Key Takeaways

Marty sat down with Luke Thomas, founder of Formable.ai, who argues that AI and Bitcoin together represent a once-in-a-generation shift in how businesses form, operate, and scale. He frames AI as “unbounded leverage,” where startups can achieve outsized results with far fewer resources, while Bitcoin serves as a financial foundation that forces founders to think more carefully about capital allocation. Startups that embrace AI agents as digital co-workers can move faster than incumbents weighed down by tech debt, rigid structures, and resistant employees. Meanwhile, Bitcoin rewires treasury management, creating a new “hurdle rate” for profitable businesses: outperform Bitcoin or risk irrelevance. Luke emphasizes that small businesses have the greatest advantage, since they can adopt AI and Bitcoin without bureaucratic baggage, enabling new models of growth and capital preservation in a chaotic, shifting landscape.

Best Quotes

“We actually want to beat the hurdle rate. We want to beat the Bitcoin appreciation rate. If we don’t, we’re cooked.”

“AI agents are like little digital employees… they can contain a bunch of information about your business and do the job better than a human, because the agent doesn’t forget.”

“Most businesses sprinkle AI on top of old systems. Startups can rebuild from scratch and harness unbounded leverage.”

“Holding even a little Bitcoin on your balance sheet is like hiring a coach, it rewires how you think about building a business.”

“The number one benefit of a Bitcoin treasury isn’t price appreciation, it’s that it makes you a better founder.”

Conclusion

This conversation highlights how AI and Bitcoin together are reshaping the future of business. AI delivers unprecedented productivity through digital co-workers, while Bitcoin disciplines capital allocation and provides a hedge against fiat debasement. Incumbents struggle under old-world structures, but startups that embrace these technologies gain an edge in speed, adaptability, and financial resilience. For Luke, the combination of AI’s unbounded leverage and Bitcoin’s financial foundation marks a paradigm shift: the businesses that adapt will thrive, while those that cling to legacy systems will fade.

Timestamps

0:00 - Intro
0:45 - Luke’s Background
7:11 - Unbounded leverage, AI adoption struggle
13:54 - Osbcura & Bitkey
15:39 - AI evolution retrospective
22:59 - AI agents
30:05 - SLNT & Unchained
31:37 - AI disruption of incumbents
38:41 - Bureaucratic roadblocks
41:59 - AI arms race
51:22 - Product design and UX
55:31 - Building at Formable
1:01:50 - AI-first, decentralization
1:05:50 - Navigating hype
1:12:01 - AI at TFTC
1:20:32 - Bitcoin in the AI strategy
1:29:01 - Adoption timeline for Bitcoin treasuries

Transcript

(00:00) When you're able to store your capital in a better way, are you going to hire that super senior leader that wants a ton of money and may not work out? Or you could just shovel that into Bitcoin. I think that it's going to be a wonderful thing for businesses. We actually want to beat the hurdle rate. We want to beat the Bitcoin appreciation rate. If we don't, we're cooked.
(00:19) These startups that come out of nowhere and it's like, hey, we went from 0 to 100 million in like 8 months. No one's ever seen that before. You don't see a lot of it in the news. You will see more of it. We live in an age where there's kind of this like concept of like unbounded leverage. Your balance sheet is clearly an area where there needs to be some amount of leverage as well.
(00:35) We're only starting to see the beginning in the decade plus I've been in tech. This is easily the biggest shift I've ever seen. Luke, this is uh a great pleasure for me. I've been waiting for this this episode for I think years now. Well, uh I'm definitely excited to be here and uh to all your listeners, I'm sorry.
(01:01) Uh there'll be lots of rants, lots of uh lots of uh unhinged maybe unhinged thoughts. Um but I'm really excited to be here. Well, you've had an open invite to the show for I think at least two years now, and you said you've been saying for two years, when the time's right, and I feel like I have something to say, I will let you know. And that happened a couple weeks ago, and here we are.
