250: What Happens When Your Front Desk Quits and No One Can Fill the Role in Your Dental Practice

If a new patient leaves a voicemail and you don't call them back within an hour, it's very hard to get that booking like you probably will. And we have practices on the high end that are getting like 50 plus new patient bookings a month.

Hi, I'm Emmett Scott, and just like you, I've had my ups and downs in the dental industry, but times are changing. The DEO has built a map of how to succeed in one of the most challenging industries to navigate. On this show, we talk to dental industry leaders, solve problems, and get you the answers you need to face these challenging times and thrive. Welcome to DEO Growth Secrets podcast for dental organizations. Now let's get started. Hello everyone and welcome to another episode of DEO Growth Secrets. I'm your fearless host, Emmett Scott and today we're going to have fun with AI and crypto. I've got Dr. Miles Beckett here. He's a former medical doctor turned serial tech entrepreneur with two successful exits. He began his career as a surgery resident before leaving medicine to to co create Lonely Girl 15. We're going to have to talk about that. YouTube's first viral and number one web series after building and selling the pioneering influence digital media company eCal. Is that how you pronounce that doc?

Equal.

Equal. He returned to healthcare as co founder and CEO of SilverSheet and the leading physician credentialing platform acquired by AMN Healthcare. So anyway, so fun to have you here. Now you're the co founder and CEO of Flossy Solving Problems in the Dental Space. It's a conversational AI software company behind Fiona, and it's the industry's first dental AI receptionist. And under your leadership, Flossy is transforming how dental practices, answers, calls, books, patients and run smarter, more profitable operations. So what a cool thought leader. I'm excited to talk AI with you. I'm excited to talk crypto with you as well. But tell us a little bit about this journey. You know, medical doc, I mean, you were thinking about plastic surgery or like, where were you going?

Yeah, so I went to UC Berkeley for undergrad and I was a neuroscience major there. And then I went to medical school at UC San Diego, and then I was in a plastic surgery residency program at Loma Linda. And on the side I had always been really into creative writing, video production. I was a writer and design editor for the humor magazine in college. And then in medical school I made two different short films. And really I went to medicine because like, you know, my parents said, go be a doctor, you know, so So I just finally got to a place where I was like, you know, medicine is not right for me. I, you know, I like surgery and I liked operating, but none of it was. I wasn't very passionate about it. And so I left and started making videos on YouTube and the rest is kind of history.

Wow, you got to tell us about this YouTube thing. Well, I wasn't around when you were doing that or I wasn't watching it. So what was Lonely Girl about?

Yeah, so in like 2006, right after YouTube launched, I kind of got obsessed with YouTube. I was on a variety of different online video platforms and at the time I was making like kind of comedy video podcasts with different comedians here in LA and discovered YouTube and, you know, basically had this sort of, I guess, aha moment where all of the most popular content on YouTube at the time was either stolen content like clips of TV shows or movies or basketball games or whatever, that at the time they had no rights. And it was clearly like they had to somehow deal with that. And then kids, like blogging in their bedroom about their life. I was, I mean, kind of a kid. I was like 26 at the time, but these were like, you know, 15 year olds that were just like complaining about their life. And so the idea was, why don't we create a fake blogger that's blogging on YouTube and talking about their life and their issues. But if you kind of watch the videos, there'll be sort of a story that emerges along the lines of like sort of a Dawson's Creek type thing with a little bit of a sci fi element. So yeah, you could kind of watch these videos and follow this emerging narrative of Bri was the main character. She had a friend named Daniel. You could watch his videos on his channel. And then it sort of evolved and became this whole, like, universe and this sort of international organization that they were running from and this kind of whole story.

Wow. I mean, the creative mind, I just don't have that. It's absolutely amazing. How does all of that lead you? I mean, connect the dots for us to flossy.

