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Feb. 22, 2025

1047: Be on the cutting edge of WHAT'S NEXT (even if you have to reinvent yourself!) w/ Trevor Koverko

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Trevor Koverko's journey from aspiring NHL star to tech entrepreneur is nothing short of inspiring. After a devastating car accident ended his hockey career, Trevor navigated the tumultuous landscape of entrepreneurship to redefine his life's purpose. Listen as he candidly shares the ups and downs of his path, including the trials of a failed startup and the eventual triumph with successful companies like Polymath and Sapien. His story is a testament to resilience, embracing new challenges, and the power of reinvention, reminding us that it's never too late to find a new direction.

The conversation continues with Trevor's insights on creating successful tech businesses through experimentation and adaptation. Discover the importance of a strong team, surrounded by big thinkers, and the role of failure as a stepping stone to success. Trevor emphasizes the critical nature of passion and foundational belief in a company's mission while navigating the ever-evolving business landscape. His experience with Polymath illustrates the delicate balance of timing, luck, and learning from past mistakes, offering valuable lessons for anyone in the startup world.

Finally, we explore the future of AI startups, a field ripe with both opportunities and challenges. Trevor shares how Sapien leverages proprietary data to carve out a competitive edge, drawing parallels between AI's current landscape and the early days of the internet. Engage with Trevor's perspective on achieving product market fit, the significance of AI tools, and the unprecedented potential for innovation in today's rapidly evolving tech scene. Join us for this captivating episode, where the spirit of entrepreneurship and the promise of AI intersect, offering insights that could transform your approach to business and technology.

ABOUT TREVOR 

Trevor Koverko loves investing in, co founding companies with, and hanging out with other founders (especially in Web3). Trevor started out as a pro athlete getting drafted by the NHL's New York Rangers in 2005. A few years later, his career officially ended after a car accident. He was hit by a fully-loaded transport truck, sent to the ICU and diagnosed with a 'catastrophic' brain injury.

With Hockey over he knew he needed a new purpose in life and at the perfect time he discovered entrepreneurship. Since then, he’s founded multiple companies. The first one… failed. The second one… sold. And over the next 12 years, he built startups, including Polymath, which has since raised $75m and done 8-figures in revenue. Most recently he co-founded Sapien, a data marketplace that helps long tail AI models close the performance gap with big tech via a mobile data labeling game.

LINKS & RESOURCES

Chapters

00:00 - From NHL to Tech Entrepreneur

12:18 - Building Successful Tech Businesses Through Experimentation

18:47 - Product Market Fit and AI

24:27 - The Future of AI Startups

35:44 - Entrepreneur Podcast Guest Appreciation

Transcript

WEBVTT

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Hey, what is up?

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Welcome to this episode of the Entrepreneur to Entrepreneur podcast.

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As always, I'm your host, brian LoFermento, and we have got an incredible guest for all of you here today.

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This is someone who has an amazing entrepreneurial story.

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This is someone who, to me, it just sounds like he sees possibilities everywhere and he truly believes in the possibility of technology, entrepreneurship and society and humanity as a whole, and how all of these things are intertwined.

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So let me tell you all about today's guest.

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His name is Trevor Caverco.

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Trevor loves investing in, co-founding companies with and hanging out with other founders, especially in the Web3 space.

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Trevor started out as a pro athlete.

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He got drafted by the NHL's New York Rangers all the way back in 2005.

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But that story doesn't necessarily have a happy ending.

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I can't wait to hear him tell us about this, because a few years later, his career officially ended.

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After a car accident, he was hit by a fully loaded transport truck.

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He was sent to the ICU and diagnosed with a catastrophic brain injury.

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But it's not the end of the story.

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Of course.

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There is a happy ending because, with hockey over, he knew that he needed a new purpose in life and at the perfect time, he discovered entrepreneurship.

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Since then, he's founded multiple companies.

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I'm excited to tell you, because the first one that he did it failed, as a lot of things do.

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But then the second one he sold it and over the next 12 years, he built multiple startups, including Polymath, which has since raised $75 million.

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It's done eight figures in revenue.

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And most recently, he co-founded Sapien, which is a data marketplace that helps long tail AI models close the performance gap with big tech via a mobile data labeling game.

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So if you're thinking to yourself, gosh, this guy sees technology in different ways than the rest of the world, you're absolutely correct, but he also deeply loves entrepreneurship.

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So I'm excited about this one.

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I'm not going to say anything else.

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Let's dive straight into my interview with Trevor Kiverko.

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All right, trevor, I'm so excited that you're here with us today.

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First things first.

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Welcome to the show, thanks for having me.

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I'm really excited to do this.

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Heck.

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Yes, trevor, I'm expecting some stories from you here today, and we're going to kick it off by you taking us beyond the bio.

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Who's, trevor?

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How'd you start doing all these cool things?

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Yeah?

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no, I'm a founder through and through.

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That's kind of to your earlier point.

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I love just being one, I love hanging out with other founders, I just live and breathe it.

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And that was kind of like a pact I made to myself when I was younger, after transitioning from an old career to a new one, that this is kind of the life I chose and this is what I love.

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So since then it's been kind of a full-time journey in this industry and I've loved every minute of it.