(01:25) um thinking of how to start off this episode. I think it's important for the audience to get context. Luke has been uh somebody who's helped me immensely behind the scenes here at TFTC think about thinking about how to position uh the brand and how to increase our SEO. Not only that, how to lean into this AI revolution.
(01:47) And I think just to start off the conversations, get a little history of your career, what you've built, where you've worked, what you're working on now, and what people may may learn if they stick around for the whole episode. Yeah, sure. So, I'll do my best to keep it short. Um, yeah. So, a little bit about me. Um, I grew up in the middle of nowhere in Maine.
(02:10) Uh, up until, uh, when I first went to college, I had always lived on a dirt road. Um, I grew up in a uh small town um in uh in central Maine. It was about 800 people. I think half of the town was on some form of general assistance. Um I was homeschooled growing up. Um I uh attended, yeah, a mixture of homeschooling, private schooling. Um in high school, I ended up getting into web design.
(02:36) Um because I wanted to customize my MySpace profile. I thought it would be cool and maybe uh maybe more girls would talk to me. Um and so uh so that's what I did. I ended up uh basically devoting call it half of day. So I would homeschool for half of the day and then for like the other half of the day I would go to what's called a vocational technical school.
(03:00) Um and uh you know I was in a class with a bunch of kids that wanted to create video games. And I thought web design was cool and I thought maybe there's something there. Little did I know that it would basically influence the rest of my life to date. Um, and so yeah, in high school I kind of learned how to code very uh I wasn't very good at it, but I started creating websites for, you know, small businesses. I ended up um graduating.
(03:24) I I went to school one year in Boston because I thought sports management be would be really fun. Turns out that spending, you know, tens of thousands of dollars a year for fizzed classes probably wasn't the best idea. So I ended up uh uh going to school for marketing and uh paid my way through school.
(03:44) Um kind of did the consulting thing, ended up graduating college uh and wanted to join the startup thing. And so um long story short, my wife and I the second we graduated, we moved um to Boston. I started working in early stage tech companies. I originally joined as an engineer. Um quickly realized I wasn't good at writing code.
(04:03) Uh but I I always viewed uh writing code as a means to an end. For me it was like I loved the uh to grow businesses. And so I ended up uh kind of falling into this uh industry called like growth um which is you know how to think about marketing through a programmatic um lens like a programmer would. And anyway, did that for a few years.
(04:28) Um, you know, learned SEO, learned a bunch of, you know, internet marketing techniques and ended up falling down the product rabbit hole largely because, you know, when you build, uh, when you're building like a startup that is, you know, uh, like a digital product, um, a lot of the growth work, so to speak, that you do ends up actually being product work.
(04:46) It's like how can you create a product where these these like flywheels that help you grow at a low cost. So, you know, for those are who are familiar with like Dropbox, right? It's like people sign up for Dropbox, they get free space. If you want more free space, you share it with a friend. I became very obsessed with that. Um, and ended up doing that for a while.
(05:03) Um, in 2019, I decided to make the plunge, decided to start a remote work um, software company. I saw a bunch of these um, you know, fully distributed companies building their own like internet is the best way of describing it. um Zapier and Stripe and all these kind of well-known uh remote companies had kind of hand rolled their own systems.
(05:26) So I started that and then six months later COVID hit um and so we experienced a lot of growth. Uh I did that for about two years but I ended up shutting the business down because I didn't see a clear path to scaling um on the revenue side in particular. So I ended up joining Zapier for about three years and uh went super deep there on AI and automation. And so yeah, in many ways a culmination of um what you know your listeners will probably hear is like maybe a little bit more of a deeper dive on AI, what it looks like um how it's changing things.
(05:56) Um I also uh left uh about two months ago and I'm I started a new company called Formable. We basically are making it easy for businesses to respond to inbound leads way faster. And so for a lot of businesses, um, you have a contact form on your website. When someone fills it out, they usually have a high level of intent. You want to get back to them as fast as you can.
