this whole process that amounts to, oh, you think there's a problem. You know, let's say it was, you know, something to do with, how do you care for old people, with Alzheimer's? How do their families stay in in conversation with each other and have this idea for how to solve this problem? Like, we would go out and say, oh, we're gonna go talk to, you know, 20 people who have, family members who, you know, are dealing with cognitive issues and figure out how to how they deal with it today. Is this a problem? And would you pay to solve this problem? Right? Right.

Joshua McNary [00:08:29]:
Right. Validate validating the idea.

Eric Engelmann [00:08:31]:
Yeah. Yeah. And, I mean, straightforward customer discovery, the same stuff you would learn anywhere. Like, we're just doing that on behalf of these ideas that come in. And so the first way we do that is we go we get the idea in. We look at it and say, that's interesting. Go to LinkedIn. Who do we know who deals with this? Or family or

Joshua McNary [00:08:47]:
a friend.

Eric Engelmann [00:08:48]:
And then we write that down, and we put it in a spreadsheet. And then we talk about it. And then we have a meeting, and we decide which of those people are we gonna reach out to in what order to then talk to them

Joshua McNary [00:08:57]:
about the questions we have. And this is all internal this is your

Eric Engelmann [00:09:00]:
internal team doing this? Yeah. Absolutely. It's a team of five, six people. This is what we're doing. And then this is, like, you know, we spent six months basically doing that on behalf of 50 ideas and get getting progressive deeper as we slowly whittled them down to ones we're more interested in. But it was then we do the interview, and we write down the results of the interview. Maybe we transcribed it, but we'd write down or maybe use AI to summarize. But it was still, like, what at the end of the day, six months later, you know, we ended up with, you know, a good answer, but it like, the amount of time and effort it took to get that in is incredibly painful.

Eric Engelmann [00:09:30]:
And we ended up with thousands of Google Docs in different formats and double sheets. Yes. Basically, like, all of this information existed, but it was not organized and it was not in a workflow. Now maybe that's what we should have expected, but as we talked about what we wanted to do next time, we said, guys, like, we know there's tooling that can help us do this. Let's think about it from that perspective. So Yes. Second around. Same general starting point.

Eric Engelmann [00:09:54]:
There's a form basically on the web that we say, hey. If you have an idea, put it here. They put in a couple of pieces of information, and, we built it in a system called Retool, which I can speak more about if you want later. But it's basically a software platform, that lets us build applications very quickly. Once that idea comes in, we bounce it off the AI to say, hey. Here's our database of people that we know, for the employees at Novi. Look through those people and everything we know about them to tell us which ones are most likely gonna know about this specific idea. Make us the list.

Eric Engelmann [00:10:25]:
Tell us why you think they're a good fit for that idea, and draft an email to them ready to go to say, hey. Would you be willing to set up a conversation about this or answer this actually actually build a survey for them to say, hey. Give us a quick sniff test, like, really fast.

Joshua McNary [00:10:40]:
Mhmm.

Eric Engelmann [00:10:40]:
So what we did is we took what was, you know, multiple days and hours of people typing things into AI just wiped out all of the first eight steps of the process and resulted due, here is an email to this CEO of this hospital asking this question. Is it okay to send it from your email, Eric or David or Krista or whoever, like, it knew who had the relationship with them and would pre write the email to send it through their Google account Nice. Ready to go. It was like it just took the whole thing out. It you know, this for us was, you know, just an example. Like, it's it's it's kind of a simple example in a way, and yet every business has gobs of this, like, mental

Joshua McNary [00:11:17]:
Over and over. Yeah. Over and over and over again. When you were telling the story about about the original way and just thinking about all the human interaction both internally and just in your own head, internally within the organization, internally inside your own head that required to process all of that and to get ultimately what you need, which is these validation emails sent. That process took forever and a lot of energy that you could be putting towards more important things. Now what I like about what you're talking about here is that ultimately you got an email draft that you said go or no go, and you remained in the loop there to be able to make that decision because you don't want the AI doing anything, bonkers, especially in its current iterations. Yeah. But, ultimately, you were still in that loop and still were making a decision, but it just got you to that point much faster and gave you opportunity to intervene whether it's no, don't send it all or maybe modify what that had created.

