EXPERIENCE 202 | Rick Gardner - Bull Rider, Roofer, Rocket Scientist, Professional Walleye Fisherman, Serial Entrepreneur, Venture Hub Founder, and EOS Implementer

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Rick Gardner is an EOS implementer in our Northern Colorado region.

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He grew up in Leadville, Colorado, and had his dreams of a long professional bull riding career ended by injury.

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He's gone on to a series of interesting professional and entrepreneurial ventures, and his previous chapter was Founding and Growing a Venture Accelerator and Investment Hub, aligned with the University of Buffalo in New York, which served over 150 companies and raised over 100 million in capital.

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Disclaimer, we forgot to talk about the Professional Walleye Fisherman chapter.

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Enjoy.

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Let's have some fun.

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Welcome to the LoCo Experience Podcast.

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On this show, you'll get to know business and community leaders from all around Northern Colorado and beyond.

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Our guests share their stories, business stories, life stories, stories of triumph and of tragedy, and through it all, you'll be inspired and entertained.

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These conversations are real and raw and no topics are off limits.

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So pop in a breath mint and get ready to meet our latest guest.

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Welcome back to the Loco Experience Podcast.

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My guest today is Rick Gardner and Rick is an EOS implementer.

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He's an inventor, a serial entrepreneur, and the creator of the iHub accelerator and investment fund in upstate New York.

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And then he moved here.

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Why'd you move here, Rick?

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Well, I'm from here.

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You're from here?

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Yeah, I went out there.

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I remember that.

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Yeah, that's right.

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I went out there just for that opportunity.

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And then for family reasons, I came back to Colorado.

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Yeah.

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Yep.

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Um, where should we start?

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Like, uh, let's, tell me about your first invention.

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Let's go there.

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Um, let's.

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Even if it didn't pan out.

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Like, even if you were a teenager and never went anywhere.

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Yeah.

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Um, I had a lot of inventions when I was a kid.

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Um, I guess my first real invention was after I graduated from college.

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Um, I went to work at, um, Lockheed Martin.

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Okay.

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And, um, there was a, a rocket called the, the Titan rocket.

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And it had, um, this problem called Pogo, where it would explode after it left the launch pad.

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Okay.

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And so I worked on an invention to, uh, mitigate that.

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That was like the Titan right?

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Yeah.

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Yeah.

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Yeah.

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Yeah.

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And, you know, so that was kind of my first post college invention.

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Um, and then I went to Hewlett Packard.

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Well, what, like, you put an anti explosion device on it?

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Well, it's, it's kind of technical, but, um, basically I changed the natural frequency of the, of the propellant feed line.

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Oh.

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Which prevented the, the, uh, It was creating like a harmonic imbalance virtually.

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Exactly.

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Yeah, exactly.

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Tuning fork done wrong.

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Right, right, exactly.

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Okay.

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Yeah.

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Yeah, yeah.

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Very intuitive of you.

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I'm, uh, I like to say I'm an inch deep and a mile wide.

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Like, I don't know much about much.

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Yeah.

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But I can understand things faster than a lot of people.

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Yeah, yeah.

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A little bit.

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Yeah, so.

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But only that deep.

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It's over my head if we keep going.

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Yeah, I'm, I'm similar.

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So, so lucky to say this.

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Yeah.

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Yeah.

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Yeah.

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Let's have him do some more stuff or?

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Yeah.

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And so, you know, I, um, I worked on a lot of really cool things.

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Um, the Cassini spacecraft that went to Saturn had a similar problem.

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Okay.

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They found it just before, um, they were going to launch the vehicle.

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Okay.

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So 30, 30 days before, um, they found this instability in the test pad.

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Okay.

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So they asked me to figure out how to fix it.

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Because if we missed the launch window, uh, for the trip to Saturn, we would have had to wait.

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Yeah.

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17 years later, you're like ready to go again.

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Yeah.

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Interesting.

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Yeah.

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It was a similar, similar problem.

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So I kind of became the de facto combustion stability guy.

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Hmm.

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Interesting.

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So, um, yeah.

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It could have worked in, uh, like racing at formula one or something like that.

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Right.

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Instead too.

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Yeah.

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Yeah.

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Cause I've, I've, that's a lot of the, like how, how fuels and, you know, And mechanics react at the extreme.

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Exactly.

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Is really the secret in racing and rockets, probably.

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Right, yep.

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Yeah, and with rockets and even, you know, race cars, everything's, everything's right at the limit, right?

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So, anything that, there's not a lot of margin for error.

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Yeah, yeah.

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Let's, uh, let's shift to what you're doing now.

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We'll talk more about unfolding your journey, but, uh, EOS for those that are uninitiated, uh, on the entrepreneur's operating system.

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I know that much.

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Yeah.

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Um, do you want to set the stage?

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I've had a, I think you're probably our fourth.

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Okay.

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EOS implementer on right at the end of our fourth or start of our fifth season here.

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So, uh, it's something I'm endlessly curious in and I think people need to know more about it.

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Yeah.

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So.

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You know, I, I mean, the bottom line for what EOS is, is it helps get a group of people from point A to point B in the most efficient and effective way possible.

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Okay.

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And it sounds simple, but the first question is, where is point B?

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Yeah.

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Right?

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It's kind of hard to get everybody to go in the same direction if you're not sure where point B is.

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Yeah, yeah.

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Right.

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And so.

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You know, that's, that's really what it's about is getting all the human energy in an organization to go in the right direction.

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And in order to do that, everybody in the organization has to share the vision for where point B is and the plan for getting to point B.

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Yeah, yeah.

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And so, you know, it's really, that's kind of the simplified view of it.

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But, um, you know, what EOS is based on is six key components of any business.

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And it turns out that, you know, about 5 percent of businesses are really good at those six key components.

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Okay.

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And they're, those are the great companies.

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And, you know, about 95 percent of the companies are only good in a few of those key components, and they're kind of successful in spite of themselves.

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Yeah, yeah.

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So it's really well in 40 percent of the companies are kind of bad at some of them.

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They'll be gone in five years.

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Yeah Yeah, yeah, and and and it's really just you know the other thing that happens to with entrepreneurial organizations is we start them and You know, we kind of get things going based on our our intuition, right?

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Yeah, yeah, and we don't find until we get to a certain number of employees that our intuition is no longer gonna carry the day Yeah, yeah.

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Yeah.

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Well, and you met my small team here, you know, I've got just enough, you know Communication and vision to keep them on track ish But if we got much bigger much more complicated, it would be that much harder Yeah, and and a lot of times what happens is is that That kind of tends to creep up on us that we've grown to a point where, um, you know, it's, it's beyond our previous methodology.

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But also driving ownership, discipline and accountability.

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Yeah.

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You have to know where you're going.

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Everybody has to be aligned with that.

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You have to have the right team.

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You know, and you have to do it with discipline and accountability.

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It's funny, I, I told this story for years before I ever heard of EOS, uh, but it was kind of the same theme in that, um, have you ever been to Colorado Springs area, 11 mile reservoir?

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Yeah, yeah.

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Yeah.

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So, Jill and I got caught up by a Sleet and a huge wind and to make any progress, we had to be pointed exactly into the wind and row at the same exact time, because if we were off kilter on the road, we just sat there.

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If we turned sideways, we went back 50 yards, and I use that as a example of how teams can really be more powerful together, right?

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If you had eight rowers on each side of an old Viking boat, and one guy was goofing off, right?

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You would know it.

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Right.

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And that's what, right.

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And that's what maybe helps you find that guy goofing off That's right.

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That's right.

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Yeah.

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Yeah.

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That one guy can make the, the boat go in circles.

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Yeah.

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Right.

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Yeah.

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Interesting.

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Yeah.

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Yeah.

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So it's, it's really about all of those things coming together.

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And, you know, the other part that's pretty powerful about it is, you know, when we talk about the six key components mm-hmm Um, it's tough to get to the root cause of issues in a business.

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if you're not strong or strengthening those six key components.

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So a lot of things could be misdiagnosed.

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For example, if you think you have a people issue, but your, your plan isn't clear or accountability isn't clear, it's really tough to say whether or not you have a people issue.

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Yeah.

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Right.

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Interesting thing.

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Yeah.

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If you don't have ownership and accountability.

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Yeah.

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So Reflecting on a conversation I had with Alma here recently, um, she's been in the operations manager role for, I don't know, 16 months or something like that.

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And, you know, really, um, came into the role with a vision of making it easier for LOCO to grow and have that good experience for the members and stuff.

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And, and we've improved that.

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And, um, We're not growing as fast as we maybe have in the past.

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So she was like, Oh, maybe I'm doing, maybe I'm the problem, you know?

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And I was like, I don't think so.

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You know, I'm pretty confident if I had a 40 year old instead of a 22 year old.

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Like we'd still be stumbling over the same challenges.

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Yeah.

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Um, you know, let's call it intuition, but that's the way it is.

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Well, and that's a good sign if she's, if she's reflecting like that.

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Yeah, for sure.

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No, I mean on the GWC, she's easy.

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You know, whether we have it in the right seat, for sure.

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We don't know necessarily.

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So I guess maybe can we start with the, what are those six, uh, areas?

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Yeah.

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Yeah.

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Turn the lens on.

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Yeah.

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And it's, it's none of it's rocket science.

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It's all, it's pretty common sense, right?

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But, uh, the first one is the vision component and that's kind of as it sounds, you know, um, making sure that you have clarity on your vision and everybody in the organization is 100 percent on the same page with that vision.

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We have a special way or a unique way to define vision because vision is kind of an overused term everywhere.

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Everybody has a different definition.

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We have a pretty specific definition of what a vision is, but that's the first component.

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The second component is the people component.

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And like you were talking about earlier, Um, it's not only having the right people in there, you know, the right people to fit your culture, but also the right seats for those people.

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And, um, You know, that's a very important thing and getting the vision component strong and the people components strong leads you to the next component.

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And that's really the data component.

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And that's understanding what are the fundamental things that are driving your business.

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What are the things we should be looking for?

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It's kind of like the dashboard almost.

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Right.

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Right.

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Like what, if you were going to have a bill of dashboard, what needs to be on there?

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Right.

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And you know, I see two extremes.

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Um, some companies don't gather any data.

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Yeah.

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Right.

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Others gather too much data, and they choke on it, and they're not sure what's important, so everything's important, right?

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And so, but it turns out if you're good with the vision, the people, and the data component, then you're pretty, you're starting to get pretty good at identifying issues, and that's the next component.

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Okay.

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Is, is the issues component, and it's creating a transparent organization that's comfortable bringing up issues.

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But it's also really good at prioritizing and diagnosing, getting to root cause and making those issues go away.

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The next component is the process component and it's really putting that structure in place in the organization so that, um, you do things the right way every time.

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Yeah.

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And you know, it's, again, kind of that entrepreneurial approach.

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I haven't really thought of it this way before, but I'm almost thinking about like a race car.

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Yeah.

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Uh, right.

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Like the people.

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It might be the driver, it's the head mechanic and stuff.

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The issues is, why does this keep breaking when we do this?

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You know, the process is kind of like, okay, in turn three, if we set up the drift early Right.

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And, you know, you know, hit the, hit the throttle right at halfway point.

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Right.

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We'll come out of it perfect.

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Right.

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And, and, and, you know, what happens too is, is as your organization grows, You know, um, process isn't that is, isn't as important when you have one or two or three or four people in your organization.

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But then you start hiring people, you've got, maybe you've got a dozen or a couple dozen.

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And now that becomes an issue, right?

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Because you no longer intuitively know your processes.

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They kind of have to be documented and simplified, right?

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Yeah, and then you lose three out of those first four fully trained people.

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And some of the new people don't really have the right tools.

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Process in mind anymore.

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And so unless it's documented, you can lose a lot.

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Yeah.

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And, and, you know, I, I really preach this simplified approach, which is, you know, what are the seven or eight core processes for your business?

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What are the few steps that are required to do it?

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Right.

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So kind of a 20, 80 approach, 20 percent of the steps will get you 80 percent of the value.

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Trying to get a hundred percent of everything documented to get you a.

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700 page SOP that nobody reads.

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Yeah.

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I like it.

00:12:40.394 --> 00:12:51.104
And so, you know, once you start strengthening all of those, then, um, the, the, uh, traction component is the sixth component and that's really driving that ownership and accountability throughout the organization.

00:12:51.104 --> 00:12:51.533
And so.

00:12:52.099 --> 00:12:58.649
So, really working on all six in parallel is, is the key to, to really making progress.

00:12:59.678 --> 00:13:02.328
Um, what got you excited about EOS?

00:13:02.339 --> 00:13:04.278
Is this part of your own journey?

00:13:04.278 --> 00:13:05.649
Did you use it in some of your companies?

00:13:05.649 --> 00:13:06.798
I did.

00:13:06.798 --> 00:13:17.269
And, um, when I first read Traction, I think what, what really appealed to me is it reflected my leadership and management style.

00:13:17.318 --> 00:13:17.538
Mm.

00:13:18.408 --> 00:13:18.938
And.

00:13:19.448 --> 00:13:29.698
And, and it was so simple, simply described and, and intuitively easy to understand it's excuse me.

00:13:30.548 --> 00:13:35.639
It's very similar to everything I've done throughout my career in a much more elegantly defined way.

00:13:35.649 --> 00:13:35.828
Yeah.

00:13:35.828 --> 00:13:36.089
Yeah.

00:13:36.399 --> 00:13:38.629
And so I thought it was very powerful.

00:13:38.749 --> 00:13:39.759
I wonder if it's from that.

00:13:39.769 --> 00:13:46.288
I remember from an early loco think tank chapter meeting, um, Todd Gilson, I think he was the quote master.

00:13:46.288 --> 00:13:48.889
But, uh, Complicated is interesting.

00:13:48.889 --> 00:13:49.739
Simple gets done.

00:13:50.418 --> 00:13:50.719
Yeah.

00:13:50.769 --> 00:13:56.708
I don't know if that was, uh, from the traction book or something similar to that, but that's kind of the theme you're talking about here is it is.

00:13:57.028 --> 00:14:05.778
And, you know, being a, an engineer and a designer too, um, you know, the simplest designs are the most difficult to achieve, right?

00:14:06.788 --> 00:14:10.538
A lazy engineer makes very complicated designs, right?

00:14:11.048 --> 00:14:15.139
And so there's a lot of, there's beauty in that simplification and elegance.

00:14:15.168 --> 00:14:15.479
And.

00:14:16.259 --> 00:14:25.139
Because it's, it's, it's so simple to understand, people, um, get the illusion that it's also simple, simple to implement.

00:14:25.249 --> 00:14:25.849
Yeah, yeah.

00:14:25.908 --> 00:14:27.818
Right, and that's where the challenge lies.

00:14:28.119 --> 00:14:31.099
But conceptually, it's very easy to comprehend and understand.

00:14:31.099 --> 00:14:31.938
It all makes sense.

00:14:32.009 --> 00:14:32.288
Yeah.

00:14:32.298 --> 00:14:36.609
It's not the management du jour that, that we all read about, right?

00:14:36.739 --> 00:14:43.149
So, in your role as a, as a EOS implementer, like, what's that look like, I guess, from, from your shoes?

00:14:43.149 --> 00:14:52.188
You You connect with businesses, mostly 1, 2, 4 million dollar businesses that want to be 2, 4, 10, 20 million dollar businesses?

00:14:52.349 --> 00:14:52.729
Yeah.

00:14:52.729 --> 00:15:00.639
And you know, it's, you know, the revenue is part of it, but really when things start to break, it's by number of employees.

00:15:00.818 --> 00:15:01.168
Okay.

00:15:01.818 --> 00:15:06.489
So when businesses get to around 10 employees, that's when things start to break.

00:15:07.068 --> 00:15:08.259
So that's kind of the entry point.

00:15:08.298 --> 00:15:08.589
Okay.

00:15:08.688 --> 00:15:08.938
Yep.

00:15:09.229 --> 00:15:10.649
That was actually my, my original question.

00:15:11.144 --> 00:15:20.774
Entree to the market with loco think tank was what we called thinkers and it was mostly five to twenty employees Yep, partly because when when you get up around eight was what I was used to tell people.

00:15:20.974 --> 00:15:26.464
Yeah, you know the More than eight can't really be managed by one person, right?

00:15:26.524 --> 00:15:31.504
You know and and unless they're a superb manager and then are they still doing the other things they need to do, right?

00:15:31.524 --> 00:15:42.739
Yeah, and so that's where things start to break is, you know when they get into that range and But a lot of times, you know, maybe they'll get to 20 or 30 employees and then they hit some sort of a ceiling and they're not sure why.

00:15:43.178 --> 00:15:51.219
And, you know, that's where I can come in and help figure out what, where we might, where we might have some problems and how we might be able to help.

00:15:51.278 --> 00:15:54.578
And what kind of training do the implementers have?

00:15:54.599 --> 00:15:56.458
Because EOS has become a big Yeah.

00:15:56.558 --> 00:16:00.533
Oh, a big I don't know how many, is there a thousand implementers around the country yet?

00:16:00.634 --> 00:16:01.793
No, there's not that many.

00:16:01.793 --> 00:16:05.193
I think there's probably, um, worldwide, probably 700.

00:16:05.224 --> 00:16:05.504
Okay.

00:16:05.624 --> 00:16:05.964
Okay.

00:16:05.964 --> 00:16:07.673
So it's not saturated by any means.

00:16:07.793 --> 00:16:08.494
No, no.

00:16:08.644 --> 00:16:09.323
In that market.

00:16:09.323 --> 00:16:13.344
But no, but they have developed a big platform training program at this point.

00:16:13.394 --> 00:16:13.703
Yeah.

00:16:13.703 --> 00:16:19.614
And it's, it's really the, you know, the prerequisite is, you know, a lot of experience as an entrepreneur.

00:16:19.614 --> 00:16:20.354
Have you done something?

00:16:20.464 --> 00:16:21.153
Yeah, right.

00:16:21.203 --> 00:16:21.464
Yeah.

00:16:21.543 --> 00:16:21.783
Okay.

00:16:21.783 --> 00:16:24.953
No, you can't just become an EOS implementer because you think it would be fun.

00:16:24.984 --> 00:16:25.173
Yeah.

00:16:25.173 --> 00:16:25.283
Yeah.

00:16:25.283 --> 00:16:25.543
Right.

00:16:26.114 --> 00:16:31.634
And so they have a pretty severe or pretty rigorous vetting process to make sure that you've got the chops to do it.

00:16:31.653 --> 00:16:32.173
Makes sense.

00:16:32.254 --> 00:16:44.933
And you've got the experience to do it, but also the kind of the psychographic profile to do it, which is, you know, you're open, you're honest, you're humbly confident, you know, a lot of those kinds of things.

00:16:45.764 --> 00:16:48.374
And do they have like their own kind of vetting system in that regard?

00:16:48.504 --> 00:16:49.114
Yeah, they do.

00:16:49.173 --> 00:16:50.394
Oh, I think, is it Colby?