(06:15) Well, we're building simple and easy to use tools that make it easy for businesses to get back to their c potential customers way faster using AI and automation and a better um data collection or form uh experience. So longterm though, we we want to build kind of a a new school uh marketing automation platform, which is just like making it easy for businesses of all shapes and sizes to um market in a way where you're leveraging AI as much as possible in in new and we'll call it creative ways. We see a big opportunity
(06:47) there and we don't think the people in the space are moving fast enough. So um so that's kind of the spiel. Um I do I I live in the Nashville area. Um, and I have four kids, uh, seven and under. So, you know, life is good. Um, but I think this context is probably useful for whatever else I'm going to say over the next hour or so.
(07:06) So, this that's my story. Um, and uh, yeah. Yeah. Well, like I said, like you've been helping me a lot behind the scenes, particularly as it pertains to how we grow this business. I think over the last year through the conversations we've had, you've made it clear to me that you're you strongly believe that the nature of businesses, how they are started, how they operate, how they scale, and how big their teams get specifically is is about to drastically change. And not only that, on the business side of things, like you believe strongly that Bitcoin is going
(07:42) to play a role in accelerating these businesses as well. Yeah. Yeah. So the way I kind of think about it is the best way I can describe what I think is going on is kind of we live in an age where there's um kind of this like concept of like unbounded leverage right so before there were certain constraints that existed in a business it could be in particular teams in the business um and we're we've entered a phase where you know one person can accomplish a lot more uh with AI in particular um and so I I think like
(08:18) there's this rise, at least how I view it, of um these businesses that understand this reality and they work their way through um their own companies trying to identify these areas of leverage um and then implementing solutions or tools or processes to kind of uh take full advantage of this kind of unbounded leverage idea, right? And so I think actually Bitcoin really fits into this thesis quite a bit, right? Because if you think about it, you know, in my world, you know, if you're an early stage startup, um you you especially if you're venturebacked, you
(08:54) have to go out and you raise money, right? And usually I would say usually it really depends on the strategy, but I would say in general, a business goes out and tries to raise at least 18 months of runway. Um, often times it in in some instances it can be years of runway, right? And so you basically end up having a bunch of fiat sitting in your bank account.
(09:20) And so if you think about this idea of where are the areas where there's leverage, it's like your balance sheet is clearly an area where there needs to be some amount of leverage as well, right? If you're an early stage startup burning, you know, with a burn rate, right? like you're not making as much as you are spending obviously you c you have to be a little bit more we'll call it risk off.
(09:44) Um but for a profitable business in particular I think the the ability to be a bit more risk on here around your balance sheet in particular um uh becomes much more interesting and compelling. But like if you apply that principle of like where can I kind of like tap into this like almost like digital energy as Sailor kind of puts it right.
(10:05) Um, obviously the balance sheet is one area, but I think AI represents its own form of digital energy. Um, and that can be applied in other parts of the business. And so I think like as I survey the nature of um, of where things are going, um, the businesses of the future will kind of understand this reality and we'll look for areas where they can implement this everywhere.
(10:29) I would say to maybe take it a step further, um I actually would argue we're not seeing nearly like we're not seeing that much yet. And I would argue the reason why is because um existing businesses have a lot of we'll call it baggage, right? They have um they made certain hires based on certain assumptions. Um they implemented certain tools based on other assumptions.
(10:56) And so they've created this system um that is that is designed and um aims to function in a particular way given certain assumptions. But with AI, it's literally coming in and it's like really rattling those assumptions, right? So if you're a business, um it could mean that you need to change your pricing and packaging, right? And for a lot of like software companies in particular, um it could represent saying, "Hey, we're going to like literally axe a bunch of revenue to change our business model around to be more futurep proof." Most businesses will not do that. Um it could
(11:35) mean laying off people, right? Um and so I think we're we're only starting to see the beginning of this shift. And I would argue that the tooling and the tech um is far ahead of what is actually in use and in practice at these businesses. And so the constraint is not the tech, it's the existing structures in place.
(12:01) Um and I saw this, you know, firsthand and I see this firsthand where it's like businesses, we want to do things the way we want to do it. You can like sprinkle AI on top of it. Go for it. Have fun. you can have a CEO mandate, but like it doesn't drive the necessary change or the change that will be coming.