Eric Engelmann [00:12:11]:
Exactly. Exactly. And that's, you know, that's right. That's just step one. Right? Because then it, you know, sends out essentially what amounts to a survey, saying, hey. This was the problem, that somebody said they saw in the real world, and this is how they think they should solve it. Tell us, have you ever seen that problem? Do you believe it's real? Is it painful to you? Would you pay a lot of money if you could solve it somehow? Mhmm. Who in your business would be the one who makes that decision? And, like, we gathered all that data.

Eric Engelmann [00:12:36]:
AI processes all that data. And it's a it's a summary back to us. We don't know how to touch it. Right, whereas the first time,

Joshua McNary [00:12:43]:
we

Eric Engelmann [00:12:43]:
were touching all of it. You know, we transcript, copy it over here, and run AI on it. Yeah. We just programmed all that in using Raytool. It was, it was a there's there's still, like, so much more we wanna do, but, like, just as an example of the the kind of, manual work that is still very common, I think, in a lot of businesses. You know, you can use AI if you really want to rethink it, as a strategic advantage. And, you know, again, we saw it as Novi is being built at the very moment that AI is becoming so powerful. It would be stupid not to almost design the whole thing around potential of AI, to exploit it because we have competitors and peers who built you know, they don't have this tooling because they got started earlier.

Eric Engelmann [00:13:28]:
Like, this is an opportunity to start from scratch and really think about it.

Joshua McNary [00:13:31]:
There's a competitive advantage right now at this time in history, and perhaps it'll be it'll be another reset of that a year from now or two years from now as to say I continue to have it. But right now, all you could do is deal with right now. And you're in a position right now to be able to take advantage of that, be an AI first company, and jump ahead maybe of others, explore things that others cannot. The fact in your in your example so far as well, you're talking about being able to do things maybe that you hadn't thought to do before, like those emails you sent before for that first, stage, maybe you had some kind of template to it. But now we're talking about like really bespoke emails to each of them. Like, you wouldn't even consider doing that the old way. And now you're able to and then in the case of the second, kind of stage there, the survey component, well, now you're able to summarize it and produce better results there than you could have previously as well. So it gives you this new new superpowers since we're on the the BizTech superhero podcast to talk about, AI and how it can enable you to be a superhero in a in a really a magical way that maybe in the past, Us Technologists would say, well, yeah, we have some superpowers.

Joshua McNary [00:14:35]:
People might think we have superpowers because we can code and make magical things happen. But now with this large language models, you anyone doesn't have to be a developer necessarily can essentially program a computer using these prompts. That's what it really is, the word calculator that you can use these these these natural languages to be able to achieve these outcomes and apply it to businesses, your business in a way that that makes sense. I mean, we you and I both like business and technology and being able to think about things in one fell swoop rather than having to break it down into, okay, here's the business side of the office and here's the technology side. Let's bring those ideas together very quickly.

Eric Engelmann [00:15:15]:
A %. And I think, you know, as an advantage for us, you know, the way we're looking at it, the scale capability that we suddenly have as an option that never would have been part of our business model previous, suddenly becomes interesting. So, like, let's imagine, for example, you know, one one potential source for ideas for us would be, like, university tech transfer office. You know, somebody invents a thing at university and then it sits on a shelf. And, you know, we would love to identify opportunity in there that we could deal with, but, you know, we can't reach out to all of those people and then process all of those ideas the way we were doing it the first time. But now, like, the the size of the funnel of incoming ideas and the ability to process them 10 times as fast or maybe in the future a hundred times as fast with equal or similar quality from our end, like, suddenly means that as a venture studio, right, we need good investment opportunities. Right?

Joshua McNary [00:16:04]:
And if

Eric Engelmann [00:16:05]:
it helps us even one time find an idea that's better than we otherwise would have found, like, it it pays off. Right? Or the other end of this, like, what we're doing is, you know, when we do these this outreach to people in the target market for whatever the idea is, we're we're doing that customer discovery, but we're real the word customer is a big deal. Like, we're identifying who are the early adopter buyers who want to solve this problem and pay for it now, see the approach as valuable. What we're really doing is building a customer for that idea.

Joshua McNary [00:16:31]:
Mhmm.

Eric Engelmann [00:16:31]:
Right?

Joshua McNary [00:16:31]:
Mhmm.

Eric Engelmann [00:16:31]:
So if instead of being able to reach 10 hospital CXOs, we can reach a hundred or thousand of them because we figured out how to do it faster and better.

Joshua McNary [00:16:40]:
And and more more, qualified because the aid is helping you filter it down.