00:16:50.604 --> 00:16:50.884
No.

00:16:51.384 --> 00:16:54.094
Um, Colby's part of it, but it's not a really big part of it.

00:16:54.163 --> 00:17:01.553
Um, What they do is they, you know, they have members of the community will, will interview, um, Oh, interesting.

00:17:01.783 --> 00:17:04.634
interview people who want to become an EOS implementer.

00:17:04.923 --> 00:17:09.723
Typically what you need is a, is a referral from somebody who's already an implementer that vouches for you.

00:17:09.874 --> 00:17:10.203
Okay.

00:17:10.253 --> 00:17:14.034
And then there's a whole, uh, vetting and interview process that they go through.

00:17:14.034 --> 00:17:14.453
Interesting.

00:17:15.054 --> 00:17:18.413
And then, like, you get, kind of, certified or whatever.

00:17:18.413 --> 00:17:20.663
You start, and then you hunt your own fish, kind of thing.

00:17:20.673 --> 00:17:20.969
Yeah, yeah.

00:17:20.969 --> 00:17:21.614
Is that right?

00:17:21.653 --> 00:17:21.973
Yeah.

00:17:22.044 --> 00:17:23.523
You go to a week long training.

00:17:23.634 --> 00:17:23.983
Yep.

00:17:24.084 --> 00:17:25.463
And then, um, yeah.

00:17:26.138 --> 00:17:30.459
And then, uh, you know, clients, and then EOS takes some portion of your, of your fees.

00:17:30.459 --> 00:17:32.499
No, they just have a flat, a flat.

00:17:32.588 --> 00:17:33.088
Oh, really?

00:17:33.148 --> 00:17:37.489
You pay a flat fee to be one and then do as much work or as little within that as you want to?

00:17:37.538 --> 00:17:37.818
Yep, yep.

00:17:37.818 --> 00:17:38.298
Oh, interesting.

00:17:38.298 --> 00:17:38.558
Yep, yep.

00:17:39.838 --> 00:17:40.689
Probably makes sense.

00:17:41.138 --> 00:18:02.788
You know, the, the cynical person in me is like, you know, Be nice if they could just get 40 percent of whatever you make for them, you know, but yeah No, it's that's one of the things that's appealing about the community to me Yeah, this kind of abundance mindset Which is you know, if you if you do the right thing if you help first everything else takes care of itself Yeah, yeah, that's cool.

00:18:03.318 --> 00:18:20.124
Um Let's talk about kind of your principles for business, like outside of the traction model or whatever, like what's, what's, what, what does Rick really stand on when it comes to, to maybe even defining what clients you'd want to work with and, and, you know, your set of parts, let's say.

00:18:20.173 --> 00:18:20.534
Yeah.

00:18:20.534 --> 00:18:30.653
So, you know, for me, um, the type of clients I like to work with are, are people who are open and honest and, and vulnerable.

00:18:30.653 --> 00:18:30.703
Yeah.

00:18:31.148 --> 00:18:32.538
willing to admit they need help.

00:18:33.669 --> 00:18:35.739
It fills my cup to help people.

00:18:36.308 --> 00:18:39.759
And I'm not interested in helping people who don't want my help.

00:18:40.239 --> 00:18:40.499
Yeah.

00:18:40.519 --> 00:18:40.719
Right.

00:18:40.939 --> 00:18:42.778
Well, it's impossible usually anyway.

00:18:43.138 --> 00:18:59.808
And, and, and part of that too, is, is people who want to continue to grow and to continue to improve and, um, you know, in terms of, you know, in terms of my management style, it's always been to really try to manage by objective.

00:19:00.769 --> 00:19:06.979
And, and that's one of the things I hit on quite a bit in, in EOS is there's this concept of delegating.

00:19:07.259 --> 00:19:07.628
Sure.

00:19:08.929 --> 00:19:14.038
It's not very powerful to delegate a handful of tasks to someone, although sometimes you have to do that.

00:19:14.499 --> 00:19:21.929
What's really powerful is to delegate a significant objective to someone and let them figure out how to achieve that objective.

00:19:22.028 --> 00:19:22.489
Yeah, yeah.

00:19:22.568 --> 00:19:31.548
That's where you have a lot of power and that's where really hiring the best people you can find, getting clarity on their objective and leaving them alone is where you get a lot of power.

00:19:32.469 --> 00:19:48.403
Yeah, that's an intriguing, obviously I transmit a lot of these thoughts to my own situation and like, one of the things I know we'd like to do at Loco Think Tank is, what's that uh, FPS system or FMS system, how much your, your members would refer you.

00:19:48.703 --> 00:19:58.503
Uh, I forget what the name of it is, but like, I think that would be really useful for us to really be curious, more curious about how interested our members would be to refer to us.

00:19:58.554 --> 00:19:58.983
Right.

00:19:59.074 --> 00:19:59.473
Right.

00:19:59.473 --> 00:20:01.844
And which chapters are the strongest in that?

00:20:01.854 --> 00:20:05.673
Cause that's like a, to me, almost like a indicator of health in general.

00:20:05.713 --> 00:20:06.114
Right.

00:20:06.334 --> 00:20:08.328
Um, But it's quite a project.

00:20:08.439 --> 00:20:08.739
Yeah.

00:20:08.769 --> 00:20:10.199
And it's not just a bunch of tasks.

00:20:10.199 --> 00:20:11.134
Right.

00:20:11.134 --> 00:20:12.068
Right.

00:20:12.068 --> 00:20:16.749
Um, and, and I'm not necessarily the organizational process development person.

00:20:16.749 --> 00:20:20.469
So, you know, rather than being like, Hey, let's dip our toe into this.

00:20:20.499 --> 00:20:28.209
No, the objective is by end of Q2 Alma, you want to have a real systemized way of sampling this without driving our members crazy.

00:20:28.239 --> 00:20:28.598
Yeah.

00:20:28.648 --> 00:20:30.128
And that's, that's the objective.

00:20:30.189 --> 00:20:30.479
Right.

00:20:30.489 --> 00:20:31.419
And that's powerful.

00:20:31.439 --> 00:20:34.989
And, you know, I'll tell you kind of a lesson I learned in my.

00:20:35.489 --> 00:20:36.318
In my career.

00:20:36.409 --> 00:20:36.679
Yeah.

00:20:36.759 --> 00:20:39.409
Um, when I was at Lockheed Martin, I got promoted.

00:20:39.888 --> 00:20:41.378
probably far too early.

00:20:42.489 --> 00:20:49.429
And, um, I didn't realize it at the time, but I, I wanted that promotion for all the wrong reasons, right?

00:20:49.469 --> 00:20:51.378
I was a mechanical engineer.

00:20:52.088 --> 00:20:58.179
Um, I wanted my ideas to be the ones that had the most weight, you know, I thought I knew best.

00:20:58.568 --> 00:21:08.409
And so I became, you know, I took that leadership position because I thought, I don't know, more about ambition kind of, yeah.

00:21:08.818 --> 00:21:09.239
If you will.

00:21:09.249 --> 00:21:09.638
Yeah.

00:21:09.769 --> 00:21:10.219
And.

00:21:11.134 --> 00:21:19.554
And it was a little dis, it was a little bit of a, I didn't realize it at the time, but I was leading a bunch of engineers that were in the same discipline as me.

00:21:20.124 --> 00:21:21.324
And I thought I knew best.

00:21:22.614 --> 00:21:26.604
And then fast forward a few years, I got promoted at, at Hewlett Packard.

00:21:27.753 --> 00:21:32.324
And I had people with PhDs in electrical engineering.

00:21:32.324 --> 00:21:33.554
I had software engineers.

00:21:33.554 --> 00:21:36.624
I had, you know, a lot of different engineering disciplines.

00:21:37.374 --> 00:21:38.423
reporting to me.

00:21:38.443 --> 00:21:40.663
And I, and I was like, what am I here for?

00:21:40.663 --> 00:21:54.153
If I'm, if, if I know less than anyone reporting to me and at a very wise manager, tell me you have to understand now the product that you, that you create now is a high performance team.

00:21:55.423 --> 00:21:57.854
You still think you're trying to create new products.

00:21:58.534 --> 00:22:01.304
You're creating a high performance team that creates products.

00:22:01.433 --> 00:22:03.213
Your product is the team.

00:22:04.263 --> 00:22:08.064
And so that's what, when I had kind of a transformation that.

00:22:09.388 --> 00:22:14.709
Now I have to be very good at setting objectives because I'm not going to be able to tell them task by task what to do.

00:22:15.679 --> 00:22:17.588
I have to make sure the objective is clear.

00:22:18.429 --> 00:22:23.878
And then if they need help figuring out how to achieve that objective, That's a separate conversation.

00:22:24.538 --> 00:22:27.469
And so that's when I started to grow as a leader.

00:22:27.519 --> 00:22:29.628
Were you really good at people already?

00:22:30.269 --> 00:22:34.699
A lot of times people imagine the engineer type to be kind of, well, people averse.

00:22:34.729 --> 00:22:35.098
Yeah.

00:22:35.098 --> 00:22:36.989
I mean, I'm not your typical engineer.

00:22:36.989 --> 00:22:47.459
I, a lot of people, we could talk about my background before that at some point, but I became an engineer cause I was really good at designing and creating things.

00:22:47.919 --> 00:22:48.568
And I thought.

00:22:48.909 --> 00:22:51.989
If I become an engineer, I'll be even better at creating and designing things.

00:22:52.489 --> 00:22:57.179
A lot of people become engineers cause they were good in math and science in high school and somebody told them to be an engineer.

00:22:57.538 --> 00:22:59.528
And it's really a struggle for them to be creative at all.

00:22:59.588 --> 00:23:00.429
Right, right.

00:23:00.449 --> 00:23:03.179
And so I went into it in a little bit different.

00:23:03.679 --> 00:23:09.138
And so I've always been kind of atypical in terms of, you know, the social interaction.

00:23:09.548 --> 00:23:12.868
Managing by objectives is one of your big criterias, I think I hear.

00:23:12.868 --> 00:23:19.058
Is there other things you want to draw while we're, Well, I mean, just management by objective.

00:23:19.159 --> 00:23:23.388
Um, you know, I hired, I try to hire the best people I can find.

00:23:23.983 --> 00:23:25.963
and trust that they want to do a good job.

00:23:26.884 --> 00:23:30.314
I don't, you know, and, and I do trust from day one.

00:23:30.864 --> 00:23:33.673
A lot of people say, you have to prove to me that I can trust you.

00:23:34.534 --> 00:23:37.693
Which that's a little bit difficult to do if they decide.

00:23:38.584 --> 00:23:39.903
Well, they can choose not to still.

00:23:40.423 --> 00:23:40.624
Yeah.

00:23:40.624 --> 00:23:43.183
We had, uh, Oh, I forget his name.

00:23:43.183 --> 00:23:44.584
Trustology is this book.

00:23:45.443 --> 00:23:47.614
Um, he's a local guy, smart guy.

00:23:47.763 --> 00:23:52.854
And that's kind of the premise of the book is, is you can't, Earn trust, you can only grant it.

00:23:53.064 --> 00:23:54.084
Right, right.

00:23:54.084 --> 00:23:54.624
Ultimately.

00:23:54.683 --> 00:23:55.013
Right.

00:23:55.584 --> 00:24:00.324
So and so, I, it's always served me well to, to trust that people wanna do a good job.

00:24:00.384 --> 00:24:00.624
Yeah.

00:24:00.773 --> 00:24:01.794
And they're motivated.

00:24:01.854 --> 00:24:04.044
And if they're not successful, it's because of me.

00:24:05.153 --> 00:24:07.463
That's, that covers 99% of the cases.

00:24:07.493 --> 00:24:07.763
Okay.

00:24:10.034 --> 00:24:14.074
And, uh, anything else that are kind of your big commonalities?

00:24:18.618 --> 00:24:20.348
Um, Potentially, I can't think of any right now.

00:24:20.669 --> 00:24:20.919
Yeah.

00:24:21.009 --> 00:24:32.594
You know, I think this is going to be a better unfold as We go back to your, your roots anyway, and kind of explore that journey out of big corporate ultimately into kind of that serial entrepreneur space.

00:24:32.923 --> 00:24:36.644
Um, but we usually go back even further to like first grade.

00:24:36.713 --> 00:24:37.054
Yeah.

00:24:37.324 --> 00:24:39.144
So were you Colorado already then?

00:24:39.584 --> 00:24:42.294
Um, so I was born in Colorado.

00:24:42.344 --> 00:24:42.614
Okay.

00:24:42.634 --> 00:24:44.023
Um, my parents were in college.

00:24:44.223 --> 00:24:45.273
And where was, where was that?

00:24:45.284 --> 00:24:47.324
They, they were in Alamosa at Adams state.

00:24:47.364 --> 00:24:47.804
Okay.

00:24:48.124 --> 00:24:55.463
And, um, I was Still young, I don't remember when this happened, but my dad got his first job out of college.

00:24:55.523 --> 00:24:55.864
Okay.

00:24:56.084 --> 00:24:58.374
And we moved to New Jersey.

00:24:59.163 --> 00:24:59.574
Okay.

00:24:59.663 --> 00:25:00.693
For a year or two.

00:25:01.314 --> 00:25:03.844
Then he got transferred to California for a year or two.

00:25:04.314 --> 00:25:05.653
Then we moved back to Colorado.

00:25:05.884 --> 00:25:11.314
And tell me, what was the circumstance, maybe, of them being at college at Adams State University?

00:25:11.788 --> 00:25:13.778
Were they from Colorado families as well?

00:25:13.788 --> 00:25:14.189
Yeah.

00:25:14.749 --> 00:25:16.298
My mom grew up in Walsenburg.

00:25:16.358 --> 00:25:16.729
Okay.

00:25:16.769 --> 00:25:16.979
Yep.

00:25:17.019 --> 00:25:18.648
Um, my dad grew up in Steamboat.

00:25:18.798 --> 00:25:19.128
Yep.

00:25:19.239 --> 00:25:22.989
And, uh, he was an athlete, so he had a wrestling scholarship to Adams State.

00:25:23.009 --> 00:25:23.308
Gotcha.

00:25:23.338 --> 00:25:23.699
Gotcha.

00:25:23.739 --> 00:25:24.679
And that's where they met.

00:25:24.749 --> 00:25:29.151
And so they had, um, At least two, they, well they had two.

00:25:29.151 --> 00:25:31.824
And from Walsenburg, like, Alamosa is like a city.

00:25:31.864 --> 00:25:32.814
Right, exactly.

00:25:32.933 --> 00:25:33.413
Metropolis.

00:25:33.414 --> 00:25:34.933
Right, right, yeah.

00:25:35.433 --> 00:25:37.523
Yeah, so they had two of us when they were still in college.

00:25:37.523 --> 00:25:37.903
Cool.

00:25:38.034 --> 00:25:38.374
Yep.

00:25:38.903 --> 00:25:46.773
And, uh, so you kind of got to experience this, this city life, uh, as you, as a toddler kind of thing, and then back to Colorado.

00:25:46.864 --> 00:25:48.433
Yep, yep, yep.

00:25:48.773 --> 00:25:51.294
Move back to Leadville and what okay?

00:25:51.614 --> 00:26:00.203
It's interesting place to grow up there, too I imagine yeah, so that's probably what in some of your earliest actual memories are you're like a middle You know a middle elementary of at this point.

00:26:00.203 --> 00:26:00.534
Yep.

00:26:00.594 --> 00:26:03.513
Yeah, and what was what was young Rick like?

00:26:03.513 --> 00:26:06.953
What would your what would your third grade teacher describe you as in Leadville or fourth grade?

00:26:07.054 --> 00:26:14.354
Um, that's a good question I don't think people thought I was a very good student.

00:26:14.433 --> 00:26:16.963
Yeah I Just not paying attention enough.

00:26:16.973 --> 00:26:17.564
Yeah.

00:26:17.673 --> 00:26:19.213
Yeah, I think I wasn't paying attention.

00:26:19.213 --> 00:26:26.844
I don't think I was Real energized about school at that age, you know Were there more siblings to come by the way?

00:26:26.923 --> 00:26:29.493
Yeah, so I have an older sister and a younger sister.

00:26:29.493 --> 00:26:30.243
Okay, okay.

00:26:30.493 --> 00:26:39.064
Yeah, and So you're cruising along and how long in in Leadville or what was some of the major milestones there as you grew?

00:26:41.503 --> 00:26:46.574
You know I'm trying to remember the, the earliest things.

00:26:46.644 --> 00:26:47.683
Um, you know.

00:26:47.693 --> 00:26:48.614
Yeah, what was the culture of that town?

00:26:48.614 --> 00:26:51.054
It had, because it couldn't be, what, maybe a couple hundred kids?

00:26:51.253 --> 00:26:51.804
Yeah, I think.

00:26:51.805 --> 00:26:53.693
At least three, four hundred kids in the whole high school?

00:26:53.733 --> 00:26:56.653
Yeah, I think my graduating class was, was fifty kids.

00:26:56.743 --> 00:26:57.094
Okay, yeah.

00:26:57.104 --> 00:26:59.574
Um, you know, we, we lived in the country.

00:26:59.574 --> 00:27:00.933
We had horses and cattle.

00:27:01.023 --> 00:27:01.374
Okay.

00:27:01.503 --> 00:27:02.223
And, um.

00:27:02.334 --> 00:27:04.469
And your dad was like Engineer or something like that?

00:27:04.999 --> 00:27:07.449
He was, but he quit that early.

00:27:07.798 --> 00:27:11.648
He quit the corporate stuff early and he moved back to Leadville and became a silver miner.

00:27:11.699 --> 00:27:12.548
Oh, interesting.

00:27:13.358 --> 00:27:14.138
For his vocation.

00:27:14.419 --> 00:27:14.838
Yeah.

00:27:14.939 --> 00:27:17.159
On his own or working for a silver mine?

00:27:17.179 --> 00:27:18.028
For a silver mine.

00:27:18.038 --> 00:27:18.338
Okay.

00:27:18.578 --> 00:27:20.229
But we ran horses and cattle.

00:27:20.269 --> 00:27:20.699
Yeah, yeah.

00:27:20.749 --> 00:27:22.489
And we had hay and stuff like that.

00:27:22.489 --> 00:27:27.439
And then, um, you know, those mines shut down in the early 80s.

00:27:27.558 --> 00:27:27.929
Okay.

00:27:28.489 --> 00:27:32.558
So we found ourselves trying to scratch out a living up there by any means.

00:27:32.558 --> 00:27:35.368
With horses and cows and whatever else.

00:27:35.429 --> 00:27:35.778
Yeah.

00:27:35.848 --> 00:27:36.868
Harvesting logs.

00:27:37.348 --> 00:27:37.798
Yeah.

00:27:37.868 --> 00:27:38.219
Yeah.

00:27:38.229 --> 00:27:42.308
We had a, we had a business where we would clear cut National Forest.