(12:21) Um, and so yeah, I think like we're kind of entering an age of where there's unbounded leverage startups when you start from scratch or if you're building a business from scratch, you can start with a green field environment, but the existing business cannot.
(12:38) And so that's why you see a lot of these startups that are like they're shipping code way faster than others. they're moving way faster than others. It's because they're tapping into all that like unbounded leverage where the existing business has the structures in place that just are not uh they're not uh uh set up in that way. I'll give you one more analogy.
(12:59) Um I was uh maybe too young uh to experience this firsthand. I wasn't working in tech but you know there was a season I feel like it was maybe like in the early or middle 2000s where there was this concept of like software moves to the cloud right and so you had these like you know code that was on prem or it was like you know in the confines of the four walls of the business and then like you know Salesforce comes al along is like hey it's like an address book in the cloud whatever the cloud means you know um but like the those old businesses had to make a decision around
(13:32) how serious they were about this new cloud thing, right? And I think the same is true now with existing even software businesses like are we going to like fully embrace this AI thing? And I just think that you're going to see a lot of uh we'll call it a flipping um that takes place over the next few years. Anyway, I digress, but that's kind of like the thesis in a nutshell.
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(15:39) Speaking of digressing, let's regress and do like a retrospective on the last one to two years, the evolution of AI, and let's get more specific. You're talking about this unbounded leverage that it provides, but what has happened since GBT3 launched, like how good have the models got, what specifically are they good at, and how are you and other founders leveraging them to out compete incumbents? And then on the incumbent side of things, let's get into the specifics of what sort of confines them and makes them unable to make the necessary changes to compete.
(16:12) Yeah, sure. So, I'll kind of walk you through my personal uh firsthand experience using AI. So, it's kind of a funny story. Um, back actually at my previous startup, I think it was like I don't know, it was maybe early 2022, late 2021, and I chatted with a fellow founder.
(16:32) He was kind of a bit of a brainiac, and he's like, "You got to go get an invite. Email this guy." And I think it was Greg Brockman, I think one of the co-founders of OpenAI. He's like, "Email him and ask him for access." So, I emailed somebody at OpenAI and they gave me access to um to to I think it was either it was chatbt or it wasn't chatbt, it was GPT 2 or 3 and I started playing around with it and it had a developer experience and I'll I'll just share my screen for a second.
(17:03) We'll come back to this later as well uh because there's some stuff I want to show you guys but it looked something like this. It was a developer first experience and you know once again like nobody ever hired me at least for a long period of time to write code but like I started playing around with it and at the time I was like wow this this is kind of like autocomplete you know it's like autocomplete at the end of the day like AI in in many ways like this is maybe a simplistic um uh way of describing it. But at the end of the day, it's like it it uses math to
(17:43) determine what the next word or set of characters should be. Like that's kind of that's how it works in a nutshell is it's like it makes guesses. It's trained on data. It makes guesses about what the next words or words should be. And so I was like, "Oh, this is pretty Cool.
(18:07) And obviously as you know someone coming from like the content marketing and the SEO background, I'm like I I get my head of marketing who's like an amazing content marketer, right? He he writes blog posts, they rank in Google. Like we got traffic. I think we were doing like, you know, 15,000 signups a month with like a $2,000 a month marketing budget, right? Um and I'm like, you got to start using this to um to basically help scaffold up some blog posts.
(18:32) Um and and so he started using it and we went from like I think it was like $200 a post, right? $200 a post. Like we had, you know, people off in yonderland writing posts and they were okay but they weren't that great, right? And all of a sudden it's like uh this is like $25, $30. And it was like wow that's pretty cool.
(18:50) And so you know I used it ended up shutting you know shutting the business down joined Zapier. Um, and then I think it was maybe like 6 months later, Chat GPT comes out. One of the founders was going down the rabbit hole on AI. It's going down the rabbit hole and uh and all of a sudden it's like, hey, we we need to care about this. This is like a big bang moment in the tech world. Like everybody needs to care about this.