So. So that kind of. We got a ton of press. We ended up being the number one channel on YouTube for about two years. We, we ended up producing spinoffs of this show around the world. We raised venture money and we ended up becoming one of the first influencer companies. So we were working with celebrities and running all of their digital. We worked with like Jennifer Lopez, Lauren Conrad, a bunch of like reality TV people. And I really love the creative side of like writing and directing and producing shows. But as it became a bigger organization and I was really just spending all my time arguing with agents and managers and lawyers in Hollywood, I didn't really like that. And we also got an offer to buy, sell the company. And it was kind of a crazy multiple on the revenue that we were doing. We sold to a bigger company that ended up going public. And so, you know, I was like, I'm going to sell. I think this is a good time. And it was nice to make a little money. So that was good. And so I kind of got pulled back into healthcare, started a company called silversheet that initially was a marketplace matching doctors to surgery centers for them to, like, find work. Like, if you're an anesthesiologist, you want to pick up extra shifts. And then that morphed into a SAS platform for medical credentialing. So we basically verified doctors backgrounds and nurses backgrounds and training. We actually did dental as well and sold that company to AMN Healthcare, which is the big staffing firm in the healthcare space. Big public company. Yeah. And then, you know, coming out of that exit was sort of like thinking about new ideas. We had my partner and I was doing bunch of investing. We did some SPVs and tech companies and really, like, kind of went down this rabbit hole in dental. Originally looking to sort of reinvent how people pay for dental care, we built initially with Flossy, a discount network. And in the process of doing that, we just really got to know the dental industry. A lot of the pain points and challenges. And when AI kind of came out in 2023, we. We started using LLMs as part of our company, like solving a lot of our internal pain points around, like marketing to patients and scheduling them. And we built like a diagnostic chatbot on the website to like, kind of as lead gen to get patients matched to dentists. And the biggest pain point that we saw was like, staffing, like, just finding good staff at dental offices. Really challenging, particularly front desk.

What year was this?

Yeah, this was last year. Last year.

Okay. Wow.

Yeah, last year we like. We like kind of sort of, you know, had a moment. We were like, what do we do? Like, where do we want to take this business over the next five years? And the resounding answer was AI. And the pain point that we saw the most frequently was answering the phone, booking new patients, and sort of then a whole host of things that we can talk about in a minute that kind of come out of that. And yeah, we built a proof of concept of Fiona last Fall and decided to literally pivot the whole business into that.

Wow. And as you've gotten into it, where did you see the biggest opportunity as far as that front desk piece? And it sounds like you're solving one problem at a time here. So which one did you take on first and where are you at today?

Yeah, so the very first thing we were trying to solve was scheduling and scheduling over a phone call because most people, the majority of people interact with their dentists by phone. And you know, we saw there was like a practice that was on our discount network in Pennsylvania, in Philadelphia, and they were the top performing practice by volume. Like, we were sending way more than half of our volume in Philly to this one practice, and their front desk person quit and we had to pull them out of the network and turn them off. And it took like two months before they could get someone new. So we basically were like, how do we solve, like, that problem? And so the first version of Fiona really was just like answering the phone, scheduling new patients, rescheduling and canceling appointments, and scheduling new appointments for existing patients and then answering questions about the practice. You could kind of ask any question that you want.

Now, was this like a bot on the website or was this was all.

Yeah, we started with Voice first.

Wow.

Which was, in hindsight, probably the hardest that we could have been. And, and yeah, and so that was the, the, the first thing that we launched. And we basically added. I think we've done kind of a few things with that core product, which is make the, the, the, the voice better and better and better. And there's a whole bunch to unpack there. But like around how it sounds, how it listens and actually hears the patient on the other end, which is its own challenge. The scheduling logic and how she can schedule and the complexity and sophistication with respect to that and then a ton of nuance around. Like she can now schedule three kids all at once and get the match on the calendar. She can create family files and different pms is like, there's a bunch of like, nuance there. And then. Yeah, we've expanded beyond that. So you can now text back and forth with Fiona. You can chat with her on the website. So she's kind of multi channel now at this point.

For those who aren't in the day to day and they just kind of like, it's good or it's bad. You kind of hit on some of these things. But, like, what are the challenges to solve that? I mean, you named one of them, which is like, yeah, I want to schedule my three kids. Right.

Yeah.

I'm assuming different accents and how they pronounce certain words is. Can be really challenging, but getting their name right.

Yeah.

Right in the file and so forth. So, yeah, to talk us through that. And like, what were the early things to solve and what are some of the things now you're tweaking the small knobs on that are still. Because I. Some people like, oh, I tried that AI six months ago. It doesn't work. And it's like, it's a totally different product than 12 months, six months every month. Probably there's an evolution that's happening, right?