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Yeah, I love that, trevor, especially because, just doing the research ahead of our conversation here today, I want you to take me back to the hospital room because obviously you I mean your entire life was geared towards becoming a professional athlete, which you very much succeeded at, and then it took that big turn and I want to hear about that spark, that moment where you found entrepreneurship and what was so appealing to you, because I feel like it's not just the business side.

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It sounds in your story like it was also part of the mindset and the drive to go along with it.

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Yeah, I'm from Canada so that's kind of a rite of passage is to play sports, especially hockey.

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So that was my first career.

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I was kind of in that I guess junior world of like being competitive, and then as you kind of grow up you move into more serious competitive teams.

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Canada does it a little differently than the US.

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There's not a lot of collegiate sports, it's more like private junior clubs and stuff and such.

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And I woke up one morning I was drafted to the New York Rangers in 2005.

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And that was like a big dream of mine and just hanging out with that organization and the quality of people, especially the competitiveness, it's just like such a small margin of error that you really have to be prepared, you really have to be disciplined.

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And looking back, I think that's one of the things I took away from that part of my life is just like how incredibly competitive it is and how if you want to be at the top of your game, you can't really screw around.

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And um, and yeah, it was kind of unfortunate after in my early 20s I was in a pretty bad car accident that um, abruptly kind of ended the career and it forced me to kind of go through a bit of a self-reflection and figure out how to reinvent myself.

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But luckily, because I was, I was young, there was still some time to do that.

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I think there's always time to do that, but for me it was always time to do that.

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But for me it was especially natural because I always, you know, like new challenges and trying new things and I was lucky that the recovery was very positive.

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It was kind of unclear at the diagnosis.

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I was in pretty rough shape.

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I was actually paralyzed on the left side of my body because it was a diffuse brain injury, but kind of concentrated to the right side.

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So it created all these, all these, uh, these handicaps.

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But, um, again, I just got really blessed and lucky to recover well from it and and um, just tried to seize every day from there on in and realizing how, uh, how precious, precious life is.

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Yeah, trevor, you said something right there you interjected on yourself about there's always time, and I really appreciate that insight and especially that attitude, especially because, having seen your career trajectory, obviously a lot of people will point towards your successes, trevor.

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But I love how it's even it's very prominent in your LinkedIn profile.

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You don't hide the fact of my first startup it failed.

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It's right there and you highlight that part of your journey.

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Of course, all of these I got a lot more of that, a lot more of those as well.

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That's just the one I.

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Trevor, talk to us about that then, Because I feel like people overlook that when they look at people's successes.

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Yeah, I think the one thing that was really helpful for me was just kind of moving to Silicon Valley early and, above all else, I think that culture is okay with failure and it's really not a big deal and it takes a lot of the risk away from trying.

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And that's kind of the approach I had early on.

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It was just like I'm trying to do this for the long run and, even though it is tough getting started when you don't have a network and you don't have a lot of experience, if you have that kind of mindset of growth and learning, success is just inevitable.

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So for me it was just embracing that mindset.

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You don't have to be in California to do it.

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I think you should be.

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I recommend a lot of people spend time there, especially in Silicon Valley.

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But just cause, like, the networks are so important and the surface area of luck is so much bigger when you're in an area where there's a lot of like-minded people that are ambitious.

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Um, but yeah, for me, even when I wasn't there, I kind of uh, again made that pact to myself that you know, this is what I'm going to do, this is who I am, and this is a win.

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Lose or draw.

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This is the um, the work I want to do every day.

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Yeah, Speaking of the work that you want to do, obviously, Trevor, so much of your professional career has been within the tech space and a lot of people might think to themselves all right, NHL to the tech world.

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What is that link?

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What was it about the tech space that?

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That's what drew you in.

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Was it something that was an intentional decision of yours, or was it I love how you say the surface area of luck?

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That's such a cool way to phrase it.

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Was it it just your surroundings?

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I'd love to hear why you went in that direction yeah, it wasn't anything fancy, it was I don't know what I want to do next.

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And I actually went back to school briefly and was going down a certain career path that was more traditional and a little more like nine to five and it just it didn't appeal to me at all and it was just kind of like I didn't fit in it.

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Just I think that's a healthy career as well, like I don't.

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I don't look down on on that lifestyle or career choice, but for me I just know it didn't align with my kind of goals and my personality.

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So I know choice sounds like it.

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I'm not gonna.

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I'm not gonna get a real job.

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I gotta go and be an entrepreneur from or be a wantrepreneur, I should say.

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And I was definitely in the wantrepreneur side because you know, I had no idea what that meant and I kind of believed all the TV shows.

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It was like glamorous and it was fun and it was just like instant success and IPOs and stuff like that.

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But it was definitely a reality check because there actually wasn't a lot of crossover from an athletic world to an entrepreneurship world.

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I think I've appreciated more of the lessons I learned as I've gotten older from that first part, but a lot of it is brand new and, like you know, going to the gym every day other than having the discipline, it's not really going to help you build a product that people want and get customers.

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So a lot of it was just a fresh, blank slate of learning a new skill.

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And entrepreneurship, I do believe, is a skill that you can learn.

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It's not something that you're necessarily born with, inherently yes.

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I love that, trevor.

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I love the fact that you called out it's the not so glamorous side.

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When I tell people I have a business podcast, everyone immediately asks me the same question oh, do you like Shark Tank?