(19:15) And so they pulled this what we uh looking back called a code red, which is kind of just like an internal, you know, we'll call it fire drill. it's like we need to care about this and here's how we're thinking about this. Um, and so immediately, you know, at the time I was a product manager there and I started playing around with it because I knew that it was powerful before, but it was like how am I going to use it now, right? And at the time I would actually say I was a little bit of a skeptic. Um, even though I experienced the power in one particular area, I was like, you
(19:47) know, what is like what is the scope here? like what are we what are we dealing with? Um how useful is it especially with this new launch? And so at the time I kind of had this fun little hobby and I still do where I would like read these old books written in old English and and I just like I I find that there's something cathartic about reading old books outside of the current moment that we're in.
(20:14) And I was like, I bet you it I bet you I could use this to update the text so that I can make sense of what the heck I'm reading right now. And so I ended up doing that. I was like, "Oh, it's it's good, but it's not great." Like, it would maybe make it a few sentences in a paragraph. It would update it and then all of a sudden it just kind of go off the rails.
(20:34) I was like, "Man, that's that's kind of a bummer, but like cool." Well, three months later they launched I think it was like a new model. And so I returned to that problem. Um, and it was like, "Oh, wow. I'm getting like full paragraphs now.
(20:51) " And so I decided to have a friend build me a little tool where I could update like, you know, 20 pages of text at a time. And then I decided, oh, I'll just keep going down the rabbit hole. So I'm learning how to prompt. I'm learning how to use different models. I'm use learning how to kind of adjust things.
(21:08) Like, how can I make it less creative and more uh, you know, based on like that original text with minor updates? And so I just kept going and going going down the rabbit hole and uh and then I ended up I'll just put it up on Amazon. Well, long story short, I think I've sold about 50,000 books in the past 3 years. But um but they I I modernized Old English and uh and then all of a sudden it's like my world is AI.
(21:32) And then at work I uh we we launched a feature that used um that used AI and it just took took right off. It was this basic capability where you could ask questions. Um, you could kind of like embed like this widget on your website and ask questions. Um, and so a business could put a widget on their website.
(21:50) People would ask questions and then they wouldn't have to ping you and ask you like generic questions over and over again. So I'm like I'm way down the rabbit hole now, right? And then it's been one of those things where I just consistently as a result of tinkering um you know just trying things the models have just continue to get better and better.
(22:11) Some models aren't as gamechanging as others. Um, but you just continue to see this improvement being made where before, you know, I could ask a question of a 10-page PDF and now I can ask a question of a 300page PDF and get the right answer, right? Or summarize this short text, sum summarize this long text.
(22:36) Um, and so I'm once again I'm digressing, but as a result of tinkering and kind of building in the space, you're able to kind of monitor things and see the nature of the progression. Um, and so as a founder, gosh, where do I even begin? Maybe I'll walk you through um how Yeah, like where do I even begin? Um, what's the best way of describing what maybe I'll talk about agents for a couple minutes? Sounds good. Um, okay.
(23:09) So, for those who, um, you know, you've probably seen the pieces in the news and all that, like there's this whole kind of idea of like AI agents. What are AI agents? It's like, well, a lot of it's hype, but there is a reality underneath it, and it's basically that um, agents are I view them as almost like literal digital co-workers, right? where you can tell them what to do and they'll do something for you and then they'll give you back a result.
(23:33) So the way I describe this is, you know, if you've ever used chat GPD before, you give it an input, hands- on keyboard, you type in something that the agent goes to work and then it returns um text for you to to take a look at. Well, the chat experience is just one implementation of an agent, right? It takes an input, it does a thing, it gives you back an output, right? And this instance, it does it through a chat experience.
(24:04) Well, um, one of the big things that I I I guess learned, um, is well, that's cool, but when it's initiated by a human, there's only so like you have you basically have to rely on human behavior change to get the result that you're looking for with AI, right? It's like, oh, I need to go to chat.
(24:25) I need to remember to use it. Like, that's actually really difficult. Um, but there's no reason why you couldn't feed these little digital brains information behind the scenes where it does a thing and then it gives you back a result and then you use it further down in some type of workflow. And so Zap year is a workflow automation product. Um, it's been around for 10 years.