00:27:42.338 --> 00:27:53.844
We'd get a contract to clear cut National Forest and then we would, you know, uh, firewood to the ski resorts up there and had a snow plowing business and, um, all kinds of different stuff.

00:27:53.923 --> 00:27:54.253
Yeah.

00:27:54.294 --> 00:28:04.183
Was your dad ever, or was your mom, if you reflected on that, like, were they happy to not have taken the Lockheed Martin path or the Jersey path or whatever?

00:28:04.213 --> 00:28:04.564
Yeah.

00:28:04.614 --> 00:28:04.804
I think so.

00:28:04.804 --> 00:28:05.763
They were there because they wanted to be.

00:28:05.814 --> 00:28:06.773
Yeah, I think so.

00:28:06.773 --> 00:28:09.124
I think, um, you know, especially my dad.

00:28:09.134 --> 00:28:12.659
He, He was happier, um, doing that kind of thing.

00:28:12.659 --> 00:28:16.439
He just never fit into that corporate, yeah, that corporate environment.

00:28:16.568 --> 00:28:16.999
Yeah.

00:28:17.608 --> 00:28:20.429
Um, so let's take you to the end of high school here.

00:28:20.429 --> 00:28:22.838
You're trying to decide where to go to college and stuff.

00:28:22.838 --> 00:28:23.608
What does that look like for you?

00:28:23.618 --> 00:28:25.594
Oh, that was not Never thought.

00:28:25.594 --> 00:28:26.384
Not even on the radar?

00:28:26.413 --> 00:28:26.804
No.

00:28:26.864 --> 00:28:27.213
Really?

00:28:27.233 --> 00:28:27.263
Okay.

00:28:27.294 --> 00:28:30.453
So I, I, I rodeoed all through school.

00:28:30.473 --> 00:28:30.903
Okay.

00:28:30.953 --> 00:28:33.594
I did six events all the way up through high school.

00:28:33.763 --> 00:28:36.983
Like starting as like a 11 year old or 12 year old or something?

00:28:36.993 --> 00:28:39.923
Actually, I started riding steers and stuff when I was five years old.

00:28:39.923 --> 00:28:40.844
Yeah, interesting.

00:28:40.854 --> 00:28:42.074
Um, and then.

00:28:43.064 --> 00:28:43.483
Okay.

00:28:43.574 --> 00:28:49.179
Rodeoed And was, was that what your dad was raising like bucking bulls and stuff like that too or?

00:28:49.199 --> 00:28:52.949
Um, we had, we had rope and cattle and rope and horses and stuff like that.

00:28:52.969 --> 00:28:53.269
Gotcha.

00:28:53.298 --> 00:28:56.878
But, um, and so I did six events through high school.

00:28:56.959 --> 00:29:02.628
Um, when I graduated from high school, my, my best event had clearly shown itself to be bull riding.

00:29:02.769 --> 00:29:03.118
Okay.

00:29:03.318 --> 00:29:07.709
And so I, as soon as I graduated from high school, I turned pro.

00:29:07.919 --> 00:29:08.308
Wow.

00:29:08.318 --> 00:29:08.628
Yeah.

00:29:09.308 --> 00:29:11.439
And rodeoed, and I had no plan B.

00:29:11.440 --> 00:29:21.729
Um, but, but the only thing I did have going for myself is I took auto shop and welding in high school, so I could work on cars and I could, and I could weld if I needed a job.

00:29:21.739 --> 00:29:24.019
Well, imagine rodeo is at least very seasonal, right?

00:29:24.028 --> 00:29:25.009
No, it's year round.

00:29:25.048 --> 00:29:25.568
Is it really?

00:29:25.568 --> 00:29:25.878
Okay.

00:29:25.929 --> 00:29:28.999
I would have said, I guess you just do indoor arenas in the wintertime.

00:29:29.068 --> 00:29:29.469
No.

00:29:29.969 --> 00:29:30.608
Not always.

00:29:30.939 --> 00:29:31.209
No, not always.

00:29:32.269 --> 00:29:32.638
Gotcha.

00:29:32.669 --> 00:29:33.028
Yeah.

00:29:33.199 --> 00:29:34.959
A lot of rodeos down south in the wintertime.

00:29:34.969 --> 00:29:35.429
Oh, sure.

00:29:35.429 --> 00:29:35.888
Yeah.

00:29:35.890 --> 00:29:36.509
Yeah.

00:29:36.509 --> 00:29:39.689
Can we, like, how long did you do rodeoing?

00:29:40.288 --> 00:29:40.739
Let's see.

00:29:40.739 --> 00:29:41.318
As a pro.

00:29:41.469 --> 00:29:45.528
Um, two, a little over two years, and then I had a career ending injury.

00:30:28.904 --> 00:30:30.755
Tell me about the lifestyle.

00:30:31.454 --> 00:30:32.045
Um.

00:30:32.065 --> 00:30:33.144
Like, what's that look like, really?

00:30:33.315 --> 00:30:34.974
Is Chris LeDoux telling us true?

00:30:35.065 --> 00:30:35.384
No.

00:30:35.394 --> 00:30:38.075
Chris LeDoux, he pretty much hits it on the head.

00:30:38.075 --> 00:30:38.365
Yeah.

00:30:38.654 --> 00:30:42.525
Um, back in those days, it was a hundred and some rodeos a year.

00:30:42.724 --> 00:30:43.005
Okay.

00:30:43.045 --> 00:30:44.515
You were on the road all the time.

00:30:44.555 --> 00:30:44.944
Wow.

00:30:44.954 --> 00:30:44.974
Yeah.

00:30:45.174 --> 00:30:45.684
You were.

00:30:45.984 --> 00:30:48.845
You were scratching, scratching to make a living.

00:30:48.904 --> 00:30:53.404
If you were making enough money to stay on the road, you were doing really well.

00:30:53.674 --> 00:30:54.765
And when is this?

00:30:54.765 --> 00:30:57.045
This is like in the mid nineties or something like that?

00:30:57.055 --> 00:30:57.615
Mid eighties.

00:30:57.634 --> 00:30:58.154
Mid eighties.

00:30:58.154 --> 00:30:58.375
Okay.

00:30:58.859 --> 00:31:09.059
Yeah, you must be a lot older than I think But yeah, and so, you know, it was you know, it was great You know, I was living the dream.

00:31:09.220 --> 00:31:09.430
Yeah.

00:31:09.430 --> 00:31:10.910
Yeah, that's what I always wanted to do.

00:31:10.910 --> 00:31:17.980
You were staying on the road Yeah, we were putting much in their savings account, but right right to pick up truck that didn't need new tires yet Yeah, that's right.

00:31:18.359 --> 00:31:21.119
Yeah, and so and you're a single guy, I guess.

00:31:21.119 --> 00:31:23.670
Yeah, I was single Yeah, it was great.

00:31:23.779 --> 00:31:28.579
The um Did you have, like, buddies that you toured around with and stuff, or whatever?

00:31:28.599 --> 00:31:30.890
Like, rent an apartment for a while or anything like that?

00:31:30.890 --> 00:31:32.819
Or were you just pretty much staying in hotels?

00:31:32.890 --> 00:31:34.849
Yeah, we were on the road all the time.

00:31:35.599 --> 00:31:38.210
How do you get your mail and bills and stuff like that?

00:31:38.500 --> 00:31:41.500
Well, we'd have a, you know, an apartment back home that we all shared.

00:31:41.509 --> 00:31:42.000
Gotcha.

00:31:42.079 --> 00:31:44.569
You know, but That you were there for like Right.

00:31:44.630 --> 00:31:45.500
27 days a year.

00:31:45.519 --> 00:31:48.180
Yeah, yeah, yep, yep, yep.

00:31:48.599 --> 00:31:48.869
Hmm.

00:31:50.069 --> 00:31:53.224
So The injury.

00:31:53.565 --> 00:31:53.904
Yeah.

00:31:54.174 --> 00:31:54.424
that?

00:31:54.515 --> 00:31:54.845
Yeah.

00:31:54.845 --> 00:32:00.865
So, um, I tore the ulna from my wrist on my riding hand.

00:32:00.875 --> 00:32:01.355
From it?

00:32:01.515 --> 00:32:01.904
Yeah.

00:32:01.974 --> 00:32:03.964
The ulna disconnected from my wrist.

00:32:03.964 --> 00:32:07.555
So the radius and the ulna are these two, the big one's the ulna?

00:32:08.224 --> 00:32:09.295
The little one is the ulna.

00:32:09.305 --> 00:32:10.305
The little one is the ulna.

00:32:10.454 --> 00:32:12.765
And that popped up and disconnected from my wrist.

00:32:13.654 --> 00:32:15.444
And I had to have reconstructive surgery.

00:32:15.454 --> 00:32:16.734
Like a pond head in the ground?

00:32:16.744 --> 00:32:18.944
No, it was You were holding on too tight.

00:32:18.984 --> 00:32:20.144
I was holding on too tight.

00:32:20.144 --> 00:32:20.881
Oh, damn.

00:32:20.881 --> 00:32:23.505
My I had a big strong bull.

00:32:23.535 --> 00:32:27.355
My elbow didn't give, and my ulna popped up.

00:32:27.894 --> 00:32:29.654
And so that was the end.

00:32:29.924 --> 00:32:30.224
Really?

00:32:30.224 --> 00:32:30.974
Just like that?

00:32:31.065 --> 00:32:31.365
Yeah.

00:32:31.365 --> 00:32:35.295
There was no surgery rehab for a year or anything like that?

00:32:35.345 --> 00:32:35.664
No.

00:32:35.684 --> 00:32:41.244
The When I finally got the surgery, the doctor was like, You You can't do this anymore.

00:32:41.244 --> 00:32:41.474
Yeah.

00:32:41.944 --> 00:32:46.654
You know, did you have ideas to maybe I could do team roping or some other thing?

00:32:46.664 --> 00:33:08.444
No, you focused all your effort into yeah bulls and you know when that was gonna do it when that got taken away from me I was like, you know, I was one of those people who I couldn't have anything to do with it anymore Yeah, because I missed it so much I had to kind of put that in a box put it aside and try to move on because I missed it So much were you like depressed?

00:33:08.454 --> 00:33:08.865
Yeah.

00:33:09.035 --> 00:33:09.325
Yeah.

00:33:09.664 --> 00:33:11.394
Had you in those?

00:33:11.394 --> 00:33:12.890
You Months on the road and stuff.

00:33:12.890 --> 00:33:14.779
Were you like partying and stuff like that?

00:33:14.779 --> 00:33:15.829
Did that get worse?

00:33:16.150 --> 00:33:19.410
No, I mean, he didn't turn to alcohol as a soothe.

00:33:19.710 --> 00:33:22.009
No, I mean, you know, we did party.

00:33:22.009 --> 00:33:25.630
I don't want to, I don't want to say we didn't, but we were professional too.

00:33:25.660 --> 00:33:26.450
We were professional.

00:33:26.500 --> 00:33:26.740
Right.

00:33:26.740 --> 00:33:27.049
Right.

00:33:27.059 --> 00:33:27.329
Fair.

00:33:27.329 --> 00:33:27.559
Right.

00:33:27.609 --> 00:33:27.900
All right.

00:33:27.930 --> 00:33:34.329
You know, so for me, yeah, for me, the hardest thing about staying on the road was staying in shape, you know?

00:33:34.329 --> 00:33:36.579
And so that was always something we were trying to do.

00:33:36.880 --> 00:33:39.599
Um, but for me, it was my identity.

00:33:39.599 --> 00:33:39.615
Yeah.

00:33:39.924 --> 00:33:44.734
Yeah, and so when I got taken away, it was like what well, what is my you're like 20 years old?

00:33:44.744 --> 00:33:46.295
Yeah, or something like that, right?

00:33:47.065 --> 00:33:59.595
And you go through a process to figure that out or yeah, you know I had to go home and get a job right away And so, you know, I went to work for a farmer out in Eastern, Colorado Okay, then I got a job building elevator legs as a welder.

00:33:59.904 --> 00:34:03.184
Okay, I'm doing some stuff in the oil fields as a welder.

00:34:03.184 --> 00:34:14.364
I Decided you know, maybe I should go to college You And, um, so I moved to Greeley because there was a junior college in Greeley.

00:34:14.855 --> 00:34:19.605
And I got a job at the meatpacking house in Greeley, Momford.

00:34:19.605 --> 00:34:22.644
And they asked me what shift I wanted to work.

00:34:22.644 --> 00:34:24.125
And I said, straight graveyards.

00:34:24.864 --> 00:34:25.695
And they were like, really?

00:34:25.695 --> 00:34:25.905
Who?

00:34:26.315 --> 00:34:27.875
Nobody ever chooses that.

00:34:28.219 --> 00:34:28.519
Right.

00:34:28.570 --> 00:34:31.320
You just wanted to have your rest of your day open for school.

00:34:31.320 --> 00:34:31.699
Yeah.

00:34:32.019 --> 00:34:32.309
Yeah.

00:34:32.769 --> 00:34:34.835
So I got a job at Monfort.

00:34:34.835 --> 00:34:35.750
Dang.

00:34:35.750 --> 00:34:36.969
Probably paid better too, I reckon.

00:34:37.320 --> 00:34:38.059
It paid pretty good.

00:34:38.059 --> 00:34:39.039
It had full benefits.

00:34:39.050 --> 00:34:39.329
Yeah.

00:34:39.690 --> 00:34:45.989
And Turns out I couldn't have reconstructive surgery until I got a job with benefits.

00:34:46.059 --> 00:34:47.570
Oh, gotcha.

00:34:48.050 --> 00:34:57.570
So Dang, so you were, you were, you were Building grain bins and doing these different things with kind of a little bit jacked up, uh, Yeah, wrist there.

00:34:57.579 --> 00:34:59.280
Yeah, it was it was pretty bad.

00:34:59.360 --> 00:35:21.289
Mm hmm but so I went to the community college in Greeley and You know, they said the first thing to do is take a pre assessment test to see where you are Okay, and so I took a pre assessment test and they Got the results back and they called me in and they said, well, you're at a ninth grade math level on the ninth grade reading level.

00:35:21.289 --> 00:35:23.090
What is it you think you want to study?

00:35:23.210 --> 00:35:24.559
And I said, I want to be an engineer.

00:35:24.559 --> 00:35:28.969
And they actually laughed, they were like, I think you should be a little bit more realistic.

00:35:30.010 --> 00:35:30.789
Maybe a welder.

00:35:31.250 --> 00:35:31.619
Right.

00:35:31.860 --> 00:35:32.230
Right.

00:35:32.909 --> 00:35:35.630
And so, um, and so.

00:35:36.230 --> 00:35:44.300
Um, I was taking classes part time working in the meatpacking house and then, um, I started a roofing business, left the meatpacking plant.

00:35:44.849 --> 00:35:45.409
And.

00:35:45.909 --> 00:35:50.869
And so you, like, you really just didn't pay much attention to school at all, like during your high school years too.

00:35:50.949 --> 00:35:51.309
No.

00:35:51.699 --> 00:35:58.519
Cause it's obvious to me and I've, this was obvious to your parents and your teachers that you were smart, intelligent enough to get it.

00:35:59.159 --> 00:35:59.909
I think so.

00:35:59.920 --> 00:36:01.539
No, but I think, um.

00:36:03.219 --> 00:36:04.519
Maybe they knew, but I didn't.

00:36:04.599 --> 00:36:05.090
Right.

00:36:05.280 --> 00:36:11.480
Well, it's also easy for you to be annoying enough by your disinterest that they don't care whether you're smart or not.

00:36:11.510 --> 00:36:12.039
It could be.

00:36:12.349 --> 00:36:13.320
You know, like, whatever.

00:36:13.329 --> 00:36:15.679
If you don't want to learn nothing here, then we'll check you later.

00:36:15.739 --> 00:36:16.050
Right.

00:36:16.079 --> 00:36:16.849
That's really interesting.

00:36:16.869 --> 00:36:17.280
Right.

00:36:17.449 --> 00:36:21.989
Okay, so, so you start dabbling, getting some classes under your belt?

00:36:22.000 --> 00:36:22.349
Yep.

00:36:22.489 --> 00:36:25.369
Started my roofing business, kept taking classes.

00:36:25.769 --> 00:36:35.474
Um, In roofing businesses, like you and a couple of contract laborers here and there kind of thing, just doing residential roofs when, especially when there's hailstorms.

00:36:35.485 --> 00:36:38.304
When there's hailstorms, you're, you're making money hand over fist.

00:36:38.304 --> 00:36:38.514
Right.

00:36:38.525 --> 00:36:48.394
And, um, and so I, I was taking enough prerequisite classes at Ames that I was ready to start an engineering program.

00:36:48.394 --> 00:37:01.369
And then I got accepted into CSU engineering program on a, On a probationary basis, because, you know, if, if you don't have the ACT or SAT scores and you're not right out of high school, they don't know what to do with you.

00:37:01.739 --> 00:37:02.559
So they accepted me.

00:37:03.315 --> 00:37:14.135
Um, on a one year probation and so I had to take all the, all the math and science and engineering classes my freshman year and get a B or better in all of them and then they would accept me.

00:37:14.135 --> 00:37:14.465
Okay.

00:37:14.545 --> 00:37:15.014
Interesting.

00:37:15.014 --> 00:37:15.264
Yeah.

00:37:15.264 --> 00:37:18.235
And so, you showed them?

00:37:18.385 --> 00:37:20.025
You got B's and above on everything?

00:37:20.034 --> 00:37:20.364
Yeah.

00:37:20.364 --> 00:37:21.585
And you were allowed to stay at CSU?

00:37:21.625 --> 00:37:25.000
But it was, it was, um It was out of pure fear.

00:37:25.980 --> 00:37:28.260
I mean, I had a family that was depending on me.

00:37:28.710 --> 00:37:32.460
And, um You're talking about your parents and stuff?

00:37:32.460 --> 00:37:34.579
Or did you find a gal on this journey?

00:37:34.579 --> 00:37:34.849
Yeah.

00:37:34.849 --> 00:37:36.110
When you were bull riding?

00:37:36.110 --> 00:37:36.449
Yeah.

00:37:36.510 --> 00:37:39.489
No, after bull riding, before college, I got married.

00:37:39.650 --> 00:37:40.110
Okay.

00:37:40.170 --> 00:37:50.190
And, um, and so, you know, that self induced poverty of Well, and married and had a child too, otherwise she'd been making a little scratch for you and you could have coasted.

00:37:50.369 --> 00:37:50.739
Yeah.

00:37:50.969 --> 00:37:51.309
Okay.

00:37:51.320 --> 00:37:56.170
And so, um, you know, there was a lot of fear that I wasn't, I wasn't smart enough.

00:37:56.210 --> 00:37:56.730
Yeah.

00:37:56.769 --> 00:38:01.340
You know, I'm looking around in these freshman classes and everybody was the valedictorian from their high school.

00:38:01.349 --> 00:38:01.670
Hmm.

00:38:02.039 --> 00:38:02.389
Right.