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And that's what everyone thinks entrepreneurship is like.

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It's just Shark Tank.

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People pitch, someone says here's a few million dollars, go build it.

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But of course that's not the reality.

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Thinking back, I would imagine I'll contradict one part of what you said, because, being a professional athlete, to me the biggest crossover is facing adversity.

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And obviously you faced it, not just with regards to how your career ended, but also along the way.

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All those tough nights, the nights that you had tryouts, the nights that you were waiting for someone to pick you for a team.

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I'm sure draft night was a very exhilarating time for you and your family.

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So you face that adversity along the way, same adversity as when a business doesn't work out or when a product doesn't work out.

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What's your attitude?

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Take us into those very moments, because that's what ultimately makes or breaks people in this world.

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Yeah, I actually.

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The draft night was kind of funny.

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I actually didn't watch it with my parents or anything, it was the GM just called me.

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I didn't even think I was going to get drafted and then I was like, oh cool, I guess I'm on the path to being a New York Ranger.

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But no, to your point, the thing you brought up adversity I should have said that that is a huge, huge skill to learn is to fail and be okay with it.

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Huge, huge skill to learn is to fail and be okay with it, and to not really care about adversity or to care about it in a positive way is absolutely paramount.

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Another one for me was just the bias for action.

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I think I lacked and I lack present tense a lot of skills that a lot of my peers have, but I would just take action more than anyone.

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I would just go and jump off the cliff and build a plane on the way down, and I think that's, looking back, like I kind of had a bit of imposter syndrome to a lot of other really smart people in Silicon Valley about like really prestigious engineering degrees and deep networks.

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But over time I realized like all that doesn't compare to having a bias when you're getting started and also um a way to deal with adversity.

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You see a lot, of, a lot of kids these days where they, you know, went to a fancy school and they've kind of always succeeded and never failed in their life, and then when they go to their first investor pitch and they get rejected, or they go to recruit their first executive and they they get rejected, they can't really internalize it and fail forward quickly.

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So definitely appreciate your comments there that those skills that partly were learned in the professional sports world did definitely apply.

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Yeah, trevor, I want to go a little bit deeper into a very important point that you just made, which is your bias towards action, because I love that.

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I think it's something that we all need to embrace.

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It's probably something I wish we all learned even more as children about imperfect action.

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It's something that, when I was reading about your VR project that you founded all the way back in 2014, it's within the realm of VR and you, especially, you write it right on your LinkedIn.

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We eventually helped sell a penthouse, despite the product being suboptimal.

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To me, that's something I love, trevor.

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Is that imperfect action?

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You didn't wait for things to be perfect?

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Talk to me about that, because, of course, it goes along with your bias towards action, but it just seems like that's been your mindset along the way.

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As tech changes, you've continued to change and experiment as well.

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Yeah, there's a big lesson there of being.

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There's a famous phrase in Silicon Valley which is if you're proud of your product, it means you launched too late, and it's 100% true.

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If you're in the tech world, it's all about building something quickly, putting something together and then experimenting both new features and also the target market that you're going after.

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And I think that's under the umbrella of a bias for action, which is not just being in a research, a self-imposed research prison for a year before you launch something.

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It's like being fearless, getting it out in front of people, getting ready to get rejected.

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You have to.

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If you're not getting rejected, you're not doing it right.

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And again like back to the Things that I think helped me in the past was just like I'm used to that.

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I'm used to like not making the team and even if you're on the team, not getting the best you know power play, position or not getting the all-star game, like you just kind of get used to failing.

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And then how you respond to that, because no one's going to be very few people are going to be on all those things right away.

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They have to like work their way to that and earn it.

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And I think another point of that is a team focus was how you cannot build this stuff on your own.

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No one can Steve Jobs couldn't, mark Zuckerberg couldn't.

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You need other people that have a common vision to join the team and you can't build a lifestyle business by yourself and I think AI tools are actually making it possible to build relatively big companies by yourself but like having the support of people who are not like you, who are not different skills than you, who are complementary to you is is table stakes.

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If you don't have that mindset of like recruiting a good team and working together, then you're just not going to reach the same heights that you would otherwise.

00:14:07.210 --> 00:14:08.610
Yeah, really well said it's.

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I think it's a Helen Keller quote where she said alone we can go so far, together, we can go so much further.

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And it's absolutely true and it shows and that's why we have that concept of you're the average of the five people you spend the most time with.

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If you're around big thinkers, you're going to start thinking big as well and, trevor, I think that you're living proof of that, which fast forward.

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Let's talk about one of your big success stories, which is fast forward.

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Let's talk about one of your big success stories, which is, of course, polymath.

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You started it in 2017, and obviously, it went on to do very big things and it continues to thrive.

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With that in mind, you can see the contrast, trevor, and I want to hear your vantage point there.

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What's the contrast between companies that make it the success stories that we hear about versus the ones that fizzle out?

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Because I'm going to safely call this out for listeners every single entrepreneur has those failure that fizzle out, because I'm going to safely call this out for listeners Every single entrepreneur has those failure and fizzle out stories as well.

00:14:58.758 --> 00:14:59.538
So, trevor, what's the difference?

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Yeah, there's a lot of differences.