Thousand percent. Yeah. And I would say one thing I've been saying in general on podcasts or conferences, whatever, like, Fiona's not perfect. The technology, the voice. Voice is not perfect. I was just at a conference in San Francisco hosted by eleven Labs, which is one piece of the voice stack that we use, which I can talk about in a minute. And that entire conference people on stage are basically saying, look, you know, a lot of things don't work. But we found, like, these use cases where it does work, and it works awesome. And we're getting, like, massive improvements. And to your point, it's also changing so rapidly. Like, we have literally completely scrapped and rebuilt the entire platform three times so far because the technology has changed so much that you basically are like, I just have to rearchitect the entire thing. So, yeah. So to your question, I mean, I think the things in the very beginning and the things that have improved dramatically over the last six months is hearing the patient on the other end and correctly. Hearing them correctly. And in the. In the back end technology, what's really going on there is what they call in the industry speech to text. So it's. There's specific models that different companies have built, and they are specifically tuned to intake human speech and convert it into text. And interestingly, of all the different pieces of the technology stack, that's actually the weakest right now. Across the board, there were two new models that were launched yesterday. Eleven Labs launched a new speech to text model, and another company that we use launched a new speech to text model. But to give you an example, we went from using one product that most of the industry uses called Deepgram, which is good, to now we use three different speech to text models in parallel. And in parallel, as the human is speaking in real time, the speech is being transcribed, and then we have a scoring system. We feed it basically to an AI to determine based on this Other AI. And given the context of the entire conversation, which of these three transcriptions is likely to be the most correct one?

And it's probably something you're uncovering right out of the gate is what most people don't know is these AI products you're buying are built on foundational AI, oftentimes multiple, which actually enhances the capabilities because it's like AI testing, AI testing, AI doing those iterations. It forces a smaller standard of error.

100%. Yeah. And I would, I would venture that I don't think anybody's doing what we're doing on the speech to text side, just as one example, but we use like six models behind the scenes, right? Like there's a. There's these three different. One actually it's seven now there's these three different. Now in the speech to text, there's an entire custom orchestration layer that we've built. We have what's called a multi agentic system, which basically means we have 12 different AIs that are effectively running for different types of tasks and they actually can dynamically use different foundational models depending on which will be best for that use case.

This is also what makes this challenging because, I mean, for those of us who are more like retail consumers and active in AI, you know, one day Grok is crushing it, then Gemini is, then ChatGPT is, and they're leapfrogging on each other, and then Claude's doing X, Y and Z. And so for those trying to build on these building blocks, right, it gets really challenging because you're like, okay, is this one pulling far enough ahead that we actually need to move over to that platform? And then all of a sudden this one jumps all the way up, you know, like, never mind, you know. And I'm guessing that's partly what caused you having to rebuild it three times is reorganizing who's the best in the industry now, right?

100%. Yeah. I mean, we're swapping models like regularly, certainly monthly, sometimes every couple weeks. And you know, it's funny, if you look at the AI industry, especially in the earlier days of when the models were first coming out, and every. Everyone like kind of was making these derogatory comments about application layer AI businesses, being chatgpt rappers, if you've heard the phrase. And I'm like, anybody who's actually built in the space just like laughs because it's. So far, it's like, it's the opposite. Like building an AI application, building a proof of concept. That sounds really good. In a demo is trivial. And I think this is, to your point, one of the things that you've seen where there's a ton of AI receptionists in dental, in like every vertical. And there's some good ones, don't get me wrong. But there's a lot that are actually just like chatgpt wrappers effectively. And it sounds really good. And then when you actually deploy it in production with real humans calling, who have weird accents and talk slowly and pause for like two seconds for no reason in the middle of their birth date, the whole thing fails, Right?

Yeah, that, that's fascinating. So in some ways, to be a rapper is actually the most complex thing to solve for, right?

Beyond, it's way harder than building a SaaS, a traditional, you know, SaaS product.

Like, and the quality of expectations, that's always what's fun for me is like, how quickly we become entitled, right? So it's like the iPhone comes out and all of a sudden we're like, why isn't all enterprise software? I mean, I think rightfully so at this point we should be a little ticked that not all practice management software isn't like, way simpler than it is. But anyway, we, you know, Amazon starts giving us two day deliveries and we're like, why doesn't everything just do two day and, you know, drone delivery? And for AI, I think it's like, well, you already can do this. Why can't you do X, Y and Z?

Right? No, totally. It's funny. I mean, like, and you know, we've leaned into this a bit in that we've personified the AI as Fiona and we have like a character, we've drawn, you know, animated character and stuff. But, like, you know, she's not a person, it's not magic. And like, she can't just like magically do things, you know, but it's, it's fuzzy. Like if you look at. It's both the beauty of these large language models and the challenge. If you look at traditional software, computers are extremely precise, right? They, they only do exactly what you tell it to do. And programming is like the art of like telling a computer precisely what it needs to do. But once you do that, it'll do that exactly the same every time. With the LLMs, they don't. Like, you can send an LLM the exact same prompt and the output will be different every single time. Maybe not totally different, but it will be different every single time. Because behind the scenes, they are large statistical models. And so building on top of them, you're on Like a sandy shifty foundation here. And so it's awesome because they can do these incredibly somewhat emergent things, but it's very hard to build them in a way where you kind of rein them in and keep the output to be consistent. So that's, I think, the constant challenge.