Eric Engelmann [00:16:45]:
Exactly. Like, suddenly, like, the value proposition that we offer as a value studio or as a venture studio to our idea generator cofounders or for us is way bigger. So, you know, this idea of of AI is I really I I I call it the parlor trick because I think that's still how most people think of it. Like, it it's just, like, something you use to help yourself when what it really is doing is enabling entirely new business models. And, you know, my concern is that, you know, startups that we're dealing with, if they're not thinking about it that way, like, they're missing the real opportunity right now to win over incumbents who probably are gonna be slow to adopt this stuff. They've they've got a lot of vested technology interest, and you have an opportunity to build a business right now like that otherwise could never be done. Done.

Joshua McNary [00:17:28]:
Yeah. With much less individual human contributors, more AI contributors than

Eric Engelmann [00:17:36]:
they use for cost of it. Yeah. The cost of humans in many cases, but also just the probably the quality is similar and maybe better in many cases, and the the output is just way faster. Like, there's no latency. When there's a human involved, you know, like an example would be taking a lead in on your website. You know, somebody comes in and they they look at the lead, and maybe they search their CRM. They Google the person. They connect with them on LinkedIn, and they're, like, spending an hour just thinking, is this person a good prospect for my business? Right? I mean, AI can do all of that for you, and your salesperson instead of, you know, doing that kind of grunt level work, instead is like, I'm my I'm focused on the demo.

Eric Engelmann [00:18:14]:
I'm focused on closing the deal, and we move all of that to to AI to prep all that work for us for it just takes things we need to do today and just moves up the value chain.

Joshua McNary [00:18:22]:
And and and I think where a lot of businesses are at right now, they're they're trying to think about, okay. How do I just have it help me qualify the leader do vet that lead like you first said. They're not even thinking about the fact that they could potentially then allow that time to be put towards the demo or the AI coming in to help generate that. Like, they're they're only at step one of the AI filter filtering. And then there's a second phase and a third phase and a fourth phase. Sounds like you're a number of phases down the road, but you even admitted earlier that there's more you could do. There's always gonna be more you could do. And layering this over time and connecting the dots between them is something that we've always had with regards to technology and solutions and kinda modular ways of doing things.

Joshua McNary [00:19:03]:
And that's hard enough in historical terms to be able to keep track of and document and keep moving forward. But then with the pace of AI and the ways that we can quickly iterate within that, it creates a a new problem set there that we've fought fought before, but now it's moving so much faster. You have to maybe use AI to help you even keep track of what you're trying to achieve with the AI. You're right. It starts to become this kind of thing. So what have you come across that kind of problem with regards to the the pace of iteration, or have you any thoughts on that? Kind of the opposite problem of the the the the LUGARTS in this case currently, but the those that are trying to press forward with it like yourselves.

Eric Engelmann [00:19:46]:
Yeah. I mean, I think the the these are the problems that I've seen when people would try to implement technology in their businesses as well. I can I can clearly see how, you you know, deterministic code can solve this problem in this one place? But often you have, you know, a CRM system over here and some other system over there, and, like, the whole thing just grinds to a halt as soon as you're like, well, I wanna move data from here to here. Can I compare these? Because the cost to hire a developer who knows how to integrate whatever with whatever is so painful, so expensive, so maintenance heavy. Like, where AI is evolving is it's like sitting on top of these systems and can do that translation from a to b for you as part of that same workflow. And, like, that opens up entirely new opportune for business owners to think about where I can apply technology to my business that makes the sort of iteration or or the work you would have paid a consultant or an adviser to do. It's just it's so different in in this world. When you take out that systems integration problem of making my HubSpot, my QuickBooks, talk to whatever, like, that is far, far less of an issue when AI is very quickly becoming capable

Joshua McNary [00:20:55]:
Kind of a stateless data store in a way because the AI is able to translate between that so seamlessly and quickly. Like we talked about earlier, being able to plug in the AI kind of in the middle of a process, that you were talking about earlier in a way we could do that with the data, the data translation as well between the systems if if needed. And in some cases, these processes eliminate some of those systems, or at least make those systems become less important because some of those systems were were, structured in a very rigid way versus the stateless kind of component that we're talking about here.