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I think luck is a big one, and what I said earlier, it doesn't mean you just like roll the dice and hope for the best although that's part of it but it's like increasing, I call it your surface area of luck, or a lot of people call it that, which is like A time-based.

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So if you try everything in one month, even if you try a lot of things like, you're not going to have the biggest surface area.

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You've got to try it over a long period of time.

00:15:27.250 --> 00:15:30.880
There's another saying in Silicon Valley it's get rich slowly.

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It's like quickly is not the right mindset, because it takes a long time to build an impactful business.

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But, in terms of some of my failures and successes, I had some early projects where it wasn't a luck problem, it was a methodology problem.

00:15:50.865 --> 00:15:52.006
It was it was doing.

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It was not doing certain things that should have been done, like talking to customers and building and iterating on product really quickly.

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So I kind of think, at the time, you think you're unlucky, but looking back you're like, oh, no wonder that didn't work, so I was doing things all wrong.

00:16:07.859 --> 00:16:18.301
It's true, though, that there's no like right way to do things, but there are a lot of commonalities between how some of the best companies get started and it's important to focus on your stage.

00:16:18.671 --> 00:16:28.889
If you're a pre-product market fit company, you should not be listening to podcasts on how to manage a $100 million business or how to manage a go public process.

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That's not really relevant to you at the time.

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But to finish the question, like a lot of the projects that did succeed that I did later, I think, were a combination of learnings from the past, failures and doing them not perfectly Like.

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I'm looking back now at those and saying, oh, there's even more mistakes and failures within that.

00:16:49.559 --> 00:17:04.261
But also, just timing is a big one too, and to talk about luck, it's sort of luck, sort of not, but then it's also a timing thing and it's very true that timing does matter.

00:17:04.261 --> 00:17:10.789
You shouldn't overthink it, because you just got to focus on what you're doing and pick an industry and a product that you're passionate about.

00:17:10.789 --> 00:17:33.154
I think that is absolutely non-negotiable, because it is so hard and there's so many twists and turns along the way that if you don't genuinely believe in the industry and the product, it's a problem, although there's a lot of caveats that you should expect to evolve quite a bit, and no companies that are public on the New York Stock Exchange are the exact same thing that they started out with.

00:17:33.154 --> 00:17:35.990
They've all expanded and grown and failed and restarted.

00:17:37.232 --> 00:17:47.281
But yeah, for me, a lot of it was just a mix of some learnings from past failures and then good timing in terms of the right product at the right time.

00:17:48.089 --> 00:17:56.244
Yeah and Trevor, what I also hear and what you just shared with us is a level of strategy and intention, because you called out, know what stage of business you're in.

00:17:56.244 --> 00:18:07.412
Different stages require different focus areas, different decision making, and so I'd love for you to walk us through thinking about Polymath, for example, and obviously what you're working on now in Sapien, thinking about those.

00:18:07.412 --> 00:18:09.232
What are those inflection points?

00:18:09.232 --> 00:18:41.573
So what we focus on in year one of our business and especially if a lot of people who might be pre-revenue or early stages of revenue, where they're're either pre-product market fit, it's a little bit of a buzzword, but it basically means do customers care that you built something at all or not, and post?

00:18:41.712 --> 00:18:46.723
so post-product market fit is like okay, now you've got some revenue, you've got users, you're growing.

00:18:46.723 --> 00:18:52.432
Basically, the definition of product market fit is if you turned off your product, would anyone care?

00:18:52.432 --> 00:18:56.622
And most people, including me for most of my career the answer is no.

00:18:56.622 --> 00:18:59.220
No one would know or care if the product was turned off.

00:18:59.220 --> 00:19:08.673
And so if you don't have that luxury of having a product that people want and people care about, then you should be obsessed with nothing except achieving that.

00:19:08.673 --> 00:19:10.175
And what does that mean?

00:19:10.175 --> 00:19:14.824
It means talking to more of your customers, learning from them, listening to them.

00:19:15.150 --> 00:19:23.810
Do not think you're Steve Jobs and you can just like manifest something into existence that blows up, because that's also a misnomer.

00:19:23.810 --> 00:19:28.895
He actually had a lot of within those magical moments.

00:19:28.895 --> 00:19:37.040
There's a lot of failing that happened before that that you don't see, but but yeah, a lot of it is just like can you achieve that product?

00:19:37.040 --> 00:19:40.635
And if you're doing stuff that doesn't help you get product market fit?

00:19:40.635 --> 00:19:59.550
Like going to conferences, like recruiting advisors, like talking to investors nonstop it's not the right use of your time and what you do with your time is the only thing that you can control in a startup, and so you have to really be judicious about how you spend your time.

00:19:59.671 --> 00:20:03.921
And again, the answer is not really debated anymore.

00:20:03.921 --> 00:20:13.153
The answer is if you're a tech company and you want to be like a venture scale, if you're ambitious and you want to go big, you don't even have to pick a big industry to start.

00:20:13.153 --> 00:20:16.682
In fact, you should pick a really small and narrow niche and own that.

00:20:16.682 --> 00:20:21.020
If you look at any of the biggest companies in the world, like amazon they started with books.

00:20:21.020 --> 00:20:24.217
You talk about apple, anyone they started in one niche.

00:20:24.217 --> 00:20:25.380
They didn't boil the ocean.