Where is it today? Like, if I'm trying to deploy this, you know, I know some of our members and you know, the benefit of DEO when you have 550 entrepreneurs, 2,000 practices, they're almost like beta testing with each other. Like, hey, hey, I tried this product. Here's what's working. I know some of them have deployed systems and they said, okay, step one, I'm going to move zero to one, meaning I don't answer my phones on Saturdays or the night. I'm going to at least deploy it there because something's better than nothing, right?

Yeah.

And. And then number two, I'm going to have a pickup overflow because I'm clearly not getting to overflow. So something's better than nothing. And I'm going to have some underlying system that I'm already using for my to rate their calls, to rate its calls, and I'm going to see how it does versus my human team. Right. And then eventually it's like, okay, there's areas where this is just better. It's more consistent. I mean, to your point, like, it always shows up on time and it answers the file and does it the same way, you know, doesn't quit, doesn't give you SaaS. So then they start deploying it a little more. And I think as things are getting better, we're seeing the use case and what it's freeing the team up to is to do all the things that AI still can't do. Right. And frankly, the things that are more creative, the more human facing, et cetera. And so, yeah, kind of talk me through deployment and best use cases you're seeing today.

Yeah, I mean, I think, I think some of what you described is really accurate. So, like, you know, people will start with Fiona after hours, nights and weekends as, you know, a voicemail replacement. They'll quickly add daytime overflow also, still as a voicemail replacement. And I would say that's kind of where we're at with the technology right now. We are working with some larger DSOs where I think pretty rapidly, Fiona is going to go to the front of the call rather than kind of the back of the call, and then whatever she can't handle will then get handed off to a call rep. Yeah.

Is there always kind of an option of like, I'm ready for a human?

There is in. If there is a human available. I mean, the. On nights and weekends, no one's available. And so in those cases, we take a message and we have, like, a dashboard where those messages will show up and the human can.

But there's always an option to opt out and be like, I just want to leave a message.

Yeah, yeah, yeah, for sure. Yeah, you can always back into a message. But yeah, so I would say, like, you know, if you compare Fiona to voicemail, which is the way we really talk about her right now, crushes voicemail. Like, there's no comparison. And I'm sure, you know, this having run, you know, successful DSO and running deo, like, if a new patient, we really focus, we can talk about existing patients, but new patients, the ROI is, like, immediately apparent. If a new patient leaves a voicemail and you don't call them back, they say within an hour. I don't know. When we were running a call center, we were like, after 30 seconds, it, like, starts dropping off. Actually, it's very hard to get that booking. Like, you probably will not. And so for the practices that are using Fiona, rather than it just going to voicemail for after hours, nights, weekends, and overflow, it's going to an AI that is actually making the booking for that new patient. And so it's truly just found money. And so every single practice we work with is, I'd say 99.9% are ROI positive. Because even if you get two or three new patient bookings from Fiona, like, she immediately is more than double paying for herself. And we have practices on the high end that are getting like 50 plus new patient bookings a month, where it's

just like the friction points around. This is so much more intense than I ever appreciated. But as soon as I look at my own life and my own decision tree, it becomes very transparent. Like, right now, I've been wanting to set an optometry appointment, and I went on and I almost booked one. And my wife's like, hey, I just went to our church congregation. We have a little chat there, and they're like, this one's really good. The problem is it doesn't have online book. I just have to call them, right? Like, I have to find 10 minutes and get a call. And I have not done that now for weeks because I'm like, freaking, when do I find the time? And I put it on my calendar, then I move it and I call runs over. And, you know, we're going out to dinner tonight. And it was like, so easy. I just booked my reservation and it sent me that text. The emotional relief when someone's like, hey, so are we doing that dinner tonight? Are we already booked, etc. Just knowing it's there, knowing how simple that is. And so I think it's really easy to be like, it's not that big of a deal. If they have to leave a message, we'll just call them back. It's not that big of a deal if they, you know, can't get a hold of us immediately. It's like, it's a big deal.

No, it's a big deal.

Yeah. I have no problem. And I think most of us have gotten to this point, especially now, of like, talking with an AI, doing anything that's making my life as intensely convenient. Because this is the moment at 10pm I was laying in bed and I wanted to make this phone call and, you know, and even if I was going to leave a voicemail, but the fact that you then asked me, well, when do you want to schedule that? All through a. And now I'm putting it on my calendar and I'm done. It's like the one time I had headspace that I could do this. I'm already in love with your practice. I'm already in love with whatever you're doing because I feel like you have reached across the chasm of my limited time and have met me at 10:30 in my bed. Right. And. And got me on your calendar for that Tuesday at 12:30. That I actually have some free time two weeks from now, you know, or whatever it is. So ye.