Eric Engelmann [00:21:28]:
And, you know, so far, we've talked about it as, you know, data moving it from a CRM to some other thing or pairing the data. But, you know, you've seen the video the the video generation capabilities generation. You know, one of the examples, that I watched a demo of a few months ago was a company called HighTouch. I mean, I mean, we haven't even talked about this one. They had a case study they had done. I believe that's smart. And it was AI basically deciding when and where to, do marketing campaigns online for them and delivering the right ad at the right place and then deciding on its own to stop that one and move it over here. Basically, AB testing between the two different campaigns to say, this is working better.

Eric Engelmann [00:22:05]:
We're just gonna slow this one down. No human is involved in this. It's just the AI doing it on its own. And when you think about the the sort of human work that would go into, hey. I'm doing a marketing campaign today, and I have a hypothesis. If I send this message through this channel, it will get this response. Like, it can do infinite variability and infinitely test them and compare them. And, man, the cost of that is just gonna go wildly down as this kind of technology evolves, and it gets way beyond just

Joshua McNary [00:22:30]:
And more and more personalized.

Eric Engelmann [00:22:32]:
Yeah. Yeah.

Joshua McNary [00:22:32]:
More and more personalized, more and more information that we could never as humans interpret before even if we wanted to. But the Exactly. The AI is gonna help us interpret to come from that marketing perspective.

Eric Engelmann [00:22:43]:
And it never gets tired, and it never complains, and it never has Right. No scheduling conflict. It's just it just does it when you tell it to. I mean, you have to pay a little bit maybe for the cost of it, but, like, you know, the the As

Joshua McNary [00:22:55]:
long as there's somebody somebody, hosting a CPU somewhere and and, and powering it and cooling it and such. Yeah. It's it doesn't run out, other than those, expendables that we currently have to rely on at least with regards to the AI that we have today. Well, so as we're starting to get towards the end of the show here, I wanted to ask then with regards to those that you're helping in Novi, with regards to the startups you're working with, or perhaps even those that you're reaching out to and your examples you've been giving us today, the the people you're reaching out to in health care that are that you're, validating these business ideas with and such, How are they thinking about AI? Right? Well, you and I are both early adopter type technology people. So so how are you seeing them? You mentioned that some of the startups you're you're encouraging them to think AI first as as you are internally. But how are you seeing those around us, whether it be here in the Midwest where we're both located or across the country or even in the world with regards to how how they're actually using AI and and where do you think that curve is at based on real world experience, real world contact with these, individuals?

Eric Engelmann [00:23:58]:
Yeah. I I mean I mean, there are a lot of organizations that have, you know, built, you know, large organizations have built entire team groups that are focused on figuring out how to use AI within how they work. And I would say, you know, they're in our world, it's it's health care. So there's a lot of privacy and security kinds of things that are challenging, big challenges and impediments maybe in the way you approach, these kinds of things. You know, a lot of them are are the same way that you and I would look at, you know, marketing kit for, you know, improving, the speed or accuracy of diagnosis based on

Joshua McNary [00:24:32]:
Yes.

Eric Engelmann [00:24:32]:
Radiological imaging or or whatever it might be. Right.

Joshua McNary [00:24:35]:
Amazing opportunities there. Yeah. But there's there's real world liabilities and legalities and things that have to be dealt with.

Eric Engelmann [00:24:42]:
Yeah. Exactly. So how how does an organization that has, you know, millions of records and images and whatever, how do they go about that? Like, that is that's where they're they're wrestling, and as they should be. I mean, that's a challenging challenging problem to solve. But the ability to, you know, begin with doing the work that people in health care organization do today more efficiently. You know, a lot of the start ups we talk to and a lot of the companies that we're talking to out there who may be the customers for them, a lot of them are trying to figure out how to take the business work off of clinicians. Right? A lot of it is transcribing information into electronic medical records or billing codes and stuff like that. They'll ambient listening to the the conversation, right, which is lots of privacy question, but it can go through and essentially fill out, quote, unquote, the EMR for you

Joshua McNary [00:25:29]:
Yes.

Eric Engelmann [00:25:29]:
Based on happening in the conversation. And then, hey, doc. Is this what happened in the in in the patient encounter? Like, what that what that means to me and, like, this is the the wild thing to me. Like, you and I spent twenty something years of our careers building user experiences for somebody to put information in a system. Like, that's what build a dashboard or a view for. Like, in the future, is that even necessary? Like, is there a UI that we need to build anymore when AI hears the conversation and just sticks it in the system? Like, all of the time we spent building clickable interfaces and menus and drop downs. Like, maybe that's not needed anymore. Like, I don't know.