00:20:25.380 --> 00:20:30.434
So I think that's that's kind of empowering that you don't need to take over the world in your first year.

00:20:30.434 --> 00:20:38.914
You just have to make a small amount of users and customers extremely happy, make them your champions, and then good things will happen and then you can expand from there.

00:20:39.631 --> 00:20:40.957
Yeah, really well said.

00:20:40.957 --> 00:20:42.195
This is the real stuff, Trevor.

00:20:42.195 --> 00:20:50.221
This is exactly why, when I started this podcast, we proactively seek out amazing guests like you, because this is counter to the advice that we hear Everyone's talking about.

00:20:50.221 --> 00:20:58.401
You know making a hundred thousand dollars a month in your first year in business, and that's what everyone aspires to, but so much of the real world advice is counter to that.

00:20:58.401 --> 00:21:11.490
I think back to business school and all my professors who said you got to have a three, five, 10 year plan and it sounds to me like you focus on those more actionable chunks of time of how can I invest my time today to set myself up for success in the future.

00:21:11.490 --> 00:21:15.721
What does that timeline look like in your head when you sit down for your executive time?

00:21:15.721 --> 00:21:18.135
Are you looking at six months from now?

00:21:18.135 --> 00:21:21.282
You work in a very fast changing industry of AI.

00:21:21.282 --> 00:21:23.132
How far out do you eye?

00:21:25.696 --> 00:21:30.065
Yeah, you're right about the traditional business school advice being.

00:21:30.065 --> 00:21:33.682
You're right about the traditional business school advice being wrong.

00:21:33.682 --> 00:21:34.450
I don't know how else to say it.

00:21:34.450 --> 00:21:43.351
If you want to work at KPMG or something, yes, you need to really be good at writing these big memos and these big business plans and these big, but that's not going to help you.

00:21:43.351 --> 00:21:57.038
If you're an early stage founder, you can't do that, you don't know enough, it's just a waste of time, and so you really need to be focused on breathing something into existence that people want.

00:21:57.038 --> 00:22:10.411
That's why, combinator, I highly recommend everything that comes out of that organization people want.

00:22:10.411 --> 00:22:13.557
So you need to wake up every day and look in the mirror and say am I in the path to building something people want?

00:22:13.557 --> 00:22:15.642
And then, when you say yes, you say well, prove it.

00:22:15.642 --> 00:22:18.414
How can you prove to me that you're building something?

00:22:18.414 --> 00:22:22.953
And this is a question, by the way, that is going to come up over and over again.

00:22:22.953 --> 00:22:24.739
It's going to come up from people you recruit.

00:22:24.739 --> 00:22:29.640
They're not going to want to join a company necessarily that just has no idea how to serve customers.

00:22:29.640 --> 00:22:34.198
They're going to want someone who's on the path to getting to that product market fit.

00:22:34.198 --> 00:22:35.109
Or talk to investors.

00:22:35.109 --> 00:22:37.818
Don't talk to investors before you have product market fit.

00:22:37.849 --> 00:22:42.756
Your life is going to suck, unless you're, like a seven time entrepreneur and you can just raise based on your name.

00:22:42.756 --> 00:22:46.996
And even, like myself, like I'm, I've been doing this for a long time.

00:22:46.996 --> 00:22:52.051
Like I would still tell myself, like use your ingenuity, there, this for a long time.

00:22:52.051 --> 00:22:54.060
Like I would still tell myself, like, use your ingenuity, there's no excuse not to get.

00:22:54.060 --> 00:23:04.115
It's not easy, but there's no excuse not to nowadays, because there's so many tools and the cost of getting users and revenue is so low now that it's just a matter of, hey, you don't have that, why not?

00:23:04.115 --> 00:23:05.903
Like you should be able to get it.

00:23:05.903 --> 00:23:11.003
You have a couple co founders working for just equity and you have a great idea.

00:23:11.003 --> 00:23:17.756
But, like, just start talking to people, getting users, get traction, get the flywheel spinning, and then it's going to make your life a lot easier, especially when it comes to fundraising.

00:23:18.538 --> 00:23:19.642
Yeah, very important.

00:23:19.642 --> 00:23:25.251
It sounds like simplistic advice, but it's that clarity that you're giving to our listeners of what to focus on.

00:23:25.251 --> 00:23:28.055
This is the important stuff that moves businesses forward.

00:23:28.055 --> 00:23:30.838
So, trevor, you bring up tools, and obviously you're right.

00:23:30.838 --> 00:23:39.617
There are more tools than at any other point in history right now, the biggest tool of which you are at the heart of working in this sphere, which is, of course, ai.

00:23:39.617 --> 00:23:41.142
Give us that landscape.

00:23:41.142 --> 00:23:43.596
Everyone's talking about AI in all different sorts of ways.

00:23:43.596 --> 00:23:48.015
Openai stole a lot of the thunder with the release of ChatGPT to bring it into the mainstream.

00:23:48.015 --> 00:23:51.803
But, from your vantage point, where are we right now in AI?

00:23:51.803 --> 00:23:54.940
What's it great at and, most importantly, what's the direction we're going in?

00:23:57.009 --> 00:24:01.000
Yeah, those are really great questions and I wish I was smart enough to know all the answers.