And we see that. I mean, we send surveys after the calls to patients and they can complete it. We have like, high four CSAT scores. Like, like, really, really good. And lots of, like, subjective quotes from people saying, this is awesome. I'm glad I can just get the task done. Like, it's. It's really. It's been very, very positive. And as I kind of mentioned at the beginning, like, that was kind of our V1. And now, like, you can text with Fiona. So you can initiate and text back and forth. You can actually do.

I put that on, like, my Google map. Yeah, that's the best way to do it.

Yeah. Yeah, we're helping.

That would be the other thing. Like just text me, you know.

Correct. Yeah. So we're adding the. The Fiona number to their business listings and Google and. But also on a call. So on a call, if the patient wants to convert to Text. They can say that. Or if Fiona detects that there's a lot of background noise or it's hard to understand them or whatever, she can actually say. Would you like to convert to text? And it can switch over to text dynamically during the call.

Amazing. There's half the times I want to do that with humans. Like, just text me. I'm running into a meeting. Can you just text me and like, can we take this while I, you know, under the table while I get that?

Yeah, totally.

Right?

Yeah.

It's so powerful. Do you see this moving to outbound? Yeah, yeah, Yep.

I literally right before this podcast, I was reviewing wireframes. So we, we have the back end built. The. The front end needs to be built, but we're going to be live with outbound, like very, very soon. Like 30 days, let's say less.

Do you see that patient facing outbound or like insurance company based patient facing?

So it'll be like outbound text and phone calls for a few different use cases, like missing missed appointments, getting rescheduled appointment reminders. And then like hygiene recall was a big one that we got a lot of requests for, so.

Okay, cool. And then that could eventually move into following up on billing and collections and stuff like that.

Yeah, we do, we do do insurance verific now. We use one of another vendor's API, but that's kind of integrated into the platform also.

Okay, so insurance verifications taken care of?

Yeah, we do that. Yeah.

You know, there's no team member right now who's like, dang it, I wish I was the one sitting on a call for an hour, you know, so these are like easy replacement places. But you see that even going like for the patient portion, they owe 20 bucks and it's like, it's not worth having employees call and take care of that.

Yeah, yeah. Fiona will handle billing. Like the idea we're building out, like sort of the idea of a skills marketplace where Fiona can handle billing, can handle a whole bunch of other use cases. We're also working on kind of a co pilot concept for the front office staff, where in our dashboard you could use effectively like a ChatGPT style AI to help you get tasks done within the PMS via our connections to the PMS. So there's a bunch.

Because you have that connection, you could start asking questions, correct. How are you solving. You know, I saw that, that lawsuit on the, the wiretap piece where it's like you have to disclose that this is every AI is a recorded call because how else do you do the AI? But it just wasn't thought about for some of these companies. How are you guys handling that?

Yeah, we, we disclosed that. So first of all, we actually two things. We did a bunch of testing around whether Fiona should say she's an AI or not. And we found that actually disclosing that she's an AI and also suggesting how people can interact with her drives the highest engagement between the caller and Fiona. So the calls are typically like, hi, this is Fiona with you know, Acme Dental. You. I'm an AI assistant helping Dr. Smith. You can schedule new appointments, reschedule, ask me questions, you know, how can I help you? And so that's the.

If you ever want to go to text, we can do that too.

Correct. Yeah, actually she says that now or. Or now we also do Spanish. So she'll also say, you know, hablo espanol, diga uno or so. Yeah, so she says that too. Yeah. She can also dynamically detect that they're speaking in Spanish and say would you like. In Spanish? Would you like to switch to Spanish? But. Yeah. And then the. But we. We disclose that they're being recorded in states that require it. Some states have a, have a two way disclosure requirement, some don't, but so follow all the rules. I think that the vendor for Heartland or whatever just messed up.

Yeah, yeah, they missed on that. Anything else that people should know as far as they start thinking about this in the future? I mean you hit on a lot of good things and of course I'd love for them to know how to get a hold of you and connect. Want to kind of start demoing and you know, working through the how the use case for them.

Yeah, I mean I think, look, I think a few things. One I would try it like I think trying whether it's us or another product, I think trying these AI, receptionist AI, you know, enablement solutions is a good thing. I think that if you tried before and your experience wasn't so great, I think you should call us because I think we're the best and it's getting literally gets better. Every week we roll updates out and

that goes to everybody who's current use. It's like my Tesla. Right. Everybody gets the download of the.