(24:49) And what we saw is like people would build these automations, right? When this happens in this tool, I want to do something else in another tool. Well, what we saw people doing was they were saying, "Yeah, I want that to happen, but in the middle, I want to use basically chat GPT to do a thing for me, right? So, oh yeah, when I get an email, I want to summarize the email and then I want to insert that information into another tool.
(25:20) " And so, agents, um, is kind of the the big topic these days for startup founders. Um, and once again, there's a decent amount of hype, but there is a very real reality, and it's that um these these digital employees um kind of do work for you. And so in the old world, when you're building software, you kind of it's like you assemble tools in a toolbox, right? And um and then they give you the toolbox, you pay for the tools in the toolbox, and then they say, "Have fun. we'll see you later. Maybe we'll do a little training with you.
(25:54) Um, but like ultimately it's up to you, the human, to um, pick up the tools and use them. Well, with AI and with agents in particular, um, you can basically almost have this intermediary between you and the tool. So now there's like these little digital employees that can kind of start doing work for you. Um, and so all of a sudden the human labor that I would need to do, whatever I was doing before, I don't have to do as much of it because the agents are doing work.
(26:29) And so all these startups are looking for ways where agents or these little digital employees can basically be plopped into a workflow or injected into a business process. Um uh and so you're just seeing this explosion of startups looking for places where they can just stuff a little digital employee.
(26:58) And so every time though that you know Grock or OpenAI or Anthropic releases a new model, the digital employee gets smarter, right? The digital employee couldn't do a thing before, but now it's like it received uh better training and it's able to do some new things now. And so every time a new thing is released, it gets smarter and smarter. So anyway, um startups I would say in general are looking for ways to use and kind of get these agents to do work to augment human labor to take work off people's plate.
(27:31) So that and the agent is really really good at what it does. It can contain a bunch of information about your business. like it can literally have libraries of content in its brain or in its memory um and it can reference that so that it does the job in many instances better than the human because the agent doesn't forget the agent keeps keeps all this stuff in mind and so anyway it's it's kind of nuts honestly like I've never in the you know decade plus I've been in tech you know there's been some shifts and all this this is easily the biggest shift I've ever seen.
(28:08) And and it's like and we're still really only in the beginning stages. And so if you know as a start like this is part of the reason why I'm I'm working on a new thing is because it's just like I can't sit by and watch this happen. Like I want to build stuff, you know.
(28:25) So anyway, uh I don't know if that's useful, but that's how startups are using AI and what what's happening in the market right now. Yeah. No, I'm thinking of um because you you've heard it startups or even more mature companies uh the there's always like one or two employees that know the code base extremely well and they're like a a keyman risk like if they were to leave they know how everything works and now you can sort of automate that task.
(28:50) You know that risk doesn't isn't as high as it was because you have these agents now that can just memory. I'll give you an example. Um, so you know, we have a codebase. Um, the new product that we're building has a codebase. I don't go in and I don't really know the codebase.
(29:07) Um, I mean, I could like fiddle around to see what's going on and I can roughly read what's going on, but now I can just get the code on my machine point uh cloud code edit. And so yesterday I was playing around and you know in a startup you kind of need to create you know product documentation and help docs so that you know if someone needs to find their way around the product they there's like a little repository or a series of web pages that you can go to to say how do I do this how do I do that right I pointed cloud code at this and said hey look at
(29:37) my codebase and literally write the help docs for me and it did it and it did like five minutes and so it it wrote like 20 super comprehensive help docs and like literally walked people through how to access certain features because it has knowledge of the code.
(30:00) I will tell you there are dedicated people in companies that literally do this all day. It's just like that's just that's just one example. That's just one example. Sup freaks. This rep is brought to you by our good friends at Silent. Silent creates everyday Faraday gear that protects your hardware. We're in Bitcoin. We have a lot of hardware that we need to secure your wallet emits signals that could leave you vulnerable.