00:24:01.000 --> 00:24:16.772
I think the things I do know is that we're very early for sure, and number one and number two is we're at a paradigm shift, or I should say a platform shift, because these are not unprecedented Like once a decade.

00:24:16.772 --> 00:24:20.362
We have mobile, we have cloud, we have the Internet itself.

00:24:20.362 --> 00:24:27.416
These have all been like inflection points where new platforms have come, and they don't come very often, but this is definitely a new platform.

00:24:27.416 --> 00:24:37.095
A new platform and it's probably the most unclear platform shift in terms of where is the value going to accrue.

00:24:37.095 --> 00:24:46.499
So, if I'm an investor in AI, I have no idea where to invest because I don't know if it's going to be at the base layer, like the chips to invest there.

00:24:46.499 --> 00:24:49.815
That seems like it's already kind of run away a little bit with NVIDIA and stuff.

00:24:49.815 --> 00:24:51.974
Okay, so then do I go on the models?

00:24:51.974 --> 00:24:54.967
Well, good luck investing in a large language model.

00:24:54.967 --> 00:25:03.896
You need like 100 million dollars to train a new one, and it's not clear that any of those models are going to accrue value in and of themselves, to their, to their owners.

00:25:03.896 --> 00:25:06.750
And then, okay, well, what about the application layer.

00:25:06.750 --> 00:25:08.173
It's unclear.

00:25:08.173 --> 00:25:16.659
It's like is it going to be chat gT 4.0 and 5.0 and 6.0 are going to take over all the apps just in one interface?

00:25:16.659 --> 00:25:19.405
Probably not, by the way.

00:25:20.107 --> 00:25:32.784
I think it's going to be a lot like the internet software kind of revolution where verticalization happens, where you have B2B SaaS companies verticalized that start becoming multi-billion dollar companies.

00:25:32.784 --> 00:25:41.761
I predict that's going to happen with AI as well, where you have a lot of these vertical enterprise models starting to that are very fine-tuned for a specific use case, are going to do well.

00:25:41.761 --> 00:25:46.596
But yeah, that's kind of the kind of phase we're at and I'm not trying to discourage anyone.

00:25:46.596 --> 00:25:51.461
In fact, I would say this is the perfect dynamic you want when you start a company.

00:25:51.461 --> 00:25:54.517
It's unclear, it's uncertain, it's the wild west.

00:25:54.517 --> 00:25:56.481
You have a lot of things being sorted out.

00:25:56.521 --> 00:25:59.977
I wouldn't recommend you wait on the sidelines.

00:25:59.977 --> 00:26:02.883
I think you'd look back in 20 years and hit yourself.

00:26:02.883 --> 00:26:06.435
This happened to me when mobile came out.

00:26:06.435 --> 00:26:11.531
I'm old enough to be young enough to remember when that came out and I didn't really do anything.

00:26:11.531 --> 00:26:11.619
I sat on the sidelines.

00:26:11.619 --> 00:26:13.935
I'm like to be young enough to remember when that came out and I didn't really do anything.

00:26:13.935 --> 00:26:26.320
I sat on the sidelines I'm like, oh, I'll just wait, and I didn't really achieve anything in the early mobile wave and now it's a lot harder right, because there's a lot of established mobile apps now that it's a bit tougher to break in.

00:26:26.430 --> 00:26:35.281
So I think we're in that early romantic period for AI and it's actually never been easier to create an AI company.

00:26:35.281 --> 00:26:52.011
The cost of starting a startup has already been falling logarithmically, like insanely over the last decade or two, but with AI it's like a whole different level, like you can pretend that you're a big company with just one person and a heck of a lot of AI tools helping you out.

00:26:52.011 --> 00:26:55.224
So it's just like the perfect, the absolute perfect time.

00:26:55.224 --> 00:27:07.671
If you look at the capital coming in, there's more capital than there is quality projects and there's never been more appetite for young people that don't have experience to get a lot of traction and get a lot of users.

00:27:08.472 --> 00:27:13.542
Yeah, really well said and actually I don't think it's discouraging at all the uncertainty that you just shared with us.

00:27:13.542 --> 00:27:26.618
I think that you opened up a world of possibilities and really important and big questions, so it's really cool to transparently hear the things that you're asking in the marketplace and you're asking of yourself and your businesses and your teams With that in mind.

00:27:26.618 --> 00:27:36.636
Yes, you don't have the answers, trevor, but your actions do show that you have some beliefs as to where the market's going.

00:27:36.636 --> 00:27:37.580
So tell us about what you're doing with Sapien.

00:27:37.580 --> 00:27:38.143
I think it's so interesting.

00:27:38.143 --> 00:27:41.493
I haven't come across many companies in the similar realm of what it is that you're doing, so give us an overview there.

00:27:42.916 --> 00:27:46.913
Yeah, you know I always try to explain AI in three components.

00:27:46.913 --> 00:27:51.006
There's the data, the compute and then the algorithms.

00:27:51.006 --> 00:28:01.615
It's a little more nuanced than that, but those are really the three big pillars of how AI breaks down in an architectural way is the data, the compute and the algorithm.

00:28:01.615 --> 00:28:09.698
So the compute side we all know that that's like you know, turning data centers into models that have been trained.