00:38:02.460 --> 00:38:07.019
And, um, you know, it, it took me a little while to figure it out.

00:38:07.019 --> 00:38:09.269
Yeah, and they just laughed at you when you said, I want to be an engineer.

00:38:09.300 --> 00:38:10.059
Yeah, right.

00:38:10.219 --> 00:38:10.590
Yeah.

00:38:10.599 --> 00:38:10.869
Right.

00:38:10.900 --> 00:38:13.079
I'm just this, this kid out of nowhere.

00:38:13.119 --> 00:38:13.340
Huh.

00:38:13.820 --> 00:38:15.760
Who didn't even take math in high school.

00:38:15.769 --> 00:38:16.159
Right.

00:38:16.190 --> 00:38:23.809
Well, and you were probably humble, confident, at least as far as it went to bull riding, and some of the other rodeo arts are different things, but hadn't really developed that yet.

00:38:23.869 --> 00:38:24.199
Right.

00:38:24.239 --> 00:38:25.980
In your intellectual capacity.

00:38:26.050 --> 00:38:26.320
Right.

00:38:26.349 --> 00:38:29.099
And, you know, the one thing I learned from my dad is to work hard.

00:38:29.289 --> 00:38:29.710
Yeah.

00:38:29.929 --> 00:38:36.030
And, you know, I didn't realize it at the time, but, um, everybody there was smart.

00:38:36.619 --> 00:38:36.960
Right.

00:38:37.010 --> 00:38:38.869
What separates people is hard work.

00:38:39.514 --> 00:38:48.744
And so, you know, on my freshman, my freshman, uh, first freshman class, they said, look to your left, look to your right, those two people won't be here on graduation day.

00:38:48.744 --> 00:38:52.875
They take pride in flunking out 50 or 60 percent of the engineering students.

00:38:53.375 --> 00:38:54.434
That scared me to death.

00:38:54.445 --> 00:38:54.835
Right.

00:38:55.655 --> 00:39:03.184
And, you know, I didn't realize, um, I didn't know that first year that I was going to be okay.

00:39:03.184 --> 00:39:05.235
I just, I was scared to death that I wasn't going to make it.

00:39:05.730 --> 00:39:09.550
And that fear never left me until I got to my senior year.

00:39:09.550 --> 00:39:10.309
I realized I got a 4.

00:39:10.309 --> 00:39:11.139
0.

00:39:11.289 --> 00:39:12.960
I've never even had a B yet.

00:39:13.079 --> 00:39:14.730
You're probably going to be okay.

00:39:14.730 --> 00:39:18.050
You never hardly had an A in your life before that.

00:39:18.059 --> 00:39:19.869
No, no, no.

00:39:20.099 --> 00:39:20.449
Yeah.

00:39:20.840 --> 00:39:27.940
And also I had to get done in four years, which, you know, most, I think the average engineering degree takes five or six years to get.

00:39:28.079 --> 00:39:28.750
I would say so.

00:39:28.789 --> 00:39:29.170
Yeah.

00:39:29.219 --> 00:39:33.829
I, I went to school for engineering, uh, and took five and a half years to come out with an economics degree.

00:39:33.880 --> 00:39:34.190
Yeah.

00:39:34.440 --> 00:39:34.630
Yeah.

00:39:35.019 --> 00:39:35.449
So.

00:39:35.809 --> 00:39:36.179
Yeah.

00:39:36.179 --> 00:39:40.809
So it was, you know, it was just, it was, like I said, it was all fear, fear of failure.

00:39:40.809 --> 00:39:40.869
Yeah.

00:39:40.869 --> 00:39:41.050
Yeah.

00:39:41.050 --> 00:39:41.494
You know.

00:39:41.494 --> 00:39:43.545
And then what?

00:39:44.324 --> 00:39:46.375
Like, um, were the jobs what was it?

00:39:46.425 --> 00:39:49.375
This is like what early 90s by this time?

00:39:49.425 --> 00:39:52.324
Yeah, by this time I graduated in 94.

00:39:52.425 --> 00:39:52.815
Okay.

00:39:52.905 --> 00:39:54.255
Okay, so mid 90s.

00:39:54.344 --> 00:40:05.614
Yeah, and you know I had you know, I had an opportunity to to work at the engines lab at CSU.

00:40:05.675 --> 00:40:06.074
Oh, really?

00:40:06.094 --> 00:40:06.574
With Dr.

00:40:06.574 --> 00:40:07.025
Wilson.

00:40:07.094 --> 00:40:07.525
Okay.

00:40:07.755 --> 00:40:09.844
And, you know, Dr.

00:40:09.844 --> 00:40:14.945
Wilson and I and a couple other students kind of opened up that, that building where the engines lab was.

00:40:14.945 --> 00:40:15.554
Oh, is that right?

00:40:15.625 --> 00:40:18.864
And I got to do a bunch of really cool stuff as an engineering student.

00:40:18.954 --> 00:40:19.195
Oh, wow.

00:40:19.204 --> 00:40:27.949
And, um, my junior year, um, I started realizing that the economy was looking a little worse than I had hoped.

00:40:28.579 --> 00:40:34.550
And so to kind of mitigate the risk that I couldn't get a job, I had put together some funding for a graduate program.

00:40:35.019 --> 00:40:36.230
In case I couldn't get a job.

00:40:37.039 --> 00:40:40.519
Fortunately, my senior year, I got an offer from Lockheed Martin.

00:40:41.349 --> 00:40:43.599
And they made me an offer before graduation.

00:40:43.800 --> 00:40:47.199
And so Were you an intern for them or something like that?

00:40:47.199 --> 00:40:48.250
Or how did they get to know you?

00:40:48.250 --> 00:40:51.360
Uh, just like a professor's vouch for you somehow?

00:40:51.369 --> 00:40:52.699
No, they did recruiting.

00:40:53.070 --> 00:40:53.320
Okay.

00:40:53.409 --> 00:40:54.219
On campus.

00:40:54.260 --> 00:40:54.610
Okay.

00:40:54.920 --> 00:41:10.800
And, um, they were hiring for something called the Leadership Development Program where they hired 10 new college grads nationwide with this idea that they were going to be, um, you know, set up for leadership in Lockheed Martin.

00:41:10.860 --> 00:41:22.389
I mean, my, I, I got started in a credit and management training program, you know, teaching the near future lenders and distant future bank presidents, uh, how to be in our, in Thing, you know?

00:41:22.389 --> 00:41:22.539
Right.

00:41:22.539 --> 00:41:24.280
That was my beginning of my career was the same kind of thing.

00:41:24.340 --> 00:41:24.699
Yeah.

00:41:25.059 --> 00:41:33.994
And you know, I think looking back on it, I was, um, I was probably a little more seasoned than most new college grads because I was, you know, I was damn near four years older.

00:41:34.394 --> 00:41:35.949
I was damn near 36 years older.

00:41:35.949 --> 00:41:38.590
You know, I was damn near 30 by the time I graduated from college.

00:41:38.590 --> 00:41:38.590
Yep.

00:41:38.614 --> 00:41:38.835
Yep.

00:41:39.409 --> 00:41:41.809
Um, you know, that, that was probably a benefit.

00:41:41.869 --> 00:41:43.159
And was that a good program to you?

00:41:43.159 --> 00:41:49.730
Like beneficial outside of just the being a part of Lockheed or was the program less important than the people around you?

00:41:49.809 --> 00:41:53.599
Well, what ended up happening is it was an ill conceived program.

00:41:54.820 --> 00:42:07.425
So the idea was you'd get a new job every six months for four years, and then you'd be a well trained, well rounded leader, but you show up at each manager's, um, office and say, I'm leaving in six months.

00:42:07.655 --> 00:42:07.905
Right.

00:42:07.934 --> 00:42:09.244
They're like, you're a pain in my ass.

00:42:09.585 --> 00:42:11.534
I don't even want to give you any time or resources.

00:42:11.605 --> 00:42:15.695
And so I pulled out of the program and went into the engines propulsion lab.

00:42:15.844 --> 00:42:16.175
Okay.

00:42:16.215 --> 00:42:18.164
And that's where I kind of found my home.

00:42:18.184 --> 00:42:18.454
Yeah.

00:42:18.454 --> 00:42:21.284
And found that first, uh, residence challenge and whatnot.

00:42:21.744 --> 00:42:22.175
I'll saw.

00:42:22.184 --> 00:42:22.204
Yeah.

00:42:22.215 --> 00:42:22.485
Yeah.

00:42:23.445 --> 00:42:33.585
And, you know, after a few years, I realized that, um, although it's fun work, um, becoming labeled as an aerospace engineer can be suicide.

00:42:33.974 --> 00:42:34.255
Hmm.

00:42:34.960 --> 00:42:45.320
And so, because there's such a few number of companies that you can work for or it's, you know, you can kind of be pigeonholed if you've been an aerospace engineer for 20 years, Hewlett Packard is not going to hire you.

00:42:45.349 --> 00:42:45.730
Right.

00:42:45.800 --> 00:42:46.099
Right.

00:42:46.139 --> 00:42:51.869
And so I left when I was still a young engineer with good experience, but I wasn't pigeonholed yet.

00:42:51.900 --> 00:42:53.139
And so I went to Hewlett Packard.

00:42:53.190 --> 00:42:53.579
Okay.

00:42:53.710 --> 00:42:53.969
Yep.

00:42:54.579 --> 00:42:56.449
Which was very much in its infancy.

00:42:57.170 --> 00:42:59.650
strong part of life at that point in time.

00:42:59.650 --> 00:42:59.840
Yeah.

00:42:59.840 --> 00:43:01.880
I mean, everybody wanted to work at HP.

00:43:01.920 --> 00:43:02.349
Totally.

00:43:02.449 --> 00:43:02.610
Yeah.

00:43:02.610 --> 00:43:02.980
Yeah.

00:43:03.059 --> 00:43:03.929
It was the best place.

00:43:03.949 --> 00:43:04.639
Best and brightest.

00:43:04.639 --> 00:43:04.909
Yeah.

00:43:04.909 --> 00:43:05.230
Yeah.

00:43:05.260 --> 00:43:05.579
Yeah.

00:43:06.170 --> 00:43:11.059
So, and right back into product stuff or is this when you transitioned into managing people more?

00:43:11.070 --> 00:43:15.630
I went right into, right into product development and it was just great.

00:43:15.760 --> 00:43:21.480
It was great because you know, we had in the division I was in, we had everything in one place.

00:43:21.489 --> 00:43:22.889
So we had marketing.

00:43:23.394 --> 00:43:27.625
engineering, manufacturing, sales, everything was in, in one place.

00:43:28.025 --> 00:43:30.164
And so it really was a cool.

00:43:30.204 --> 00:43:37.954
So you got to kind of what Lockheed was trying to show you by having these different jobs, you got to just meet people that are doing these different functions.

00:43:37.965 --> 00:43:38.394
Right.

00:43:38.494 --> 00:43:38.735
Right.

00:43:38.764 --> 00:43:39.184
Interesting.

00:43:39.184 --> 00:43:39.505
Yeah.

00:43:39.864 --> 00:43:48.795
And so that's when I started realizing that, um, you know, the, the biggest failure in product development happens long before the product is developed.

00:43:49.835 --> 00:43:57.704
And that's really understand what the market needs are, making sure that you have a compelling product for those market needs.

00:43:57.855 --> 00:44:00.164
You don't over design it or under design it.

00:44:00.764 --> 00:44:06.635
And you have clarity about what the value proposition is and what people are willing to pay for that value.

00:44:06.704 --> 00:44:07.335
Yeah, yeah.

00:44:07.335 --> 00:44:15.590
And so Well, that was really, we'll get to there, but that was really the The linchpin of your accelerator, uh, investment hub.

00:44:15.760 --> 00:44:16.639
Right, exactly.

00:44:16.940 --> 00:44:29.474
And it turns out it doesn't matter whether you're a startup or a fortune 500 company, um, If you don't develop the right product for the market, in a Fortune 500 company, you just have a small decrease in revenue, right?

00:44:29.485 --> 00:44:35.525
I remember when CNN came out with their, what was it, CNN Online or something like that?

00:44:35.954 --> 00:44:44.460
And it's like, to fix the problem of nobody wanting to watch online, Our news network, we're going to create a huge online community where people pay to watch it online, right.

00:44:44.510 --> 00:44:46.139
To not watch it online or something.

00:44:46.159 --> 00:44:46.440
Right.

00:44:46.449 --> 00:44:50.090
I think they lost 300 million in like six months and then pulled the plug.

00:44:50.190 --> 00:44:50.519
Right.

00:44:50.690 --> 00:44:51.050
Yeah.

00:44:51.579 --> 00:44:54.389
And you know, more product market fit analysis first.

00:44:54.420 --> 00:44:54.900
Yeah.

00:44:55.000 --> 00:44:56.150
And talk to 10 people.

00:44:56.900 --> 00:44:57.309
Right.

00:44:57.639 --> 00:45:05.480
And you know, the, but what ends up happening is especially in, with entrepreneurs.

00:45:06.179 --> 00:45:33.699
Um, we see the solution to something and we pursue that solution, you know, with, with just reckless abandonment, a solution, it's a solution and also, and I'll get to my, I'll wrap this point up, but also, especially as an engineer, if you're an innovator and an inventor, you're all about, you're taught for four years, how to solve problems.

00:45:33.710 --> 00:45:33.855
Thank you very much.

00:45:34.664 --> 00:45:38.905
You're never really taught the importance of clearly defining the problem.

00:45:38.985 --> 00:45:39.434
Mm hmm.

00:45:39.864 --> 00:45:41.704
And whether or not it's worth solving.

00:45:41.824 --> 00:45:42.114
Yeah.

00:45:42.880 --> 00:45:45.349
And so we're trained to do solutions.

00:45:45.349 --> 00:45:49.119
We're not trained to think long and hard about the problem.

00:45:49.119 --> 00:45:49.730
Yeah, yeah.

00:45:49.949 --> 00:45:54.320
And so, um, that's, that's what ends up happening even in Fortune 500 companies.

00:45:54.320 --> 00:45:55.260
For sure, for sure.

00:45:55.840 --> 00:46:02.679
And in economics training, uh, you know, that notion of unintended consequences is kind of right there from the beginning.

00:46:02.690 --> 00:46:03.030
Right.

00:46:03.070 --> 00:46:05.500
Much more so than, than on an engineering basis.

00:46:05.519 --> 00:46:09.599
Cause it's like, Um, and it's kind of like, there's the problem, make it go away.

00:46:09.659 --> 00:46:09.960
Right.

00:46:10.190 --> 00:46:17.550
You know, and yeah, sometimes you'll cause other problems from that, but it's not in the same way that the complex systems are exposing.

00:46:17.550 --> 00:46:25.690
That's the difference between, I guess, engineering is generally dealing with, um, one, I don't know what the complicated system, right.

00:46:25.690 --> 00:46:27.440
But it's all kind of within that thing.

00:46:27.449 --> 00:46:31.210
You know, if you get that harmonic vibration out of that rocket engine, it doesn't blow up anymore.

00:46:31.219 --> 00:46:31.860
Right, right.

00:46:31.869 --> 00:46:33.920
But it's a complicated or a complex system.

00:46:34.414 --> 00:46:40.054
You know, all these people making all these different buying decisions based on competing products and brand awareness.

00:46:40.054 --> 00:47:00.295
And, and, you know, the thing that I, that I really started to put a lot of thought into is, um, and I've kind of segmented it, you have problem space and you have solution space, the longer you can stay in problem space without thinking about a solution.

00:47:01.005 --> 00:47:03.905
the better you are at clearly defining the problem.

00:47:04.434 --> 00:47:11.744
Once you start entering solution space, your ability to detect that you missed the root cause of the problem goes away.

00:47:12.574 --> 00:47:16.644
You get enamored with your solution and you'll never revisit the problem again.

00:47:17.635 --> 00:47:19.875
Have we talked about Locos process?

00:47:19.925 --> 00:47:20.275
I'm sure.

00:47:20.295 --> 00:47:21.954
Well, you're familiar probably with Vistage at least.

00:47:21.954 --> 00:47:22.175
Yeah.

00:47:22.175 --> 00:47:22.394
Yeah.

00:47:22.394 --> 00:47:23.125
The Vistage meeting.

00:47:23.485 --> 00:47:28.094
It's kind of the same, but you know, it's clarifying questions before suggestions.

00:47:28.784 --> 00:47:38.875
Right, you define the problem, ask the question, and then your fellow 10, 12 members can only ask clarifying questions for 15, maybe even 20 minutes out of a 30 minute session.

00:47:39.565 --> 00:47:41.704
And then you get five minutes for suggestions.

00:47:41.905 --> 00:47:42.295
Okay.

00:47:42.425 --> 00:47:45.175
And the same kind of thing, the longer you can stay on the problem.

00:47:45.565 --> 00:47:53.534
And so when, when I'm facilitating free think sessions and stuff, when there's newbies there, like always, I have to be like, now, is that a suggestion?

00:47:53.534 --> 00:47:55.175
Is that a, is that a question?

00:47:55.690 --> 00:47:58.349
Made, or suggested, it made it sound like a question.

00:47:58.730 --> 00:48:01.199
And it's for that same reason of staying on the problem.

00:48:01.280 --> 00:48:02.070
Right, right.

00:48:02.070 --> 00:48:02.659
Long enough.

00:48:02.949 --> 00:48:07.250
And staying on it long enough to, to really distill it down to its essence.

00:48:07.300 --> 00:48:07.769
Yeah, yeah.

00:48:07.909 --> 00:48:08.269
Right.

00:48:08.880 --> 00:48:14.230
And so, um, so anyway, that's, that's where the problem usually starts in product development.

00:48:15.594 --> 00:48:22.215
So, you have a little time in HP and there, and then that's when you kind of started being in the people business, is that right?

00:48:22.224 --> 00:48:22.244
Yeah.

00:48:22.255 --> 00:48:23.704
That mentor that shared that with you?

00:48:23.775 --> 00:48:26.425
Yeah, yeah, so I And was this in Fort Collins here?

00:48:26.454 --> 00:48:28.114
This is in Northern Colorado at HP?

00:48:28.155 --> 00:48:32.275
It was at HP in Greeley, and then I went, uh, to HP in Loveland.

00:48:32.375 --> 00:48:32.625
Okay.

00:48:32.625 --> 00:48:35.514
During the, the, uh, Agilent spinoff time frame.

00:48:35.545 --> 00:48:36.545
Yep, yep, yep, okay.

00:48:36.764 --> 00:48:38.074
And that's where I was promoted.

00:48:38.284 --> 00:48:38.914
Yep, gotcha.

00:48:39.545 --> 00:48:47.795
And then, um, Like, did you go straight from there into your first entrepreneurial venture or tell me that circumstance maybe, and maybe set the stage.

00:48:48.284 --> 00:48:51.795
You've got a wife and more than one child by now, this time in your career.

00:48:51.824 --> 00:48:52.105
Yeah.