Eric Engelmann [00:26:08]:
There's something there that's pretty wild as you think about how this evolves over the next three to five years. Like, that's what we're trying to do is get rid of a human typing it into a machine in some sense.

Joshua McNary [00:26:19]:
We are we already we already voice dictate our our our text messages. Right? This this Yeah. Yeah. There's been this iteration from from the keyboard to the mouse to the to the touchscreen to the, you know, all these different and then we're talking about just the continual iteration of that, let alone what you can now what we talked about earlier, which is what you could do with that data, which is what is amazing to us as well. But then, yeah, how do we actually interact with these systems, whether they be, a box somewhere or, device in our pocket or a a droid walking through our our home or what it might be going forward or a car or whatever. Well, so let me let's bring it back to Earth here for a minute, with regards to what do you think is your biggest challenge around technology right now inside of of your work, and maybe what's kind of the next challenge you're gonna try to take on?

Eric Engelmann [00:27:06]:
I don't need any more challenges to take on. I but, you know, I think in the context of ISA Ventures and Innovi, you know, the finding the right balance because there is so much opportunity in the technology and, like, the cost and and time needed to build it has come down astronomically in the last three years, that, you know, figuring out how and when to, you know, spend the time on those things on for behalf of ISA Ventures or Novi is where a lot of the challenges or our customers or our startups. Like, there's just there's more to do than could possibly done is prioritizing Strategizing and value. Focusing. Yep. Yep. And, you know, what's practical for people to do today? I mean, you and I can, you know, envision a future where there are no UIs anymore for software. But, you know, when I think about it today, a lot of the startups have problems that need to be solved today that can make them more viable, more, faster grow faster, whatever their their issues are.

Eric Engelmann [00:28:02]:
It's it's, swapping down those issue as best we technology. That's okay. Yeah.

Joshua McNary [00:28:05]:
That makes a lot of sense. Okay. Well, here's our final question. So what is one actionable tip that you would give to those who are listening here today that they can do within their business to better leverage technology?

Eric Engelmann [00:28:18]:
And for me, the technology is, a mechanism to do whatever is valuable, you as a business owner or leader or your customers. And the ability to step back and really think about where that value comes from, and what's the fastest, best, easiest way to deliver it and then step into the technology? How can I use technology to then deliver that way possible? Like, there's there's something about, I think, the way we we train people, in in jobs that I think makes them think that they need to fall back on a process that exists and not maybe think about it from the sort of raw principle of how did we get from this information valuable to someone. Mhmm. Like, that's what every startup is trying to figure out. Right? How do I make something valuable? Some of them will so it's kinda baked into startup thinking valuable. But for existing business owners and leaders, the ability to step back and look at it that way is the crucial first step.

Joshua McNary [00:29:11]:
And that and that creeps that creeps right into even startups very early. Right? The process and the trying to implement and and actually do the thing. So spoken like a a true entrepreneur, a true solution oriented person that I know you are, your answer does not surprise me.

Eric Engelmann [00:29:27]:
Well, it is it's because as you know, when you have technical skills, there's an instinct to I'm gonna fire up and write some code today. And sometimes that's a good exploration. So maybe sometimes you need to kinda alternate a little bit because you don't know what's possible until a little bit. But, you know, understanding where the value comes from has to be done first. So, you know, fight the instinct to write code on day one of whatever it is, whether it's a new product or fixing a process that already exists is a challenging one to figure out how to balance this.

Joshua McNary [00:29:54]:
Don't write the code first. Don't write the prompt first, talking about AI, without thinking about what's important first. Alright, Nick. Well, this has been great. So where can people find out more about you online and your various things that you're doing if they wanna get in touch?

Eric Engelmann [00:30:09]:
Yeah. Easiest is probably LinkedIn. And from there, no vventures.com and isaventures.com, are out there, and we can happy to talk about this stuff. It's, it's exciting times as, in the venture world, in real world, and, excited to explore and see where this future leads us.

Joshua McNary [00:30:26]:
Perfect. Thanks for joining me today, Eric.

Eric Engelmann [00:30:28]:
Appreciate it, Josh. Thanks.

Joshua McNary [00:30:29]:
Alright, folks. That's it for today. I'm Joshua McNary, and I hope you will join me again next time so you can learn how to become a biz tech superhero. Bye now.