00:28:09.698 --> 00:28:24.453
There's like a well proven step to do that and it's just a lot of expense, a lot of infrastructure, and it's not clear that that's where the value is going to accrue, or I shouldn't say that it's not clear that that's where the competitive advantage is going to be for a startup.

00:28:24.453 --> 00:28:29.997
So good luck competing with the big data centers, the hyperscalers and NVIDIA at the chip.

00:28:29.997 --> 00:28:31.320
So that's a big point of it.

00:28:31.320 --> 00:28:33.217
The second is algorithms.

00:28:33.217 --> 00:28:41.769
So these are like the transformer paper that came out, that kind of sprang ChatGPT-1 into existence.

00:28:41.769 --> 00:28:50.776
Google made authored that paper, but another startup used it because it was open to commercialize it before anyone.

00:28:50.776 --> 00:28:52.182
So those are the algorithms.

00:28:52.182 --> 00:29:11.902
But the third one is data, and that's to me the most exciting component, because it's pretty obvious to me that there is a competitive advantage for data and if you have a data strategy where you can acquire proprietary data data or you can get access to data that no one else has, that you can have an advantage.

00:29:11.902 --> 00:29:15.023
So Sapien identified that early on.

00:29:15.023 --> 00:29:21.241
We're only about a year old and we've got a lot of work to do still, but we've identified that component of AI.

00:29:21.375 --> 00:29:23.963
I kind of recommend other founders do that as well.

00:29:23.963 --> 00:29:44.272
Where they don't just like pick one giant category, you kind of like zoom in at least two or three times to pick a vertical or a vertical within a vertical, and so if you look at AI data, so there's a lot of existing startups that do this and and there's also a big problem where there's just not enough new data happening.

00:29:44.272 --> 00:29:50.885
To give an example, chatgpt 4.0 was0 is trained on open internet data.

00:29:50.885 --> 00:29:53.017
So are all the major models.

00:29:53.017 --> 00:29:59.788
So, like Gemini and Mistral and Anthropic, they're all trained on open internet data and that seems like a lot like open internet data.

00:29:59.788 --> 00:30:05.166
It's like holy crap, look at all the videos and audio that are freely available on the web and being created every millisecond.

00:30:05.166 --> 00:30:07.962
That seems nauseating how big that is.

00:30:07.962 --> 00:30:09.537
But it turns out it's actually not that big.

00:30:09.537 --> 00:30:19.586
It turns out these data centers and these chips can actually like mine or train on and access all of that data pretty quickly.

00:30:19.705 --> 00:30:20.827
And now we're out of data.

00:30:20.827 --> 00:30:31.981
So we call it in our industry a data wall, where these models are actually not getting better fast enough, not because there's not enough compute, not because there's not enough compute, but because there's not enough new data to train on.

00:30:31.981 --> 00:30:35.147
And so how do we solve that?

00:30:35.147 --> 00:30:36.678
Like, how do we create new data?

00:30:36.678 --> 00:30:49.313
It's actually called frontier data in our industry Like, how do we create a foundry, you know, like these chip foundries that make all these chips, like TMC, like in Taiwan, you have foundries.

00:30:49.313 --> 00:30:58.159
So we actually want to want to create a new data foundry where you can produce new data as well as, as uh, access existing data.

00:30:58.159 --> 00:31:08.586
And so that's kind of how sapien started out was to be like a data foundry, just like these chip foundries that are creating new data, that that we can help other people access and create new data at scale.

00:31:09.587 --> 00:31:18.847
Yeah, gosh, trevor, hearing that backstory, I love the way you walk us through it, because it also reveals your strategic and your visionary mind as to where those market gaps are.

00:31:18.847 --> 00:31:20.654
And you use the word zoom in and zoom out.

00:31:20.654 --> 00:31:33.856
And that's what I love about the way that you think and the way you articulate things is it is that macro and micro view of the marketplace, because, sure, ai has a lot of trends and, as we talked about a little earlier in our conversation, who knows where they're going?

00:31:33.856 --> 00:31:44.439
But on a micro level, you can see some of those needs and even just hearing the way you talk about that, trevor, it made me realize so many people are just pumping out blog posts these days generated by ChatGPT.

00:31:44.439 --> 00:31:53.967
Eventually, chatgpt and other large language models are only going to be learning from the same exact content that it's created that everybody else is regurgitating.

00:31:53.967 --> 00:31:55.940
So super important considerations here.

00:31:55.940 --> 00:31:57.523
That's a good insight.

00:31:57.904 --> 00:32:14.986
Yeah, it's kind of cannibalistic or kind of what we call it, like mad cow disease data, where it's just like this recursive loop of data training on synthetic data, training on on new synthetic data and it's just like a never-ending loop.

00:32:14.986 --> 00:32:23.519
And also what you said earlier about zooming in and zooming out, that caught my attention because, um, that's exactly what you have to do as a founder.

00:32:23.519 --> 00:32:29.655
It's not just like doing a micro macro analysis of the industry, but like running a company like your whole day.

00:32:29.655 --> 00:32:39.076
You're zooming into the absolute most detail of like, what does this button say on the website?

00:32:39.076 --> 00:32:40.981
Or what is this customer ticket?

00:32:40.981 --> 00:32:42.044
How does that get handled?

00:32:42.044 --> 00:32:46.423
All the way up to, like, the big hairy audition, audacious vision that you have for the company.