00:48:52.204 --> 00:48:52.494
Yeah.

00:48:52.644 --> 00:48:52.905
Yeah.

00:48:52.994 --> 00:48:53.375
Okay.

00:48:53.505 --> 00:48:53.784
Yeah.

00:48:53.784 --> 00:48:58.715
And so, um, yeah, so I got to do a lot of really cool stuff at HP.

00:48:59.005 --> 00:49:05.914
I got to figure out where, you know, like I mentioned, where the, the root cause of the problems were for, for products.

00:49:05.914 --> 00:49:06.164
Yeah.

00:49:06.184 --> 00:49:11.954
And so I started moving upstream from, uh, the engineering to more of the product management.

00:49:12.349 --> 00:49:12.599
Yep.

00:49:12.730 --> 00:49:15.489
Inbound marketing, um, that kind of thing.

00:49:15.519 --> 00:49:23.960
And so, um, you know, then I was promoted at Agilent and I ran a team of people designing the system on a chip tester.

00:49:24.380 --> 00:49:24.730
Okay.

00:49:25.030 --> 00:49:32.230
And so, um, really trying to understand what the market needs were, um, you know, how we could differentiate the product, that kind of thing.

00:49:32.239 --> 00:49:32.559
Yeah.

00:49:32.610 --> 00:49:35.219
And what did Agilent do that was different than HP?

00:49:35.250 --> 00:49:36.590
Like when that spun apart?

00:49:36.989 --> 00:49:40.219
The, the only difference was they separated it by product line.

00:49:40.300 --> 00:49:40.929
So, okay.

00:49:41.610 --> 00:49:47.500
HP was originally started by, um, Bill and Dave developing engineering test equipment.

00:49:47.650 --> 00:49:47.929
Yep.

00:49:48.389 --> 00:49:51.690
Then they moved into consumer products like the printers and that kind of thing.

00:49:51.739 --> 00:49:55.900
So when they spun off Agilent, it was all the original engineering and test equipment.

00:49:56.000 --> 00:49:56.420
Okay.

00:49:56.679 --> 00:49:58.329
HP became all the consumer products.

00:49:58.369 --> 00:49:59.311
Gotcha, gotcha, okay.

00:49:59.311 --> 00:49:59.534
Yep.

00:49:59.864 --> 00:50:04.574
That was, that was my perception, but I wasn't really clear about if Agilent had other products or things like that.

00:50:04.585 --> 00:50:11.704
Well, when I made the move, I thought, you know, Agilent would probably carry on the heart and soul of HP.

00:50:11.764 --> 00:50:12.065
Yeah.

00:50:12.500 --> 00:50:17.980
You know, they had already hired a celebrity CEO for HP, and I could see things were changing.

00:50:17.980 --> 00:50:22.039
And so I went with Agilent because I wanted to be part of that, that culture.

00:50:22.059 --> 00:50:23.380
And then what happened with that?

00:50:23.420 --> 00:50:25.880
Did Agilent continue on as it continued on?

00:50:26.309 --> 00:50:27.030
Did it re emerge?

00:50:27.059 --> 00:50:28.480
I don't, I don't really know, honestly.

00:50:28.489 --> 00:50:39.280
So Agilent continued on, uh, they went through, um, a period of about 10 years where they were, um, spinning off businesses.

00:50:40.360 --> 00:50:44.449
Taking the proceeds from those spinoffs and doing stock repurchase.

00:50:44.630 --> 00:50:45.219
Oh, interesting.

00:50:45.239 --> 00:50:52.230
And they got down to where, I think, HP in Loveland, for example, went from 13, 000 people down to about 900.

00:50:52.300 --> 00:50:52.730
Yeah.

00:50:52.809 --> 00:50:53.909
In that 10 year period.

00:50:53.969 --> 00:50:54.519
Yeah, yeah.

00:50:54.809 --> 00:51:04.445
And, um, I think after I left, Agilent decided to go into just, um, biotech stuff or maybe healthcare stuff.

00:51:04.454 --> 00:51:04.514
Oh, interesting.

00:51:04.514 --> 00:51:04.885
Yeah, yeah.

00:51:05.045 --> 00:51:08.445
And then the rest of the electronics stuff was spun off into Keysight.

00:51:08.864 --> 00:51:09.324
Oh, okay.

00:51:09.574 --> 00:51:09.855
Yeah.

00:51:10.135 --> 00:51:10.425
So.

00:51:10.474 --> 00:51:10.885
Interesting.

00:51:11.025 --> 00:51:11.364
Alright.

00:51:11.695 --> 00:51:14.655
And so you leave to chase, chase what pasture from here?

00:51:15.074 --> 00:51:21.905
Um, so I left, um, I left Agilent and I went to, um, Pelco.

00:51:22.505 --> 00:51:28.304
They, Pelco designed, um, video surveillance and back end software systems.

00:51:28.355 --> 00:51:29.014
Oh, okay.

00:51:29.054 --> 00:51:33.295
So they developed the cameras and the back end software for Yeah, for banks and stuff especially.

00:51:33.664 --> 00:51:35.034
Convenience stores, whatever.

00:51:35.065 --> 00:51:35.775
Yeah, yeah.

00:51:35.804 --> 00:51:36.164
Okay.

00:51:36.585 --> 00:51:45.985
And so that was really fun because they had started a new, a new, uh, It was basically a startup within Pelco, which was in, in Fort Collins.

00:51:45.985 --> 00:51:54.635
And we were developing internet protocol technology and everything prior to that had been the old analog recording stuff on discs and right.

00:51:54.764 --> 00:51:55.074
Right.

00:51:55.144 --> 00:51:57.835
Get rid of them after a month or six months or a year.

00:51:57.835 --> 00:51:59.445
If nobody claims that he got robbed or whatever.

00:51:59.445 --> 00:51:59.914
Right.

00:51:59.914 --> 00:52:00.244
Right.

00:52:00.594 --> 00:52:00.804
Yeah.

00:52:00.905 --> 00:52:01.204
Interesting.

00:52:01.204 --> 00:52:01.545
Okay.

00:52:01.704 --> 00:52:01.934
Yeah.

00:52:01.934 --> 00:52:02.934
So that was really fun.

00:52:03.315 --> 00:52:05.474
So super early cloud really in some ways.

00:52:05.644 --> 00:52:06.025
Yep.

00:52:07.724 --> 00:52:07.824
And.

00:52:09.550 --> 00:52:13.500
And from there, like you mentioned, you, you got taken out of state for an opportunity.

00:52:13.500 --> 00:52:14.309
What was that?

00:52:14.329 --> 00:52:16.369
Or maybe went what time timeline?

00:52:16.550 --> 00:52:21.480
Um, yeah, so that there was a few, a few businesses and startups in between there.

00:52:21.480 --> 00:52:26.315
But, um, you know, I went, you started, Um, two that I started.

00:52:26.864 --> 00:52:29.135
I want to, I want to hear the first story of the first start.

00:52:29.425 --> 00:52:29.855
Yeah.

00:52:29.905 --> 00:52:34.864
So the, um, so I went to, um, there was a startup in Boulder called MinuteKey.

00:52:35.974 --> 00:52:36.315
Okay.

00:52:36.565 --> 00:52:42.775
And they, um, they developed those kiosks that you see in grocery stores where you put your house key in.

00:52:42.775 --> 00:52:43.215
Yeah, yeah.

00:52:43.534 --> 00:52:45.684
And 60 seconds later, it kicks out a copy.

00:52:45.724 --> 00:52:49.744
A little bit similar to when you buy your dog tag at Vetco or whatever.

00:52:49.824 --> 00:52:50.695
Yeah, exactly.

00:52:51.235 --> 00:52:59.275
So they had, um, they had put out a couple of prototypes of those machines and gotten some traction in the market, gotten quite a bit of funding.

00:52:59.849 --> 00:53:05.460
Um, but they really needed some professional help in terms of how to develop a product.

00:53:05.519 --> 00:53:05.840
Okay.

00:53:06.070 --> 00:53:09.900
So they brought me in, you know, I analyzed the To be kind of the product manager?

00:53:09.949 --> 00:53:10.300
Yeah.

00:53:10.440 --> 00:53:10.710
Yeah.

00:53:10.909 --> 00:53:11.449
Effectively?

00:53:11.489 --> 00:53:11.860
Yeah.

00:53:11.900 --> 00:53:12.199
Yeah.

00:53:12.199 --> 00:53:15.989
So I And the problem solver for the few little glitches that were keeping so many people from buying it?

00:53:16.039 --> 00:53:16.400
Right.

00:53:17.030 --> 00:53:17.380
Or whatever.

00:53:17.380 --> 00:53:22.389
And so, but you know, how do you scale from a handful to three or four thousand of these machines?

00:53:22.449 --> 00:53:22.730
Right.

00:53:23.039 --> 00:53:25.989
And, um, what are the challenges associated with that?

00:53:26.000 --> 00:53:32.559
What does the machine need to do not only to meet the business goals, but also meet the goals of the consumer and that kind of thing.

00:53:32.789 --> 00:53:36.260
And so, you know, I ran that, um, scaled that up.

00:53:36.329 --> 00:53:36.500
Yeah.

00:53:36.500 --> 00:53:36.789
Yeah.

00:53:37.119 --> 00:53:37.869
Sounds pretty interesting.

00:53:37.900 --> 00:53:38.110
Yeah.

00:53:39.019 --> 00:53:44.909
Then, um, I started a, um, it was, it was an engineering.

00:53:45.130 --> 00:53:46.369
Did you get chips for that?

00:53:46.510 --> 00:53:49.739
Uh, did you get any extra compensation for helping them figure it out?

00:53:49.739 --> 00:53:50.739
Did you have an equity slice?

00:53:50.750 --> 00:53:52.639
Yeah, I had some, I had some little piece.

00:53:52.719 --> 00:53:53.019
Okay.

00:53:53.079 --> 00:53:53.340
Yeah.

00:53:53.760 --> 00:53:56.409
Well, that's not, I mean, it's nice if you're going to solve big problems.

00:53:56.409 --> 00:53:57.960
It's nice to have a piece of the upside.

00:53:58.010 --> 00:53:58.380
Yeah.

00:53:58.460 --> 00:53:58.800
Yeah.

00:53:59.480 --> 00:54:07.900
Um, then I went to a, um, engineering research, applied research, um, idea that, that, um, would take.

00:54:08.489 --> 00:54:17.139
Engineering technology for manufacturing and help small to medium sized manufacturers utilize that technology to become more competitive.

00:54:17.340 --> 00:54:17.670
Okay.

00:54:18.039 --> 00:54:19.690
Um, that failed miserably.

00:54:19.789 --> 00:54:20.250
Okay.

00:54:20.469 --> 00:54:22.019
What was the value proposition there?

00:54:22.019 --> 00:54:23.230
Is this machinery?

00:54:23.239 --> 00:54:24.150
Is it software?

00:54:24.420 --> 00:54:26.570
Um, all of the above.

00:54:26.570 --> 00:54:33.945
So one of the, one of the technologies was non destructive evaluation of, um, of weld joints and things like that.

00:54:34.815 --> 00:54:37.934
So you could determine non destructively whether or not a weld was good.

00:54:38.534 --> 00:54:54.594
You could also use artificial intelligence, um, looking at the stock coming into, uh, a, um, a forge machine and you could determine what parameters the forge machine needed in order to put out, you know, parts within spec and that kind of thing.

00:54:54.625 --> 00:54:55.204
Oh, right.

00:54:55.235 --> 00:54:59.625
Like the quality of the base stock coming in kind of matters, how long the forge has to cook it kind of thing.

00:54:59.875 --> 00:55:01.925
And it's real time evaluation.

00:55:01.945 --> 00:55:02.264
Okay.

00:55:02.264 --> 00:55:02.695
Interesting.

00:55:03.014 --> 00:55:09.974
You know, so the idea was that a lot of this, this technology, small to medium sized manufacturers can't afford to develop.

00:55:09.974 --> 00:55:10.304
Sure.

00:55:10.635 --> 00:55:13.034
And so we would develop it and then make it available.

00:55:13.275 --> 00:55:13.456
Yep, yep.

00:55:13.724 --> 00:55:16.385
So, and then, like, what was the failure?

00:55:17.184 --> 00:55:19.675
So it was a hybrid model.

00:55:19.704 --> 00:55:22.405
It was a a, um, non-profit.

00:55:22.434 --> 00:55:23.565
Mm mm.

00:55:24.965 --> 00:55:26.795
Not for loss, but not for profit.

00:55:26.795 --> 00:55:27.155
Right, right.

00:55:27.215 --> 00:55:29.824
So that you could get government grants to do the research.

00:55:29.974 --> 00:55:30.125
Yep.

00:55:30.155 --> 00:55:34.054
And then you would charge small to medium sized manufacturers for those solutions.

00:55:34.085 --> 00:55:34.445
Right.

00:55:34.744 --> 00:55:38.135
And that was the, that was the sustaining component.

00:55:38.574 --> 00:55:39.715
The sustaining component.

00:55:39.715 --> 00:55:40.704
Never really materialized.

00:55:40.704 --> 00:55:40.795
Yeah.

00:55:40.795 --> 00:55:41.815
Gotcha, gotcha.

00:55:41.934 --> 00:55:46.465
Yeah, we researched some stuff, we came up with some conclusions and the marketplace didn't really find us.

00:55:46.525 --> 00:55:46.945
Yeah.

00:55:46.945 --> 00:55:49.945
And you know, I think there was a, there there, um.

00:55:50.344 --> 00:55:53.054
You know, that could have worked out, I think, with more time.

00:55:53.054 --> 00:55:56.045
But, um, so then I, I had an opportunity.

00:55:56.045 --> 00:56:05.985
There was a guy in Louisville that had developed technology, um, for taking sunlight, capturing it, um, on a rooftop.

00:56:07.090 --> 00:56:07.369
Okay.

00:56:07.420 --> 00:56:16.710
Unit putting it into, uh, fiber optics and, and then you basically can provide daylight at a very high efficiency.

00:56:17.409 --> 00:56:20.800
So I partnered with him and like a skylight.

00:56:20.800 --> 00:56:24.650
I, I actually had a business that did solar tubes back in the day.

00:56:24.650 --> 00:56:31.769
And so like, even in this place, they would put a skylight 10 feet up and then run a little tube and then a little receiver, and so you got skylight and sunlight in here.

00:56:31.769 --> 00:56:32.139
Yeah.

00:56:32.190 --> 00:56:32.489
Yeah.

00:56:32.755 --> 00:56:33.784
But in a different way.

00:56:34.005 --> 00:56:34.295
Yeah.

00:56:34.295 --> 00:56:37.315
And so this was, um, you know, pretty powerful technology.

00:56:37.315 --> 00:56:41.344
It was four or five times more efficient than any other, uh, that's really cool.

00:56:41.574 --> 00:56:49.755
And, you know, there's, so you have this, this beautiful technology, but what do you do with it?

00:56:49.925 --> 00:56:50.164
Yeah.

00:56:50.164 --> 00:56:51.255
You're competing with a light bulb.

00:56:51.664 --> 00:56:52.065
Right.

00:56:52.255 --> 00:56:58.315
Uh, that run, and now we've got LEDs and stuff besides and whatever else, you know, they just don't take that much energy, right?

00:56:58.315 --> 00:57:02.954
And so, you know, you start looking at, well, could it, could it replace the lighting and business and.

00:57:03.510 --> 00:57:05.269
In, in office buildings.

00:57:06.659 --> 00:57:09.980
Well, it could, but who cares?

00:57:10.900 --> 00:57:12.130
Does the tenant care?

00:57:12.760 --> 00:57:22.909
Yeah, the tenant would see a decrease in their utility bill, but the owner of the building has to approve all this change to the infrastructure and they see no benefit to it.

00:57:23.039 --> 00:57:23.250
Yeah.

00:57:23.885 --> 00:57:39.574
So that really turned out not to be maybe you might have Happier employees by a little bit or something because they got natural sunlight instead of these right good light bulbs But then we thought hey, I got an idea all these marijuana growers.

00:57:39.585 --> 00:57:39.954
Mm hmm.

00:57:40.784 --> 00:57:46.755
They're using all this crazy amounts of electricity Yeah, maybe we can pipe in natural sunlight.

00:57:46.974 --> 00:57:49.284
Yeah full spectrum natural sunlight, right?

00:57:49.715 --> 00:57:52.025
And help and grow marijuana that way.

00:57:52.085 --> 00:58:05.929
Yeah, and so, you know, we came up with this You All the, all the analysis that showed that we could probably grow marijuana and we could do it full spectrum and it would probably be cheaper.

00:58:06.719 --> 00:58:08.019
And all this other stuff.

00:58:08.039 --> 00:58:13.730
And then, you know, I got to the point where I said, we have to prove that this is feasible.

00:58:14.309 --> 00:58:19.639
I don't want to do any more product development until we prove that this is feasible, viable.

00:58:19.650 --> 00:58:21.900
We got to talk to some growers and see if they want to buy this.

00:58:21.920 --> 00:58:22.920
We talked to a lot of growers.

00:58:23.230 --> 00:58:24.269
They were very interested.

00:58:25.019 --> 00:58:27.449
Everything looked good, but I said, we have to do a pilot.

00:58:29.440 --> 00:58:36.349
And so, um, we got a grower that agreed to do a 12 week flower cycle with our technology.

00:58:38.465 --> 00:58:41.434
And it turned out it did have an improvement to yield.

00:58:41.554 --> 00:58:41.855
Okay.

00:58:42.034 --> 00:58:48.175
But it was not enough of an improvement to justify kind of the re fitment of all these you.

00:58:48.175 --> 00:58:49.105
The complexity.

00:58:49.525 --> 00:58:51.505
The complexity, the cost, all of that.

00:58:51.855 --> 00:58:52.184
Yeah.

00:58:52.275 --> 00:58:56.204
And it turned out that LED technology was getting better and better and better.

00:58:56.235 --> 00:58:56.625
Mm-hmm.

00:58:56.744 --> 00:58:57.224
And cheaper.

00:58:57.224 --> 00:58:58.125
And cheaper and cheaper.

00:58:58.304 --> 00:58:58.545
Yep.

00:58:58.574 --> 00:58:59.954
And that was the solution.

00:59:00.135 --> 00:59:00.494
Yep.

00:59:00.585 --> 00:59:01.125
Was better.

00:59:01.125 --> 00:59:01.934
LED technology.

00:59:01.934 --> 00:59:02.925
That makes sense, honestly.

00:59:02.954 --> 00:59:04.275
'cause then, and plus you can do.

00:59:04.599 --> 00:59:08.079
Kind of whatever parts of the spectrum you want to supplement, you can do that with LED too.

00:59:08.090 --> 00:59:08.739
Right, right.

00:59:08.889 --> 00:59:09.409
Interesting.

00:59:09.610 --> 00:59:14.309
So I left that, um, you know, I gave it, I gave it the good college effort.