Oh yeah, right. Oh yeah. I mean we're pushing updates like daily in some cases. I mean it is very. There's a lot going out. Yeah. And people can go to flossy.com flossy.com where they can follow me on X at M. Beckett M B E C K E T T. Perfect.

If we can pivot for a second. One of my favorite topics right now. So you were like early crypto guy.

Yeah, yeah, yeah. Well, I'd love to hear your crypto story first. How'd you get into it? And what.

Yeah, so, you know, I graduated accounting, CFP, first 10 years was all investing. And I walked right into like the dot com world of like that spiking up and then falling apart. And then, you know, even in that there was a Google and an Amazon sitting in there. But so I've always followed investing and kind of taking care of it myself. But. And they've always said like, the best entrepreneurs are investors and the best investors are entrepreneurs. Right? So I think living in both of those worlds is important. I did a little bit in bitcoin because one of our dentists said, hey, Emmett, you really should do this. And I do try to listen. Like, I think dentists like to play in a lot of different spaces. And so I grabbed some, I had a good return. And I'm like, well, that was fun. And I was out. Of course. Now I'm like, I'm an idiot. But at the time I was like, wow, I played that really well, you know, and kind of saw it as, I guess what you'd call a meme coin today, right? Like, it was just. I saw so much dot com go up and down and I was like, man, I got out of that before it fell apart. When Trump came into office just recently, and I, I'd still been following it and I'm like, okay, wait, the whole money monetary policy is falling apart, the printing of money since 2020, and I'm enough into macroeconomics, I started going a little deeper and I was like, how does money actually work? And so forth. If you ever read that book Sapiens, it's fascinating on like our imagination creating money and so forth. And so anyway, then I see, yeah, I see Trump go, hey, this is. I'm going to invest in this. I'm like, well, when the most powerful man in the world says, this is interesting. And then it's like, when's a good entry point. And when the tariffs happened, I was like, this is a fabulous entry. So the one thing I have learned between 9 11, sadly and Covid and the housing market is those are fabulous entry points because everyone freaks out. But the US economy moves on, right? Unless you think it's like the end of the world, which at that point, who cares what I invested in?

Yeah, right.

And so I dropped a bunch in. In April. So I get to again, be a genius for a moment in time and of course had an immediate, really nice return. And then I'm like, wait, once I went deep, I was like, wait, this is like an ongoing thing. And then once I go deep on something, I probably spend two hours a day now in crypto.

Nice.

And so I, I hired a coach from a hedge fund managing and meet with them each week and doing a lot with liquidity pools on Solana right now. And then got my bitcoin going so forth. And I started off with like, if I could just get to one bitcoin per child, then I feel like I passed on like the. Right. So got there and then kind of have moved on to other things at this point. So, yeah, that's. That's where I'm at. And like. Yeah, understanding. I think what I learned from the dot com era is I want to understand the underlying utility.

Sure.

And then that helps me discern very quickly what's like pets.com that's gonna, you know, or beer.com and what's Amazon and Google, you know, and. Yeah, but you started way earlier.

Yeah. I first read about Bitcoin in 2011. There was like a Wired article, I think, and at the time I was like, I think in the throes of like, trying to sell my company or my first business or I don't know, something, and I kind of forgot about it. And then I sold. I sold the company in 2012 and kind of looked back and dug back into bitcoin. I think at that point I read the white paper and read, you know, all the stuff that was out there on online forums at the time. And you know, I am, you know, I wasn't a philosophy major, but I'm very into like, philosophy and like, what's the meaning of the world? I was a neuroscience major because I wanted to figure out, like, what is consciousness? And like, so the, the idea as you were alluding to of like, you know, what even is money is like a very interesting thought experiment and rabbit hole to go down just in general because it is a 100% made up human construct. Right?

Yeah.

Like, you know, if when people come to me and say, well, bitcoin, it's nothing. Like, it's not based on anything. There's no utility or whatever, I'm like, okay, well, like, you know, beyond air and like water and food, what other utility really is there? Like, are your genes, like, why are you paying more for Levi's? I don't know, like, right.

Like, or you just pull out a dollar bill and you're like, tell me what you can do with this other than burn it.

Totally.

Like, yeah.

I mean, we've been off the gold standard since 1971. So, like, you know, it's not tied really to any technically either. So anyway, there's that whole rabbit hole and I got really interested in that. You know, I am a nerd at heart. And so like the, the mathematical challenge or, or, or problem that bitcoin solved. The general's paradox, like, that was very interesting. I had always actually been into cryptography and public key encryption. I, I had already always found kind of pretty fascinating. So, yeah, so I got into it. I, you know, I made some money off sale. My first company. I basically was like day trading Bitcoin through 2013.