00:32:46.423 --> 00:32:50.142
So you do have to get really good at the zooming in and zooming out part.

00:32:50.703 --> 00:32:52.590
Yes for sure, gosh Trevor.

00:32:52.590 --> 00:32:54.638
So much food for thought for all of us here today.

00:32:54.638 --> 00:33:02.406
You've dropped a lot of knowledge bombs on us, which is why I'm excited to see how you take this last question, because it's super broad and you can truly take it anywhere.

00:33:02.406 --> 00:33:10.679
And that is what's your one best piece of advice knowing that we're being listened to by entrepreneurs and entrepreneurs at all different stages of their own growth journeys.

00:33:10.679 --> 00:33:13.405
What's that one thing that you'd like to impart on them?

00:33:15.511 --> 00:33:15.775
today.

00:33:15.775 --> 00:33:28.842
Make sure that whatever product you're building, that you or someone on your co-founding team is capable of building a world-class product.

00:33:28.842 --> 00:33:34.318
So what you don't necessarily want to do is outsource everything.

00:33:34.318 --> 00:33:45.577
If you're starting a new startup, like, where you have a bunch of like business people in a room and no one is like capable of like living and breathing the product from a technical level.

00:33:45.577 --> 00:33:49.467
So it doesn't mean you have to be like a PhD in computer science, but like try to recruit.

00:33:49.467 --> 00:33:56.503
If it's either you, that's great, or recruit other people on your team that can be obsessed with the product.

00:33:56.503 --> 00:33:59.298
It's products that are going to help you grow and you have to.

00:33:59.298 --> 00:34:05.199
You can't escape like building a really good, kick-ass product and I've just found in my experience it's a lot.

00:34:05.199 --> 00:34:11.737
It's a lot better to have that done within the core co-founding team than it is to do it outside of it.

00:34:12.579 --> 00:34:14.443
Yeah, really well said.

00:34:14.443 --> 00:34:16.307
Such important considerations.

00:34:16.307 --> 00:34:20.405
Here we go, trevor, also piggybacking off of your sports career.

00:34:20.405 --> 00:34:23.114
The team the team also matters.

00:34:23.114 --> 00:34:35.586
We're so tricked in the world of entrepreneurship to think that one person we can go and do a lot of things, which is true, especially with the tools available to us, but make sure you surround yourselves with all the different pieces of the puzzle to set yourself up for success.

00:34:35.586 --> 00:34:38.036
I so appreciate those real world insights.

00:34:38.036 --> 00:34:50.690
Trevor, I'm excited to follow your journey from here because, beyond just the great work that you do I'll publicly praise you for this is that I love the way you think and I love the way that you fit in with the short term, but also that longer term, more macro vision.

00:34:50.690 --> 00:34:53.217
It's so cool to see the way you navigate these things.

00:34:53.217 --> 00:34:59.081
So for listeners who want to follow along in your journey, see all the great things that Sapien's doing, drop those links on us.

00:34:59.081 --> 00:35:00.465
Where should listeners go from here?

00:35:01.815 --> 00:35:05.041
Yeah, check out gamesapienio.

00:35:05.041 --> 00:35:09.538
So we have a product now where anyone can produce data and you can get paid for it.

00:35:09.538 --> 00:35:14.373
So check out gamesapienio and we have more information on our product there.

00:35:14.373 --> 00:35:19.043
And then just for my stuff, it's just my name on all socials at Trevor Coverco.

00:35:19.704 --> 00:35:21.576
Yes, listeners, you already know the drill.

00:35:21.576 --> 00:35:36.664
We're making it as easy as possible for you to find all of Trevor's links down below in the show notes, wherever it is that you're tuning into today's episode, including to the game that Trevor has launched into the world to be a part of the next wave of creating useful data for AI to continue improving on.

00:35:36.664 --> 00:35:42.063
So, trevor, on behalf of myself and all the listeners worldwide, thanks so much for coming on the show today.

00:35:42.885 --> 00:35:43.487
Appreciate it.

00:35:44.976 --> 00:35:50.561
Hey, it's Brian here, and thanks for tuning in to yet another episode of the entrepreneur to entrepreneur podcast.

00:35:50.561 --> 00:35:54.543
If you haven't checked us out online, there's so much good stuff there.

00:35:54.543 --> 00:36:03.771
Check out the show's website and all the show notes that we talked about in today's episode at the entrepreneur showcom, and I just want to give a shout out to our amazing guests.

00:36:03.771 --> 00:36:12.545
There's a reason why we are ad free and have produced so many incredible episodes five days a week for you, and it's because our guests step up to the plate.

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These are not sponsored episodes.

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These are not infomercials.

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Our guests help us cover the costs of our productions.

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They so deeply believe in the power of getting their message out in front of you, awesome entrepreneurs and entrepreneurs, that they contribute to help us make these productions possible.

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So thank you to not only today's guests, but all of our guests in general, and I just want to invite you check out our website because you can send us a voicemail there.

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We also have live chat.

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If you want to interact directly with me, go to thewantrepreneurshowcom.

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Initiate a live chat.

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It's for real me, and I'm excited because I'll see you, as always every Monday, wednesday, friday, saturday and Sunday here on the Wantrepreneur to Entrepreneur podcast.