00:59:14.550 --> 00:59:14.789
Yeah.

00:59:14.920 --> 00:59:18.460
And, um, I'm sure that technology at some point will find a home.

00:59:19.150 --> 00:59:19.579
Maybe.

00:59:19.699 --> 00:59:21.570
It's still in hibernation right now.

00:59:21.789 --> 00:59:25.559
But it was the classic example of a solution looking for a problem.

00:59:25.559 --> 00:59:26.019
Yeah, yeah, yeah.

00:59:26.539 --> 00:59:33.929
And, um, you know, that, that became kind of a recurring theme in my career is a lot of solutions looking for problems.

00:59:34.030 --> 00:59:34.260
Mm hmm.

00:59:34.570 --> 00:59:40.710
And so, it's about that time that I got the opportunity to build that investment fund.

00:59:41.030 --> 00:59:41.380
Okay.

00:59:41.440 --> 00:59:45.949
And the, the, the coaching program and the accelerator program in Buffalo.

00:59:46.019 --> 00:59:55.400
And, like, were there some, some wealthy and people in Buffalo that were like, Hey, we got enough money, we just need the right person to build this around?

00:59:55.400 --> 00:59:56.650
Or like, what, how, what's that?

00:59:57.000 --> 00:59:57.219
Yeah.

00:59:57.219 --> 00:59:59.860
You said I got this opportunity, that seems such a random thing.

00:59:59.860 --> 01:00:01.780
Yeah, it sounds random.

01:00:01.780 --> 01:00:08.784
Um, So the connection is, um, I had a very close friend in Buffalo who told me this, this thing was coming up.

01:00:08.795 --> 01:00:09.155
Okay.

01:00:09.385 --> 01:00:18.724
But what it is, is you, you know, Buffalo has this history of being, you know, the center of the universe in terms of manufacturing at the turn of the century in the 1900s.

01:00:18.724 --> 01:00:20.864
Sure, and Woodward Governor here locally.

01:00:20.974 --> 01:00:21.855
The center of wealth.

01:00:21.855 --> 01:00:22.465
Kodak, right?

01:00:22.465 --> 01:00:22.715
Yeah.

01:00:22.715 --> 01:00:23.385
Even and stuff.

01:00:23.644 --> 01:00:26.795
It was like the center of wealth in, in industrial America.

01:00:26.835 --> 01:00:27.054
Hmm.

01:00:27.429 --> 01:00:32.469
And, you know, in the 50s, 60s, 70s, and 80s, that all just tanked, right?

01:00:32.500 --> 01:00:40.239
And so, you know, Buffalo's been this great culture, this great city looking for a spark.

01:00:40.869 --> 01:00:47.769
And the people there are just incredibly hardworking and innovative, but they just kind of needed a spark.

01:00:48.119 --> 01:01:01.195
And so the state of New York and other foundations started realizing, You know, maybe the spark is to start putting some things in place for entrepreneurial endeavors in Buffalo.

01:01:01.625 --> 01:01:01.925
Yeah.

01:01:02.155 --> 01:01:04.985
And so Well, and Pittsburgh has had kind of a similar Exactly.

01:01:04.994 --> 01:01:07.894
Uh, whatever, rebirth of sorts.

01:01:08.025 --> 01:01:08.304
Right.

01:01:08.304 --> 01:01:10.105
And probably came with some intentionality.

01:01:10.864 --> 01:01:11.125
Yeah.

01:01:11.125 --> 01:01:23.065
And so, you know, what ended up happening is the state of New York and, and, and other philanthropic groups wanted to start funding, um, startups in Buffalo.

01:01:23.195 --> 01:01:23.465
Okay.

01:01:23.465 --> 01:01:23.514
Yeah.

01:01:24.105 --> 01:01:37.144
And so they started pulling together these resources looking for someone who could kind of, you know, put that together, pull it all together and put something together that was actually going to work.

01:01:37.195 --> 01:01:37.494
Right.

01:01:38.275 --> 01:01:41.534
Well, cause it's easy to give a bunch of grants away and have none of it ever do anything.

01:01:41.565 --> 01:01:41.855
Right.

01:01:41.855 --> 01:01:51.105
And so that's, that's, that's where I came in and, you know, I said, okay, um, let's take a step back and think about root cause.

01:01:51.554 --> 01:01:51.954
Yeah.

01:01:51.985 --> 01:01:53.085
Why do startups fail?

01:01:53.085 --> 01:01:53.125
Right.

01:01:55.260 --> 01:01:58.530
Well, 90 percent of them fail because they have a solution to a problem.

01:01:58.530 --> 01:01:59.159
That's not worth solving.

01:02:01.130 --> 01:02:04.679
So we do know that 90 percent of the startups fail for that reason.

01:02:05.610 --> 01:02:09.010
We would be remiss if we didn't mitigate that as our number one risk.

01:02:10.329 --> 01:02:10.639
Right.

01:02:10.670 --> 01:02:21.360
And so, um, and I said, the way we do that as we intervene very, very early before they've become enamored with their solution, spend all their life savings on a solution.

01:02:21.920 --> 01:02:23.489
Let's intervene before that happens.

01:02:24.594 --> 01:02:38.844
And so, um, you know, I put together this, this phased program where if you wanted to become part of this, I'll give you incubator space and I'll give you coaching for three months.

01:02:39.664 --> 01:02:42.994
Those first three months, you're not allowed to talk about your solution.

01:02:43.715 --> 01:02:44.144
Okay.

01:02:45.074 --> 01:02:53.764
And I went through this whole, um, kind of rigorous process where I would force them to answer questions about what's your target market.

01:02:53.764 --> 01:02:53.795
Okay.

01:02:54.534 --> 01:03:04.405
What problem do they have if you could solve that problem, and I don't know what I don't want to know how you're gonna solve it But if you could solve it, how much how much could you charge for it?

01:03:04.425 --> 01:03:21.284
You know and I want you to gather evidence about how big that market might be if you're right about your target and all of Those sorts of things then I would say if you get through those first three months And I believe that you may be on to something.

01:03:21.864 --> 01:03:25.739
I'll give you a hundred thousand dollars in six months You To prove you might be right.

01:03:26.530 --> 01:03:29.980
That still doesn't mean I want you to go spend a hundred thousand dollars on product development.

01:03:29.980 --> 01:03:33.269
I want you to work on proving.

01:03:33.985 --> 01:03:37.605
Or getting more, um, confidence that you might be right.

01:03:37.605 --> 01:03:42.204
How many customers actually are there, I want you to talk to people about what they actually would pay for this.

01:03:42.244 --> 01:03:42.635
Right.

01:03:42.715 --> 01:03:43.335
Those kind of things.

01:03:43.344 --> 01:03:43.655
Right.

01:03:43.744 --> 01:03:45.375
Putting some quantification to those guesses.

01:03:45.465 --> 01:03:54.755
And if they get through that, then there's 250, 000 to do a very early minimum viable product to prove even further that you might be on to something.

01:03:54.764 --> 01:03:56.744
You're still not doing product development yet.

01:03:57.925 --> 01:04:02.795
But now you're preparing to, to prove to other investors you might be right.

01:04:04.224 --> 01:04:12.114
And so that was the, and that's when the, and then at that point they might get either angel funding or, or a seed round or something like that.

01:04:12.125 --> 01:04:12.405
Yeah.

01:04:12.405 --> 01:04:18.735
So I would do pre seed a hundred K 250 K, um, kind of pre seed seed.

01:04:19.215 --> 01:04:22.704
And then, you know, later I would help broker a deal.

01:04:22.844 --> 01:04:23.164
Right.

01:04:23.264 --> 01:04:25.034
Um, maybe even put some of your own chips in too.

01:04:25.344 --> 01:04:28.014
Put another million in and get other investors.

01:04:28.844 --> 01:04:29.894
That was kind of the concept.

01:04:29.905 --> 01:04:38.784
Now, are these, um, like software as a service products or the physical products, uh, mostly with some technology involved, I'm assuming, but maybe not.

01:04:38.835 --> 01:04:39.804
It didn't have to be.

01:04:39.914 --> 01:04:43.905
Is there stories that you're particularly proud of, um, from that incubator?

01:04:43.985 --> 01:04:44.375
Yeah.

01:04:44.385 --> 01:04:56.554
So you can talk about, yeah, no, there's, there's a couple, you know, the one that, that I'm really, that I think about all the time is there was, um, a lot of this was through.

01:04:57.090 --> 01:04:58.369
The University of Buffalo.

01:04:58.889 --> 01:05:06.760
So for logistical reasons, it was easier to take this investment and put it into the infrastructure of university at Buffalo.

01:05:07.329 --> 01:05:12.630
And so we would take not only innovations from the community, but innovations from university at Buffalo.

01:05:13.230 --> 01:05:17.420
And, yeah, kind of that notion of a commercializing stuff that's been invented here.

01:05:17.469 --> 01:05:17.820
Yep.

01:05:18.369 --> 01:05:27.010
So there was this, um, um, medical student, I think he, he had graduated by this time, but he had an idea of saving.

01:05:27.704 --> 01:05:37.304
Healthy stem cells for use later when people got cancer and charging Storage fee for your stem cells, right?

01:05:37.394 --> 01:05:38.744
Because it's your actual stem cells.

01:05:38.744 --> 01:05:39.105
Yep.

01:05:39.284 --> 01:05:39.635
Okay.

01:05:39.784 --> 01:05:40.114
Yep.

01:05:40.264 --> 01:05:42.724
Yeah, and so Stem cell bank.

01:05:42.815 --> 01:06:05.000
Yeah, and so he was convinced that he needed a million dollars to build this lab for extracting and storing So he came into the program and I said Excuse me He came into the program and I said Let's, let's put that aside for a minute.

01:06:06.019 --> 01:06:08.039
Let's talk about who your target customer is.

01:06:08.059 --> 01:06:13.719
And he was like, um, people who are concerned about getting cancer someday.

01:06:13.969 --> 01:06:14.510
I don't know.

01:06:15.010 --> 01:06:24.980
So, so we kept, you know, I met with him every week to talk about the kinds of things he could look at to determine what the target customer was.

01:06:25.650 --> 01:06:37.449
So he, he was a very good student, he was very diligent and he, he came to the conclusion that it was, you know, women of a certain age, of a certain income level that were the most likely to want this.

01:06:37.510 --> 01:06:37.820
Okay.

01:06:40.139 --> 01:06:40.699
Excuse me.

01:06:41.489 --> 01:06:50.710
And so then we started talking about the value proposition and he was dumbfound, he was befuddled for a while.

01:06:51.710 --> 01:06:53.719
How do you quantify the value of that?

01:06:53.769 --> 01:06:54.210
Yeah.

01:06:54.340 --> 01:06:56.210
And I said, well, just think about it.

01:06:56.690 --> 01:06:58.309
Are there any other things out there?

01:06:59.130 --> 01:07:01.780
that are similar in terms of the value that they provide.

01:07:03.369 --> 01:07:09.090
And a couple of weeks later he came back and he goes, I think it's kind of like life insurance.

01:07:10.900 --> 01:07:12.280
It's really peace of mind.

01:07:14.130 --> 01:07:27.000
And so then he started really understanding the demographic and psychographic profile of his target, what they were really wanting and understanding, you know, what their needs were and how to provide that.

01:07:27.000 --> 01:07:33.940
And so he spent his first hundred thousand on really understanding that more deeply.

01:07:34.905 --> 01:07:42.835
And then he spent his next 250, 000 getting a third party lab spun up to do some of it.

01:07:42.835 --> 01:07:44.275
But it wasn't a long term solution.

01:07:44.284 --> 01:07:50.465
It was to get enough customers to sign up for it, pay for it, and store their cells so that he could get a Series A round.

01:07:51.635 --> 01:07:56.485
And so, you know, what was so rewarding about that is now he's growing.

01:07:56.989 --> 01:08:00.559
You know, he's now getting to the point where he's building the infrastructure himself.

01:08:00.829 --> 01:08:07.320
He's gotten the funding, seeing where he was when he came in and seeing where he is now.

01:08:07.519 --> 01:08:08.619
It's like night and day.

01:08:08.670 --> 01:08:09.489
Yeah, that's really cool.

01:08:09.539 --> 01:08:15.559
And you know, it was just really rewarding to see somebody that passionate and that open to.

01:08:15.925 --> 01:08:17.234
And what was his field?

01:08:17.295 --> 01:08:20.564
Like, he was obviously passionate about the stem cell technology for some reason?

01:08:20.564 --> 01:08:22.024
Yeah, he was a medical student.

01:08:22.095 --> 01:08:22.555
Oh, yeah.

01:08:22.635 --> 01:08:22.965
Yeah.

01:08:23.324 --> 01:08:27.015
He just probably saw somebody's life impacted by access to stem cells.

01:08:27.015 --> 01:08:28.085
Well, shouldn't everybody have this?

01:08:28.654 --> 01:08:38.725
Well, in medical students especially, like, my veterinarian or any veterinarian will spend all of your money if it will increase by 1 percent the chance that your dog lives.

01:08:38.784 --> 01:08:39.215
Right.

01:08:39.225 --> 01:08:40.515
From getting run over by a car.

01:08:40.524 --> 01:08:40.824
Right.

01:08:40.885 --> 01:08:41.324
Or whatever.

01:08:41.324 --> 01:08:41.654
Right.

01:08:41.734 --> 01:08:43.225
Like, it doesn't really matter.

01:08:43.225 --> 01:08:46.534
Your wallet is to their concern.

01:08:46.534 --> 01:08:48.354
Yeah.

01:08:48.354 --> 01:08:48.645
Yep.

01:08:48.704 --> 01:08:51.385
Um, and it's kind of the nature of medicine in some ways.

01:08:51.385 --> 01:08:56.755
One of the things that's the hardest to combat is except for the risk of being sued for not doing enough.

01:08:56.755 --> 01:08:57.494
So then we test it.

01:08:57.694 --> 01:08:58.045
Right.

01:08:58.324 --> 01:09:01.675
Every test under the sun, which again is spending all your money.

01:09:01.725 --> 01:09:02.225
Right.

01:09:02.345 --> 01:09:03.645
Uh, anyway, I digress.

01:09:03.715 --> 01:09:04.095
Yeah.

01:09:04.774 --> 01:09:05.074
Yeah.

01:09:05.074 --> 01:09:06.675
So, you know, and, and it was.

01:09:07.420 --> 01:09:09.039
It was high tech stuff like that.

01:09:09.189 --> 01:09:24.529
Um, you know, we had some battery technology, we had that kind of thing, but we also had some, you know, just really good ideas that just needed to get, needed, needed some structure in order to get to market, you know?

01:09:24.630 --> 01:09:26.239
How long were you involved with this accelerator?

01:09:26.250 --> 01:09:27.699
Uh, it was about four years.

01:09:27.760 --> 01:09:28.079
Okay.

01:09:28.189 --> 01:09:28.550
Yep.

01:09:29.149 --> 01:09:31.510
Had to come back to Colorado for family reasons.

01:09:32.090 --> 01:09:32.350
Yeah.

01:09:33.170 --> 01:09:35.583
You're caring for a parent or something like that, is that true?

01:09:35.583 --> 01:09:35.850
Yeah.

01:09:35.850 --> 01:09:37.859
It has, uh, in the.

01:09:38.734 --> 01:09:40.024
Challenges of later life, I guess.

01:09:40.055 --> 01:09:40.595
Yeah.

01:09:40.675 --> 01:09:41.024
Yeah.

01:09:41.345 --> 01:09:42.795
Did they move down from Leadville?

01:09:43.034 --> 01:09:45.265
He moved down right after I graduated from high school.

01:09:45.305 --> 01:09:45.795
Oh, really?

01:09:45.864 --> 01:09:46.024
Yeah.

01:09:47.010 --> 01:09:48.869
Turns out he thought he was staying there for me.

01:09:50.609 --> 01:09:52.210
Well, there was more rodeos up there and stuff.

01:09:52.210 --> 01:09:52.600
Right, that's right.

01:09:53.880 --> 01:10:01.819
Um, let's uh, I guess, other business lessons, um, that we should talk about from the incubator days, or?

01:10:01.840 --> 01:10:17.579
Well, I think, um, I mean, building a community like that, I, I met Allison Seebeck early in her, uh, time at the Warehouse Business Accelerator, and it's hard to spin something like that up, even if you've got, you know, Investors that are eager to support, you know, known demand.

01:10:17.590 --> 01:10:19.279
There's just a lot of, a lot of complexity.

01:10:19.439 --> 01:10:19.710
Yeah.

01:10:19.710 --> 01:10:23.119
And I think, um, you know, there's a couple of things that make it difficult.

01:10:23.300 --> 01:10:31.550
You know, one is, um, especially when you're doing it, like I was in Buffalo, where I had, it was basically a double bottom line investment fund, right?

01:10:32.060 --> 01:10:40.979
I had to create, the result had to be jobs and economic impact, but I had to get enough return on that investment to keep the fund evergreen, right?

01:10:42.100 --> 01:10:44.619
So it turns out it can be very difficult to.

01:10:44.689 --> 01:11:02.569
And so, you know, I said early on, yes, I'm here to create jobs, but I'm going to be brutal in terms of if the founder is not a fit, if they're not open, right, they're out.

01:11:02.760 --> 01:11:03.050
Right.

01:11:03.100 --> 01:11:06.079
If I can't, if they're not open to, to help, they're out.

01:11:06.159 --> 01:11:06.399
Yeah.

01:11:06.470 --> 01:11:10.659
If their idea sucks and they're not willing to pivot off of it, they're out.

01:11:11.675 --> 01:11:11.954
Right.

01:11:11.965 --> 01:11:14.295
And so that's what that first three months was for.

01:11:14.295 --> 01:11:17.654
And a lot of these places that are trying to do this.

01:11:18.055 --> 01:11:19.274
And are you like working there?

01:11:19.274 --> 01:11:21.345
You're coaching them once a week or something like that, too.

01:11:21.354 --> 01:11:22.984
Are you in some other people as well?

01:11:23.015 --> 01:11:27.585
Yeah, I had eventually, you know, started out with me and a few other people that worked for me.

01:11:27.935 --> 01:11:40.694
Eventually we built the whole infrastructure with what we call the entrepreneurs in residence, where I would hire serial entrepreneurs for 10 hours a week and I would assign them in areas where they had expertise and that kind of thing.

01:11:40.694 --> 01:11:41.635
So we built the whole.

01:11:42.055 --> 01:11:43.595
a pretty big infrastructure around.

01:11:43.604 --> 01:11:45.694
Well, and you were not attached to that community.

01:11:45.694 --> 01:11:46.904
So that was quite a push.

01:11:47.220 --> 01:11:50.310
You must have had somebody, like, connecting you to the right people with intention.

01:11:50.329 --> 01:11:52.989
You know, the funny thing was, they Or they just got drawn to you.

01:11:53.060 --> 01:11:56.529
They, they, they adopted me as one of their own from the beginning.

01:11:56.779 --> 01:11:57.630
It was really cool.