Interesting.

And like, you basically could like read

because of the volatility.

Yeah, it's super. It's. It's. Yeah. Which is. Come back to that because it's less volatile now. But it still is volatile. But it was very volatile back then. And you could basically read positive news about bitcoin on some nerdy bitcoin blog. And then you could see that story starting to get picked up by bigger blogs. And if you bought off that early blog coverage, presuming that news propagated up to like Yahoo or like some big techcrunch or some big blogs, the price I basically downloaded at Google Trends and like at the time, the price of bitcoin perfectly correlated to Google trend data. And so I was just trading off that and I did fine.

I don't know, it was so retail oriented, that emotional. It was just emotional roller coaster that you could trade against 100%.

Yeah. And so I like, you know, did. I like, wasn't trading with a lot, but I like doubled or tripled my money, which is good. And then, then I was like looking into a whole arbitrage strategy because you still see this. But it was even more extreme at the time where different exchanges will have different spot prices for bitcoin at any given point in time. And typically that is related to the fees or if it's foreign exchanges, like currency exchange and there really isn't an arbitrage opportunity. But there was a huge arbitrage opportunity with Mount Gox at the time, which was. If you have heard of Mount Gox.

No, I don't know.

Okay. So it was the number one crypto exchange in crypto at the time. It was based in Japan. It seemed very sketchy. And there was tons of rumors that there's probably some like shenanigans going on and it would probably fail. And so probably for that reason there was like a large price spread between Mount Gox and everyone else. And so I was looking into building like an automated arbitration system. But when you kind of modeled it out at any given point in time you would have a huge amount of bitcoin sitting on Mount Gox and it seemed like a counterparty risk that like I was not comfortable with.

And then centralized exchange. You weren't holding it. Yeah, got it.

And I didn't trust them basically. And in 2012 Mount Gox failed and that's what triggered and they like had stolen like a bunch of money got stolen. So it's probably a good call. But yeah, so I got into it. I was looking at starting a bitcoin company. I like went to this early conference in 2013 up in San Jose and then ultimately I was just like, you know what? I don't think, I'm not a finance person, I'm not an engineer. I don't know exactly what I'm bringing to the table. Maybe this is the wrong call, maybe not. Whatever. I was just like, I'm just going to buy a bunch of bitcoin. I'm not going to start a company because I believe in bitcoin. So that's what I did. And you know, long story short, I've been sitting on a bunch of bitcoin and you know, I've congratulated on a little bit, but it's done very well and I now own a bunch of the ETF shares, which I like a lot too. And I'm actually right now I am the most bullish I have ever been about bitcoin specifically from a risk reward standpoint because I still think there's a huge amount of upside. You know, we should be at like a million a coin by 2030ish. But I think much lower risk. Like, but back then, like because of

the volatile, because the ETFs are in it and everything else at this point.

And yeah, because the President is promoting it, because some nation states have bought it, because multiple companies that are publicly listed own lots of it. Like it is already fully entrenched. It is already entrenched within the global financial system. And I think the only remaining risk is still nation state risk. But I think that's largely mitigated at this point.

What about the quantum risk? What do you think about that?

I'm not worried about that. Like I, I know I've, I know all the I know the, I know the tech, I know the actual technological risk. And like I think before any quantum computer is at a point where it could really cause a problem, they will upgrade the encryption protocol which is they already know how to do it. It's just like agreeing and moving. It is the it is just agree. It is the it is. The annoying thing about any decentralized system is that there's a bunch of people that complain and you have to get consensus among the major miners to. To do it. But it'll. It'll happen before it becomes a problem.

Do you have a second favorite crypto?

It's. I'm definitely a bitcoin max maximalist. Like it's for me it's like bitcoin and then like everything else. I mean the other ones that I think are interesting is. Is more based on utility. Like I think Ethereum has really lost its way. But I think for a while like it was very interesting. I think there is still somewhat interesting for NFT use cases and tokens and other things.

Just the overall contractual components.

Yes, correct. The smart contract aspect. Yeah, I think Solana has taken a lot of that thunder at least during the NFT space. But I think Solana is interesting just

because it's transactional piece. I just saw Western Union partnering with Solana which the amount for those who might not be into this. Without going too deep, if you just wanted to do a surface level opportunity. Opportunity. Think about the amount of money that happens within a bank. Like why are they the largest organization? You know, buildings and organization. Think about also how inefficient. Like at 5 o' clock if I wanted to wire you money, I couldn't. Like in today's world again when I talked about all this stuff we're entitled to, I think the more people start wrapping their minds around how poor the current currency Rails are. So you take Western Union. The fact that they even exist is like yellow pages. Like how does this exist? You know? And when I go to transfer between wallets now using any kind of crypto and watching in seconds or worst case bitcoin in a few minutes or whatnot, you're just like, it's still so much better than I can Apple pay someone, but if I need to move that Apple pay into my Wells Fargo, I'm like in seven days. You know, it's like really? So once you start working on these platforms, but then you get into things like liquidity pools where that money exchange component is usually eaten up by a centralized bank and all of a sudden has to be shared with everyone else. The amount of dollars to be made for just parking your money is insane, you know? Yeah.