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(31:39) shifting this towards the companies that already exist, have these code bases, have these teams and these processes like let's dig into how they're about to get disrupted and how if at all they can reposition themselves to not get blown out of the water, actually survive this. Yeah. Yeah. So, this is uh this is a fun one. Okay. So, I'll kind of walk you through what I'll call the roadblocks or the constraints are.
(32:03) So, the first is we'll we'll maybe start with the people. Um, so I think there's two two pieces. The first is there's a lot of people that are just like, I don't care about AI and I don't care to know and I'm just going to keep collecting my paycheck and um and screw what the CEO says, you know, this mandate. I don't care. Like I I I don't care, right? And so I would say that is the fool.
(32:28) Um that is a foolish approach. Um and so you have, you know, you could have I mean depends on the company, right? But I mean, even in a tech company, you might have 20% of your employee base that thinks that way, right? Because if you just think about it, there's kind of this idea of um these technological adoption curves.
(32:51) You know, there's the uh innovator, the early majority, the late major. Some percentage of your business is the late majority. Like they're at the tail end of adoption. They're not at the cutting edge. Um, and so they are going to not necessarily fight the initiative, but they're definitely not going to look for ways to try to improve and you know they are um in some instances they will um kind of block things and be a naysayer. So that's part one.
(33:26) Part two is um the organization itself is structured in a particular way. Certain people have certain roles and responsibilities and they like that, right? People like having consistency. People don't generally like when their job description gets torn up and they're like, "You're doing something new." So, when it comes to some of these new tools, um there are new tools that because you have these agents and AI doing more of the human labor, um they rightfully notice that this is disruptive to my job.
(33:59) Right? It's kind of like, you know, I see these stories on the internet where, you know, you have these people in like IT or whatever and they're like they're training the replacement that's overseas. It's like it's kind of like that, you know, they they know and they're like, "Something's wrong here.
(34:17) " And so they will fight, right? They'll stonewall things. They will um say, "We don't need this software." They'll they'll once again kind of be a naysayer. And I and like for what it's worth, I I uh I have a certain degree of empathy for that situation, right? But I don't think I don't think uh the answer here is um you know, letting the big tidal wave smack you in the face. Like don't go to the beach and let the big you know tsunami run over you.
(34:46) Like I just don't think that's wise. Um so that's just the people, right? That's just the people. Now we'll talk about the um the tech or the the the um assets that the business has right so in my world in software it's code right the asset is the code in the codebase well for a lot of businesses unless they were started like recently they have a lot of baggage tech debt right and so when someone wrote that code they built it in a particular way based on certain assumptions as I mentioned earlier Um, well, if you if if you want to make a meaningful
(35:28) change and like put AI like deeply into an existing feature, you basically have to rewrite the thing from scratch, right? And you have to build it in a way where like you're throwing out a lot of like you know old code and like you know you're making massive investments and like tech debt is not something that uh that companies generally want to invest in.
(35:55) They like revenue generating features, revenue generating code uh that's written, right? And so it's easy to kick the can, kick the can, kick the can. So that's why if you look at a lot of these software providers, if they've done AI, it's very surface level. It's like, oh, here's a little co-pilot, right? Here's a little co-pilot on the side. You can load it and then you could talk to it and it will answer some questions, but it's kind of useless.
(36:19) But the whole rest of the experience is the same thing. So that gets into maybe part three, design. when you onboard people and when you have been around for a long time, you know, you have a user experience that has been built in a particular way and your customers are used to it and they might be a little bit of a uh I wouldn't say the naysayer, but let's call it the uh the late majority.
(36:47) So if you go in and you start ripping like you just start making huge changes to the user experience, they are going to just moan and complain because their workflow is disrupted once again rightfully so. So it's like wow well to do some type of change like let's just sprinkle a little bit of AI on top of what already exists and that's from a design perspective. Okay, moving on. Pricing and packaging.
(37:12) Um, businesses love to sell um, features, they love to sell seats. Seats is probably my favorite example. Well, if a business, like in the markets that we play in, if a business sells makes a ton of money selling seats and AI comes along and says, "You don't need as many employees.