01:11:57.689 --> 01:11:58.210
That's neat.

01:11:58.270 --> 01:12:01.930
You know, and when I started showing results, it was just like a snowball effect.

01:12:01.939 --> 01:12:02.500
Yeah, yeah.

01:12:02.500 --> 01:12:02.779
You know.

01:12:02.899 --> 01:12:17.505
Well, and because Buffalo's, you know, What, maybe half a million people or something like that in the, in the city and maybe a million, but it's like, in some ways it's more of a, you know, people have asked me where would local think tank move to next, you know, and we're local community think tank.

01:12:18.164 --> 01:12:22.484
And I hate to say it, but I think Buffalo would be a better fitted community than would Denver.

01:12:22.545 --> 01:12:22.824
Yeah.

01:12:23.055 --> 01:12:32.234
Cause there's just more sense of community kind of, Denver is kind of this fragmented amalgamation from all these different kinds of communities and Colorado Springs is even kind of that way.

01:12:32.234 --> 01:12:33.314
It's not really a community.

01:12:33.314 --> 01:12:33.425
It's.

01:12:33.765 --> 01:12:48.944
Right and different communities, you know, chase them to each other and I grew up in Colorado and I love Colorado But the thing that I realized when I went to Buffalo is a lot of people who are in Colorado or from somewhere else Mm hmm, and they're here to live the lifestyle.

01:12:49.085 --> 01:13:00.194
Mm hmm And when I went to individualistic basis, right and when I went to Buffalo I realized everybody that was there was there because they loved that community and they wanted to be there Yeah, so it was a very different vibe.

01:13:00.234 --> 01:13:09.220
Yeah, and so everybody was more You almost altruistic if you, if you could say, because they really wanted to improve the other people to succeed as much as anything.

01:13:09.220 --> 01:13:14.380
Um, I'm going to propose that we take a short potty break and then we'll hit the closing segments.

01:13:14.510 --> 01:13:15.000
Sounds good.

01:13:15.130 --> 01:13:15.550
Go from there.

01:13:15.649 --> 01:13:15.970
All right.

01:13:16.029 --> 01:13:16.189
All right.

01:13:16.210 --> 01:13:16.470
Cheers...

01:14:05.909 --> 01:14:12.460
So the closing segments, uh, as indicated in my overview email, Faith, Family, and Politics.

01:14:13.149 --> 01:14:15.479
Uh, do you have a preference on where to start in that conversation?

01:14:15.619 --> 01:14:16.250
Wherever you want.

01:14:16.439 --> 01:14:18.149
Um, let's talk about family.

01:14:18.199 --> 01:14:22.319
I feel like we could have met your wife, uh, Along the journey.

01:14:22.710 --> 01:14:23.739
You're still married, I think.

01:14:23.899 --> 01:14:24.159
Yes.

01:14:24.270 --> 01:14:24.569
Okay.

01:14:25.149 --> 01:14:26.170
How many kiddos now?

01:14:26.579 --> 01:14:27.789
So I have two.

01:14:27.810 --> 01:14:28.689
She has three.

01:14:28.770 --> 01:14:29.149
Okay.

01:14:29.279 --> 01:14:29.550
Yep.

01:14:30.380 --> 01:14:31.659
So she brought three.

01:14:32.930 --> 01:14:34.840
We just got married about ten years ago.

01:14:34.850 --> 01:14:36.670
Oh, so you had a different wife?

01:14:36.689 --> 01:14:37.189
Different wife.

01:14:37.659 --> 01:14:38.449
Okay, gotcha.

01:14:38.979 --> 01:14:43.555
Well, let's uh, I guess let's just open the family topic up to you.

01:14:43.564 --> 01:14:46.225
How did that evolution come along?

01:14:46.244 --> 01:14:50.175
So you've got two with your first wife and she's got three with her first husband together.

01:14:50.225 --> 01:14:50.585
Right.

01:14:50.675 --> 01:14:51.045
Okay.

01:14:51.085 --> 01:14:51.335
Yep.

01:14:51.555 --> 01:14:52.645
And, and who's your wife now?

01:14:52.795 --> 01:14:53.375
Does she have a name?

01:14:53.704 --> 01:14:54.135
Tricia.

01:14:54.204 --> 01:14:54.795
Hi, Tricia.

01:14:54.795 --> 01:14:56.600
She's the greatest.

01:14:56.600 --> 01:14:58.404
She's the greatest.

01:14:58.404 --> 01:14:58.744
Okay.

01:14:59.255 --> 01:15:02.345
Um, what would she say about you and where did she find you?

01:15:02.555 --> 01:15:05.385
Um, so her dad and my dad were friends.

01:15:05.585 --> 01:15:06.024
Oh, really?

01:15:06.274 --> 01:15:08.215
So when we were little kids, we played together.

01:15:08.234 --> 01:15:08.715
Oh, wow.

01:15:08.954 --> 01:15:16.265
And Um, you know, we'd known each other off and on, um, you know, when we were growing up.

01:15:16.324 --> 01:15:16.704
Sure.

01:15:16.755 --> 01:15:17.914
We kind of lost touch.

01:15:17.925 --> 01:15:17.944
Yeah.

01:15:18.114 --> 01:15:21.154
And then, you know, 20 some years later, we reconnected.

01:15:21.225 --> 01:15:21.574
Okay.

01:15:21.725 --> 01:15:24.895
You know, and I had two kids and she had three kids and, yep.

01:15:25.475 --> 01:15:27.635
So you came back here to help care for your dad.

01:15:27.645 --> 01:15:30.045
You have, you've got two sisters as well.

01:15:30.265 --> 01:15:32.895
Are they also caretaking, you go on shifts and things?

01:15:32.904 --> 01:15:34.024
Um, what's that look like?

01:15:34.274 --> 01:15:40.805
You know, we're all kind of pitching in, but they live, you know, in Colorado Springs and in Florence area.

01:15:40.805 --> 01:15:43.215
And so I'm kind of, You're the primary.

01:15:43.244 --> 01:15:44.034
I'm the primary.

01:15:44.185 --> 01:15:45.354
Does your dad live with you?

01:15:45.404 --> 01:15:46.795
No, he still lives alone.

01:15:46.814 --> 01:15:47.234
Oh wow.

01:15:47.265 --> 01:15:53.505
And so, um, he's gotten to the point though where, um, you know, I take care of all of his finances.

01:15:53.715 --> 01:15:54.975
I take care of everything.

01:15:54.975 --> 01:15:56.465
Is it Alzheimer's?

01:15:56.465 --> 01:15:56.715
Yeah.

01:15:56.784 --> 01:15:57.064
Okay.

01:15:57.104 --> 01:15:57.345
Yeah.

01:15:57.425 --> 01:15:57.895
And so.

01:15:57.914 --> 01:16:01.685
I met somebody with Lou Gehrig's, uh, recently as well, so I couldn't remember.

01:16:01.744 --> 01:16:02.265
Yeah.

01:16:02.375 --> 01:16:06.024
And you know, it's, it's, he does well if he's in his routine.

01:16:06.024 --> 01:16:06.225
Yeah.

01:16:06.225 --> 01:16:06.574
Yeah.

01:16:06.604 --> 01:16:10.604
And, um, so everything that I do for him is to keep him in his routine.

01:16:11.414 --> 01:16:20.045
It's, it's my, my grandmother, my dad's mom, uh, passed in that fashion and really up until the last couple of years, she was fairly independent as well.

01:16:20.125 --> 01:16:22.186
Um, with, again, with, uh.

01:16:22.186 --> 01:16:25.324
dad doing a bunch of things to make sure they got done and whatever else.

01:16:25.324 --> 01:16:30.034
But it's, I think the hardest part of it is how long it can be sometimes.

01:16:30.135 --> 01:16:30.574
Yeah.

01:16:30.664 --> 01:16:39.125
And his, you know, I just found out recently he has, he has Alzheimer's combined with vascular dementia, which I don't know the difference really.

01:16:39.125 --> 01:16:45.819
I guess I didn't really know the difference either, but, um, Now, what's become more predominant is the vascular dementia.

01:16:45.840 --> 01:16:46.420
Oh, is that right?

01:16:46.420 --> 01:16:46.680
Yeah.

01:16:46.720 --> 01:16:50.859
And so, it's progressing differently than it would have if it was only Alzheimer's.

01:16:50.869 --> 01:16:51.250
Okay.

01:16:51.470 --> 01:16:55.829
And so, he's, I think he's gonna be able to stay independent longer.

01:16:56.029 --> 01:16:56.949
Oh, okay.

01:16:57.020 --> 01:17:00.630
But it's still When they say vascular dementia, that's more of a blood flow thing?

01:17:00.670 --> 01:17:01.050
Yeah.

01:17:01.170 --> 01:17:01.449
Yeah.

01:17:01.579 --> 01:17:05.220
As contrasted with Alzheimer's is more of a protein Yeah.

01:17:05.449 --> 01:17:07.279
Neuron.

01:17:07.664 --> 01:17:08.555
Deficiencies, right?

01:17:08.604 --> 01:17:09.104
Or whatever.

01:17:09.154 --> 01:17:10.145
Yeah, and he has both.

01:17:10.145 --> 01:17:12.524
It's just that the vascular is more predominant.

01:17:12.595 --> 01:17:12.984
I see.

01:17:13.064 --> 01:17:13.475
Gotcha.

01:17:13.685 --> 01:17:18.885
Yeah Any key things that he taught you that have applied to your business career?

01:17:19.274 --> 01:17:27.824
You know, I think it's You know hard work and don't blame others.

01:17:28.234 --> 01:17:30.335
Look internally if you're having problems.

01:17:30.335 --> 01:17:33.784
Yeah, right There's no victims, right?

01:17:34.135 --> 01:17:37.494
If you don't like the path you're on Then you should do something.

01:17:38.074 --> 01:17:38.954
Yeah, right.

01:17:38.954 --> 01:17:39.984
And that's always stuck with.

01:17:40.005 --> 01:17:40.194
Yeah.

01:17:40.194 --> 01:17:40.425
Yeah.

01:17:40.454 --> 01:17:56.560
And you know, and then, you know, just the work ethic Yeah, you know when I was a kid when we were doing Projects on fence or whatever if I was standing there with my hands in my pocket, you know, he's He'd be like There's a million things you could be doing right now.

01:17:56.569 --> 01:17:57.840
There's a broom over there.

01:17:57.850 --> 01:17:58.979
There's a shovel over there.

01:17:58.979 --> 01:18:00.859
There's something you could be doing right now.

01:18:00.909 --> 01:18:04.829
You know, be it, be it plugged in enough to the situation that you can figure out what to do.

01:18:04.869 --> 01:18:05.220
Right.

01:18:05.270 --> 01:18:08.100
And, and, well, that's kind of that project based, right?

01:18:08.529 --> 01:18:08.779
Yeah.

01:18:08.819 --> 01:18:09.710
Or objectives based.

01:18:09.710 --> 01:18:09.939
Yeah.

01:18:09.939 --> 01:18:12.819
To your point, looking ahead, knowing what he might need next.

01:18:12.869 --> 01:18:13.239
Right.

01:18:13.329 --> 01:18:15.310
You know, dad, I'm going to go get the wire cutter.

01:18:15.329 --> 01:18:15.640
Right.

01:18:15.680 --> 01:18:17.310
You know, or we're almost out of posts here.

01:18:17.310 --> 01:18:19.090
I'm going to run back to the truck and get four more posts.

01:18:19.100 --> 01:18:19.670
Exactly.

01:18:19.680 --> 01:18:20.699
So we can finish this stretch.

01:18:20.699 --> 01:18:21.119
Yep.

01:18:21.229 --> 01:18:21.529
Yep.

01:18:21.590 --> 01:18:21.890
Yep.

01:18:22.090 --> 01:18:23.350
But I think, you know, just.

01:18:24.484 --> 01:18:27.645
You know, those kinds of things really stuck with me all my life.

01:18:27.664 --> 01:18:34.186
Would you ever consider that lifestyle of cows and horses and chickens and pigs and stuff?

01:18:34.186 --> 01:18:35.234
No, not so much.

01:18:35.654 --> 01:18:38.024
No, I just, you know, it's, it was a gray.

01:18:38.034 --> 01:18:39.354
I, I loved it.

01:18:39.744 --> 01:18:53.005
Um, but I started, as I mentioned, I started getting away from it when I, And then I realized, wow, there's so much more you can do in life if you're not, if you don't have the, the anchor of, of horses and cattle at home.

01:18:53.204 --> 01:18:56.354
So, um, with you and gosh, I'm sorry, Tricia.

01:18:56.454 --> 01:18:56.774
Yeah.

01:18:56.845 --> 01:18:59.935
Um, are you guys have any grandkids or anything yet?

01:18:59.935 --> 01:19:00.404
Yeah, we do.

01:19:00.414 --> 01:19:01.244
Some coming along soon.

01:19:01.395 --> 01:19:02.454
Let's see all together.

01:19:02.475 --> 01:19:04.824
Maybe we could play the one word description of grandkids.

01:19:04.864 --> 01:19:05.274
Yeah.

01:19:06.454 --> 01:19:10.465
Yeah, so we've got, uh, seven.

01:19:10.604 --> 01:19:11.795
Oh, that's a pretty good chunk.

01:19:12.034 --> 01:19:12.305
Yeah.

01:19:12.435 --> 01:19:12.765
Yeah.

01:19:13.555 --> 01:19:16.314
Yeah, she's, she's got two in Salt Lake.

01:19:16.314 --> 01:19:17.904
Her son is in medical school.

01:19:18.024 --> 01:19:18.625
Oh, cool.

01:19:18.845 --> 01:19:20.154
Actually, he's in his residency.

01:19:20.154 --> 01:19:21.284
His last year of residency.

01:19:21.284 --> 01:19:21.444
Yeah.

01:19:21.885 --> 01:19:28.154
And, um, one's just a baby, so I don't know about her personality, but the other one is just, she's just a firecracker.

01:19:28.524 --> 01:19:31.364
Super intelligent, great vocabulary, you know.

01:19:31.444 --> 01:19:32.055
Had like three.

01:19:32.244 --> 01:19:33.045
Yeah, right.

01:19:33.574 --> 01:19:37.484
Um, anything else when we talk about family that you'd really want to make sure we mention?

01:19:38.265 --> 01:19:38.925
Um.

01:19:39.895 --> 01:19:47.795
You know, I think, you know, for me, I, I haven't necessarily been driven by success, my life in my life.

01:19:47.805 --> 01:19:53.064
It's been about fulfillment, but really about providing security for my family.

01:19:53.895 --> 01:20:09.685
And, um, you know, it's, it's kind of come full circle with me that providing security for my family and helping others has kind of started to, to be the thing that fills my cup, you know, and so it's kind of related to the security thing.

01:20:10.284 --> 01:20:16.614
But it's really helping others overcome or avoid some of the mistakes that I've made, and seeing others be successful.

01:20:16.765 --> 01:20:17.015
Yeah.

01:20:17.064 --> 01:20:21.975
You know, that's really what's been important to me, and that's, to me it is in some way related to family.

01:20:22.064 --> 01:20:25.784
Well, and I think I see to some extent that family is.

01:20:26.404 --> 01:20:38.055
Like almost anybody I come across, uh, that could use my help, you know, like some of those founders in your incubator were, became almost like family to you, you cared that much about their experience, what they're, what they could do.

01:20:38.135 --> 01:20:38.925
Right, right.

01:20:39.265 --> 01:20:51.845
You know, and that's, that's part of what drew, drew me to EOS too is, you know, this whole idea that we help first with no expectations about getting anything out of it and everything else takes care of itself.

01:20:51.845 --> 01:20:51.864
Yeah.

01:20:52.154 --> 01:20:52.704
That's pretty cool.

01:20:53.925 --> 01:20:55.845
Um, faith or politics?

01:20:57.484 --> 01:20:59.595
We haven't talked about faith at all so far.

01:20:59.694 --> 01:21:06.095
Um, but I suspect that at least up in the mountains there, there's kind of a churchy community for most people or maybe not?

01:21:06.145 --> 01:21:12.545
Yeah, yeah, I mean I, I grew up, um My, my mom's family was Catholic.

01:21:12.604 --> 01:21:12.954
Okay.

01:21:13.225 --> 01:21:19.845
And, um, in order for my grandmother to approve the marriage with my dad, Yeah, yeah.

01:21:19.885 --> 01:21:22.045
all the kids had to be baptized Catholic.

01:21:22.425 --> 01:21:23.555
All the kids, all you kids.

01:21:23.645 --> 01:21:24.274
All of us kids.

01:21:24.274 --> 01:21:24.694
He didn't.

01:21:25.225 --> 01:21:25.954
He wasn't.

01:21:26.404 --> 01:21:27.284
He wasn't Catholic.

01:21:27.284 --> 01:21:43.255
He, you know, he went to non denominational churches, you know, but, um, yeah, so we went to Catholic church growing up and, um, you know, I remember when I got old enough to think independently, I remember asking my grandmother when we were at mass.

01:21:45.045 --> 01:21:51.904
Mainly being a smart aleck, but I would say, Hey, if we don't stand up and sit down, whenever they tell us to do, to do that, are we going to go to hell?

01:21:54.385 --> 01:22:02.154
She got so mad at me, but, um, So you're open to challenging the rules and the bends and whatever.

01:22:02.225 --> 01:22:04.725
I was open to challenging the, you know, yeah.

01:22:04.725 --> 01:22:07.385
The, the pomp and circumstance and all the rules.

01:22:08.239 --> 01:22:12.760
And, um, but I always believed in God and I always believed in a higher power.

01:22:12.920 --> 01:22:13.109
Yeah.

01:22:13.359 --> 01:22:17.630
And, you know, if I look at what's happened to me in my life, I know that that's true.

01:22:17.760 --> 01:22:18.050
Right.

01:22:18.079 --> 01:22:22.039
And, um, Once you start to see providence in your life, it's hard not to look at it again.

01:22:22.079 --> 01:22:22.489
Yeah.

01:22:22.630 --> 01:22:22.930
Yeah.

01:22:22.930 --> 01:22:31.930
And so, you know, I, I, um, I think I've, as I've gotten older too, the more I've come to realize that there is something greater than me.

01:22:31.939 --> 01:22:31.960
Yeah.

01:22:32.060 --> 01:22:33.170
There is a higher power.

01:22:33.210 --> 01:22:33.920
Yeah, yeah.

01:22:33.920 --> 01:22:34.359
You know.

01:22:35.130 --> 01:22:37.729
Um, politics?

01:22:37.729 --> 01:22:37.789
Yeah.

01:22:39.670 --> 01:22:57.319
Yeah, I mean, I can tell you my view of politics is right along the line of everything I've said about business, which is, I wish that we could talk about the root cause of issues, rather than getting in separate camps and debating solutions.

01:22:57.949 --> 01:22:58.439
Right?

01:22:58.710 --> 01:23:04.350
You know, like, I wish we could agree on the facts, agree on the problem, and then go into solution space.