And stablecoins, I think, are really interesting. They've kind of had their moment this year in the venture world.

I think it'll be huge. I think the Clarity act getting passed, which will probably happen now that government's open, which, by the way, having our treasury secretary say bitcoin didn't close down, why does the government need to close? That was also a very cool statement.

I mean, it's crazy. Yeah, it's, it's, it's, it's very cool. But, yeah, I'm, I'm excited. I, I am a. I guess I am a bit of a sound money person. Like, I, I really, you know, I think. Have you ever seen this website, wtf1971.com?

No.

You want to, like, have your brain kind of blow up, Go there.

Yeah. I love it.

Basically, some of this is just correlation. But like, basically, like every bad thing in our society happened starting in 1971. And I think there's some truth to it. Some of it is just, again, just like correlation, not causation, but like, like money debasement is a real thing. Inflation is obviously a real thing. And I think that when you look at a lot of the problems in our society, I do think it goes back to, like, us being irresponsible fiscally at the national, state and local level through monetary policy and through a currency that you can infinitely inflate. And that leads to, you know, wage stagnation and the haves and have nots and the 1% and home ownership to home prep. Like, all these things go back to that.

So I'll give you one that I think is fascinating that I've fully bought into is obesity.

Oh, interesting. Okay.

And I'll, I'll connect the dots. Yeah. If you debase this, if you debase the money supply and you make everything more expensive, one of the things you can't have is everyone starve because food's gotten so expensive. So what you have to do is you have to change the food guide pyramid and make it about wheat. Not processed food, but wheat, which happens to be all processed food. Then you have to fund processed food as much as you can and big food companies and pharma to be able to offset all the health issues you're creating with that food. Right. If you have sound money, then good organic food actually doesn't get expensive. Right. You actually have the money actually canceled. So for those who get used to 2% inflation. When you go deep on this, we actually should always be in a deflationary environment, somewhere around 5% or more. And so the cost of things should be just falling constantly. So that means the government, at minimum is moving things up at 7% every year. Which if you don't see it in the dollars, you see it in the amount of effort and time and work you're putting in to get the same outcomes. Because at the end of the day is a store of effort. Right. That's how we store our work in there. So anyway, yeah, things like that. When you go down the rabbit hole, you're like the debasement of the dollar. The only thing we all point to is like, look how much my house has gone up. And it's like, actually, your dollar went down.

Your house is not in real time price.

It always has been.

Right, right, Exactly. Yeah, No, I.

That's a fun one for you to chew on as you start going. You're already there. But someone pointed that one out to me as well.

Yeah, that's. I totally see it. And I had it.

That's cool.

Yeah.

Well, Miles, this has been so fun. And again, anyone who wants to reach out on the flossy side, please do so. I appreciate everything you're doing in the space. You know, as I often tell our members, we don't have the time or money to make all the investments that need to happen. But, you know, coming back to tying everything together, that debasement of the dollar has caused employees to have to ask for more money. They have to be able to eat, they have to be able to pay their rent. But the problem is, is that we are in an industry that we can't just raise the price on our side. So you get a squeezing of margins. Well, how do you solve for all this? The best way to solve for it is technology and to have the humans. And I think that in the next five to 10 years, we're going to see the cost of labor continue to move up and not necessarily the reimbursement rate. And so technology is going to be absolutely critical. And the dental practice of the future will be an AI ran practice with dentists, hygienists and others who are absolutely necessary for client facing things, making a ton of money, and a practice that is profitable, but not like what we see today. So, anyway, thank you for everything you're doing. I really appreciate it. Thank you. Yeah. For those who are interested in deo, check out our website at Deodental Group. And until next time, Keep smiling. Thank you for listening to deo's Growth Secrets podcast for dental organizations. Continue the conversation on our Facebook group and meet other dental leaders. Get questions answered and the strategies you need to succeed. Plus, we have some free resources for you right there on the Facebook page. Remember, you're not alone. Let's do this together. Join DEO's Growth Secrets Group on Facebook and Instagram. Until next time, keep smiling.