01:23:04.430 --> 01:23:04.939
Yeah, yeah.

01:23:04.989 --> 01:23:24.189
But we can't seem to do that, and that's Yeah, it's an interesting, like, even when you take it to any of those major, you know, like, nobody can argue that the, the inner cities of too many cities in America are a trap that's really hard to escape from or to create economic solvency from.

01:23:24.279 --> 01:23:24.560
Right.

01:23:24.680 --> 01:23:27.545
You know, they don't even have a, an affordable supermarket in a lot of these places.

01:23:27.545 --> 01:23:29.170
Walmart's pulling out, you know?

01:23:29.170 --> 01:23:29.590
Right, right.

01:23:29.649 --> 01:23:31.600
Um, I was in St.

01:23:31.600 --> 01:23:38.289
Lucia recently, and there's a little town called, uh, Ons, Onslauray.

01:23:38.795 --> 01:23:42.475
And it's kind of like where all the poor people live in St.

01:23:42.475 --> 01:23:48.305
Not all of them, but, but there's six or eight thousand people that live there and they don't even have a gas station or a proper grocery store.

01:23:49.159 --> 01:23:54.159
Um, because it's just not economically viable, you know, I guess, or whatever.

01:23:54.560 --> 01:23:58.520
The guy that we were talking to said it's kind of politics is why it's that way.

01:23:58.729 --> 01:24:04.720
And maybe it's politics is the way it's that way in Detroit and was that way in Pittsburgh and Buffalo.

01:24:04.920 --> 01:24:05.289
I don't know.

01:24:05.859 --> 01:24:06.140
Yeah.

01:24:06.220 --> 01:24:11.590
Um, what would you, so that would be your main solution is just listen to each other more and identify the real problem.

01:24:11.590 --> 01:24:11.819
Yeah.

01:24:11.819 --> 01:24:12.159
Yeah.

01:24:12.199 --> 01:24:17.909
I mean, have you ever sat down and, and talk with somebody and.

01:24:18.835 --> 01:24:23.234
Just decided you hate them because of, no, you've never done that.

01:24:23.244 --> 01:24:23.555
Right?

01:24:23.614 --> 01:24:23.984
No.

01:24:24.755 --> 01:24:26.524
I mean, only if they decide they hate me.

01:24:26.564 --> 01:24:26.904
Right.

01:24:26.935 --> 01:24:31.314
Well, that's really the only, that's really that my only criteria almost.

01:24:31.324 --> 01:24:47.194
No, but I mean, you know, we, we all have quite a bit in common and, um, you know, the other thing too, you know, I've traveled outside of the country and, you know, we went to Mexico about 10 years ago and there was this great kid.

01:24:47.204 --> 01:24:48.154
He was a local kid.

01:24:48.604 --> 01:24:50.074
He worked at the resort that we were at.

01:24:50.185 --> 01:24:50.375
Yeah.

01:24:51.560 --> 01:25:01.430
And that kid was super smart and, you know, just a great kid, but he, you know, he's living hand to mouth.

01:25:02.260 --> 01:25:04.960
He can barely scratch together a living.

01:25:05.310 --> 01:25:11.079
And I'm thinking the only difference between him and me is where I was born and who I was raised by.

01:25:11.319 --> 01:25:11.680
Right.

01:25:11.880 --> 01:25:13.090
That's the only difference.

01:25:13.369 --> 01:25:19.569
And so, you know, I'm pretty damn lucky to have been born and raised in America.

01:25:19.890 --> 01:25:21.850
And I'm proud of that.

01:25:21.949 --> 01:25:22.229
Yeah.

01:25:22.380 --> 01:25:23.539
I think all of us are.

01:25:23.845 --> 01:25:33.414
And if we come from that fundamental basis, we probably could, um, we could probably talk about our differences a little bit more, um, intelligently.

01:25:33.895 --> 01:25:40.685
Well, yes, and, like, I don't want you to discount the fact that you didn't, you came from very humble beginnings as well.

01:25:41.435 --> 01:25:42.005
You know.

01:25:42.204 --> 01:25:44.194
Yeah, but not, not like that kid.

01:25:44.425 --> 01:25:44.795
No.

01:25:45.045 --> 01:25:45.284
True.

01:25:45.354 --> 01:25:45.645
True.

01:25:45.914 --> 01:25:46.375
Understood.

01:25:47.854 --> 01:25:52.984
But your family certainly didn't have enough extra resources to scholarship him to come to college in America.

01:25:53.185 --> 01:25:56.925
No, you know, no So that's that's true.

01:25:57.005 --> 01:26:06.640
But you know, I but I still you know, it's like the other thing God God blessed me with some certain amount of capabilities to become an engineer.

01:26:06.989 --> 01:26:08.210
I was, I didn't do anything.

01:26:08.529 --> 01:26:09.460
I was given that.

01:26:09.579 --> 01:26:09.869
Sure.

01:26:10.069 --> 01:26:10.220
Yeah.

01:26:10.430 --> 01:26:11.649
And I'm lucky and thankful.

01:26:11.989 --> 01:26:17.609
Well, I think, you know, a lot of people think that even ideas don't necessarily come from your brain.

01:26:17.609 --> 01:26:18.880
They're like gifted upon you.

01:26:20.539 --> 01:26:23.010
Einstein started to wonder about how things come to him.

01:26:23.069 --> 01:26:24.020
Right, right.

01:26:24.100 --> 01:26:39.854
Um, what do you think about kind of the Like we've had a really interesting, almost shift in the political, you know, in this most recent election, I think roughly two thirds of the funding went to the, to the Democratic Party?

01:26:40.305 --> 01:26:56.564
Or, not two thirds of the funding, but the, the, the millionaires and billionaires are funding the Democratic Party much more so now and, and the Republican Party has become kind of the blue collar populist Yeah, I can't discuss party of the working class, and that's all happened in the last ten years.

01:26:56.625 --> 01:26:56.954
Right.

01:26:57.494 --> 01:26:59.715
That, that's the problem with labels too, right?

01:26:59.734 --> 01:27:00.175
Right.

01:27:00.244 --> 01:27:06.145
It's You know, I don't know, you know, it's not the Republican party that we knew in the eighties.

01:27:06.345 --> 01:27:06.875
For sure.

01:27:06.984 --> 01:27:11.154
No, you know, well, neither is the democratic party.

01:27:11.164 --> 01:27:12.484
Neither is the democratic party.

01:27:12.505 --> 01:27:12.904
Yeah.

01:27:12.954 --> 01:27:13.225
Right.

01:27:13.385 --> 01:27:14.845
They're, they're dramatically different.

01:27:14.845 --> 01:27:15.944
They just have the same name.

01:27:16.314 --> 01:27:17.465
Do you think there'll be.

01:27:18.185 --> 01:27:24.475
Like further evolution there or I think it's really hard to say what the Democratic Party's like who's it who's the next?

01:27:25.274 --> 01:27:27.555
Stars, you know who the next Barack Obama is.

01:27:27.564 --> 01:27:36.885
Yeah, it's it's really tough to tell me who the next Donald Trump is, too Right, and I think so much depends on if he does a shitty job or a good job, right?

01:27:36.925 --> 01:27:50.904
You know if he does a decently good job He's probably got the, the sway to keep those blue collar, populist kind of voters and, you know, all the Hispanics and a lot of blacks that have come on board with the Trump brain.

01:27:51.005 --> 01:27:51.404
Yeah.

01:27:51.585 --> 01:27:52.654
So that's really interesting.

01:27:52.755 --> 01:27:53.005
Yeah.

01:27:53.005 --> 01:28:03.095
And I think it, a lot of it comes down to, you know, you know, people, what people heard during, during the, the lead up to the, to the election and how they internalize that.

01:28:03.335 --> 01:28:03.614
Yeah.

01:28:03.664 --> 01:28:07.265
Some of it may, you know, maybe spin, some of it may be.

01:28:08.305 --> 01:28:16.505
According to both parties, like if their party didn't win, this might be the last election, you know, so that was the drama was over the top.

01:28:16.524 --> 01:28:17.425
It was over the top.

01:28:17.465 --> 01:28:21.944
And I, I tend to, you know, I tend to be more damp than that, right.

01:28:21.984 --> 01:28:23.625
I don't get too high or too low.

01:28:24.125 --> 01:28:28.015
Um, you know, I do think we're fundamentally structured to do the right thing.

01:28:28.645 --> 01:28:42.680
And, you know, I think, you know, I, I, I study a lot of history and I view, you know, there's been times in, in the past in America where, you know, The world's going to fall apart if things don't change in this election or that election.

01:28:42.680 --> 01:28:48.470
And I, you know, I fundamentally think, you know, America will eventually do the right thing.

01:28:48.529 --> 01:28:55.659
But I do think, I do hope that we can start talking about the facts and not opinions and spins on the facts.

01:28:55.699 --> 01:28:56.010
Mm.

01:28:56.199 --> 01:28:56.579
Yeah.

01:28:56.930 --> 01:29:01.470
Well, yeah, and that's been an interesting, you know, the What are the facts?

01:29:01.510 --> 01:29:10.590
You know, we literally had a ministry of truth or a misinformation bureau or something like that set up for briefly in 2022 or 2021 or something like that, right?

01:29:10.939 --> 01:29:16.140
You know, that's a dangerous place to me if, if, uh, somebody becomes the decider, right?

01:29:16.260 --> 01:29:16.609
Exactly.

01:29:16.630 --> 01:29:17.310
What's true.

01:29:17.369 --> 01:29:18.310
Right, right.

01:29:18.649 --> 01:29:19.340
So, yeah.

01:29:19.449 --> 01:29:23.199
Um, anything else in the political realm you'd like to make sure you get your chip in?

01:29:23.199 --> 01:29:24.750
You're not really that interested in that.

01:29:25.034 --> 01:29:26.484
No, I'm not affiliated.

01:29:26.484 --> 01:29:27.755
I just want to do the right thing.

01:29:27.765 --> 01:29:28.335
Yeah, fair.

01:29:28.755 --> 01:29:31.755
Um, did you think about what your loco experience was going to be?

01:29:32.725 --> 01:29:33.545
Before coming to this?

01:29:33.635 --> 01:29:38.744
Yeah, this is the, uh, the craziest experience of your lifetime that you're willing to share with our listeners.

01:29:38.824 --> 01:29:40.255
The craziest experience?

01:29:40.255 --> 01:29:41.784
The namesake of our podcast.

01:29:42.284 --> 01:29:44.515
Well, I've done a lot of crazy stuff.

01:29:44.765 --> 01:29:50.045
Um, but one thing that might be acceptable to your podcast.

01:29:50.045 --> 01:29:50.510
Okay.

01:29:51.300 --> 01:29:54.390
Believe it or not, this is the strangest fact about me.

01:29:54.409 --> 01:29:54.789
All right.

01:29:55.500 --> 01:30:03.699
I was the foreman of the jury in the Taylor Swift trial for the DJ in Denver who grabbed her ass during a photo shoot.

01:30:03.760 --> 01:30:04.739
Oh, really?

01:30:04.739 --> 01:30:09.010
I like it.

01:30:09.430 --> 01:30:10.500
Tell me, tell me more.

01:30:10.500 --> 01:30:13.890
So it was a federal, it was a federal.

01:30:14.079 --> 01:30:15.109
Tell me about the case a little bit.

01:30:15.119 --> 01:30:18.760
Because some people, I remember it vaguely, but uh, yeah, give me the bones of the.

01:30:18.840 --> 01:30:19.229
Yeah.

01:30:19.229 --> 01:30:20.399
So, um.

01:30:20.930 --> 01:30:25.550
It was, she was in her early, mid twenties, I guess, at the time.

01:30:26.090 --> 01:30:31.770
Um, she was doing a photo shoot for a meet and greet in Denver for a concert.

01:30:31.800 --> 01:30:32.149
Okay.

01:30:32.529 --> 01:30:33.670
A DJ was there.

01:30:34.029 --> 01:30:34.399
Okay.

01:30:34.630 --> 01:30:43.204
And he, after she did the meet and greet and a bunch of photos, um, he, Wanted to take a picture with her.

01:30:43.494 --> 01:30:59.284
Okay, and Allegedly he grabbed her ass During the photo and they took a picture of it Yeah, okay, so he sued her for using her celebrity Influence.

01:30:59.335 --> 01:31:02.095
Oh to get him fired from the radio station.

01:31:02.095 --> 01:31:04.645
Oh damn, so he sued her for three million dollars.

01:31:04.654 --> 01:31:10.835
Okay She countersued him for a dollar, um, with sexual, for sexual assault.

01:31:10.925 --> 01:31:11.414
Okay.

01:31:11.984 --> 01:31:13.265
And so that was what the trial was.

01:31:13.284 --> 01:31:13.984
Yeah, yeah.

01:31:14.095 --> 01:31:16.914
And so, we had to, it was a week long trial.

01:31:16.914 --> 01:31:19.725
To prove beyond a reasonable doubt that he actually did grab ass.

01:31:19.784 --> 01:31:23.675
No, we just had to prove, it, it had nothing to do with that.

01:31:23.715 --> 01:31:24.725
That's what was so funny.

01:31:24.765 --> 01:31:25.145
Okay.

01:31:25.944 --> 01:31:29.534
We had to decide whether she used her celebrity Mmm.

01:31:30.260 --> 01:31:32.539
Influence to get him fired from the radio station.

01:31:32.550 --> 01:31:33.039
Right.

01:31:33.630 --> 01:31:34.630
And probably not.

01:31:35.199 --> 01:31:35.449
Right.

01:31:35.510 --> 01:31:45.199
It probably, because she, she just, all she had to do was say, Hey, DJ Josh Dumbhead grabbed my ass and the station owners were like, Bye DJ Josh Dumbhead.

01:31:45.210 --> 01:31:47.439
But it was even, it was even simpler than that.

01:31:47.449 --> 01:31:48.630
She told her manager.

01:31:49.420 --> 01:31:59.489
So her management machine, her management machine told the radio station, they had all the, everything documented what they told the radio station, the radio station fired him.

01:31:59.619 --> 01:31:59.960
Right.

01:32:00.550 --> 01:32:01.310
There was a simple case.

01:32:01.350 --> 01:32:01.729
Right.

01:32:02.699 --> 01:32:08.100
And so, was it simple in managing through it as a jury foreman though?

01:32:08.180 --> 01:32:12.550
It was difficult in that the, the jury instructions were pretty complex.

01:32:12.609 --> 01:32:20.189
We, we deliberated for four hours, but three and a half hours just trying to figure out exactly what we were supposed to be deciding.

01:32:20.595 --> 01:32:22.135
And what the elements of it were.

01:32:22.835 --> 01:32:26.824
And so once we figured that out, then we're like, okay, what do you get?

01:32:26.864 --> 01:32:28.435
You know, let's take a vote.

01:32:28.465 --> 01:32:32.295
And he's like, we were like, of course she didn't get him fired.

01:32:33.164 --> 01:32:34.814
And of course he grabbed her ass.

01:32:35.305 --> 01:32:37.885
So he has to pay her a dollar.

01:32:38.704 --> 01:32:39.085
That's cool.

01:32:39.234 --> 01:32:39.885
I appreciate that.

01:32:39.885 --> 01:32:41.465
She only countersued him for a dollar.

01:32:42.385 --> 01:32:45.314
You know, she probably could have tried to make it a lot rougher on him, but, but why?

01:32:45.444 --> 01:32:45.774
Yeah.

01:32:46.265 --> 01:32:49.095
But it was funny, I showed up, I showed up for jury duty, I had no idea.

01:32:49.104 --> 01:32:49.814
Was she there?

01:32:49.954 --> 01:32:50.314
Yeah.

01:32:50.505 --> 01:32:50.765
Yeah.

01:32:51.114 --> 01:32:51.994
She was there every day.

01:32:52.125 --> 01:32:52.545
Oh, crazy.

01:32:52.545 --> 01:32:53.515
Yeah.

01:32:53.515 --> 01:32:55.734
I bet she wouldn't be there every day if the same thing happened now.

01:32:56.095 --> 01:32:56.895
Maybe, I don't know.

01:32:56.895 --> 01:32:58.284
I mean, she was pretty famous then.

01:32:58.324 --> 01:32:58.744
Right.

01:32:58.885 --> 01:32:58.984
Huh.

01:32:59.185 --> 01:32:59.274
Fascinating.

01:32:59.345 --> 01:33:00.614
But, um, yeah.

01:33:00.904 --> 01:33:01.975
So, I show up there.

01:33:01.984 --> 01:33:02.694
Are you a Swifty?

01:33:03.774 --> 01:33:09.505
Actually, I'm not a Swifty, but, um, but I do appreciate what she's done.

01:33:09.515 --> 01:33:09.854
Yeah, yeah.

01:33:09.875 --> 01:33:10.784
You know What a creator.

01:33:10.854 --> 01:33:11.204
Yeah.

01:33:11.725 --> 01:33:15.654
But, you know, I show up for jury duty and there's 200 jurors.

01:33:16.475 --> 01:33:18.145
We had no idea what we're there for.

01:33:18.529 --> 01:33:21.770
And then I get this questionnaire all about Taylor Swift, and I'm like, what the?

01:33:23.380 --> 01:33:24.199
I know nothing.

01:33:25.680 --> 01:33:29.449
Yeah, so that's a trivia fact about me that not very many people know.

01:33:29.460 --> 01:33:32.739
I haven't been nowhere close to that close to Taylor Swift, I'm pretty sure.

01:33:33.319 --> 01:33:34.229
Have you been to her concert?

01:33:34.359 --> 01:33:34.890
I haven't.

01:33:35.000 --> 01:33:35.699
No, not yet.

01:33:36.375 --> 01:33:36.765
No.

01:33:37.164 --> 01:33:39.664
Well, Rick, I really enjoyed this conversation.

01:33:39.784 --> 01:33:46.744
I hope that, uh, you continue to be blessed by and be a blessing to the business community here in Northern Colorado.

01:33:46.744 --> 01:33:47.925
I'm really glad to have you here.

01:33:47.975 --> 01:33:48.395
Yep.

01:33:48.505 --> 01:33:50.194
Um, is this your longtime home?

01:33:50.265 --> 01:33:50.475
Oh, yeah.

01:33:50.505 --> 01:33:51.104
Uh, yeah.

01:33:51.154 --> 01:33:53.484
No, no reason to go back to Buffalo or whatever.

01:33:53.555 --> 01:33:54.095
No, no.

01:33:54.095 --> 01:33:54.375
Cool.

01:33:54.595 --> 01:33:57.034
Well, we're glad to have you and thanks for pouring into our community.

01:33:57.145 --> 01:33:57.425
All right.

01:33:57.425 --> 01:33:57.904
Thanks, man.

01:33:58.045 --> 01:33:58.404
Take care.

01:33:58.524 --> 01:33:58.744
Yep.

01:33:58.835 --> 01:33:59.135
We'll do.