(37:40) " Um well a like they literally it's kind of it competes with their own business model right and so are you going to cannibalize existing revenue um for the ambiguity of the unknown I don't think they will unless they're backed into a corner. Um and so in general, you know, start uh businesses like to grow and AI is a big enough shift where you kind of have to rethink your your um your your pricing and packaging. You have to shift away from um selling seats.
(38:10) Uh I think you have to shift towards um this concept of agents doing work, right? And how do you bill based on the work and especially if the work is done well, right? Um and so that's a pretty big shift. It's a it's a huge shift. So that's on the pricing and packaging front. Trying to think of what else. I mean, it just works its way through basically every single department in the company.
(38:35) And so when you add it all up, it's like they're mired in the old world. Yeah. And the I think the other thing that we've discussed before too is just like the bureaucratic administrative layer that's been implanted into a lot of these businesses, particularly the larger ones.
(38:54) Oh, I mean I could go on and on about that, but it's like, you know, this whole managerial class concept where you have these people steering the work that don't have any idea what they're doing, you know, at least on the practice.
(39:13) So, like you have an engineer, let's say, who goes deep in AI and they're like trying to explain what the heck this new technology does and the middle manager that's, you know, selling their, you know, RSUs and making plenty of money off the old world is not going to really entertain this unless they're forced to. And so, you just have this the politics is crazy. It's absolutely insane. Um and so you you put all of this stuff together and this is why I say that the the roadblock is is around the existing structures.
(39:44) It the AI the tech itself is way further ahead than how businesses have implemented it. And then you also have this whole kind of um consultant class we'll call it where they come in and like AI is changing the game. um pay us lots of money and we will recommend mediocre things like you know may I mean and and I don't want to like be too facitious here I guess um but like we will make it so you can process your PDFs right they implement in some businesses like this is actually a game changer but they kind of just sprinkle it in oh AI
(40:19) transformation your entire company needs to be on chatbt okay I will take my monthly retainer and I will come back next month and tell you some basic obvious thing that you need to do. And so that's why I think I was reading recently, I think it's like an MIT study or something, 95% of AI uh initiatives fail.
(40:46) It's like it's no wonder why every after the last five minutes of explaining every part of a business that where things could go wrong. It makes it I mean it's like it just makes sense, right? Yeah, it makes total sense. And that that's why like number one, I'm very happy that I met you and we've been having these conversations. Number two, I feel fortunate at TFTC and at 10:31 that we have relatively small teams.
(41:04) TFTC, there's four of us and some contractors. 10:31 there's five of us. And I feel like I've been able to adapt. I mean, not saying that we're on the cutting edge of AI um in terms of implementing it on the business, but we have implemented it to a certain degree. like we're making I think we've got some automation on the back end very simple stuff just to get my head of growth and sort of my my multi-tool guy Ed um give some more time on his plate and then on the front end like the AI generated videos obviously opportunity cost which you were the inspiration for pivoting that from a mobile app to a to a browser
(41:41) extension like we were able to build that in in a month and it's been fun implementing it in this business but like we're not an AI, we're not providing AI products, we're leveraging it to make our media business and our investment platform more efficient in many different ways. And I I guess this gets to the question like it seems pretty obvious to me that there is there seems to be a an arms race in Silicon Valley and in tech more broadly um to figure this out.
(42:12) There's been billions, hundreds of billions, probably over a trillion dollars now at this point that's been thrown at this space. And even though you just described that the advantages for startups are massive, I find it hard to believe that a lot of that capital is not being miso misallocated and people haven't really clued in on what they should build specifically and how this is actually going to change.
(42:38) Yeah, I mean, I I certainly think there's um quite a bit of that. Um, and so I could kind of share some examples that kind of pop, you know, are top of mind. Actually, maybe I'll save it um, for a little bit. Um, so I think the first thing is in many ways I actually understand the rationale for why the money is slloshing around.
(43:00) And I think it's because the people that are pretty invested and are like in the weeds, they kind of understand that like things are going to change in a meaningful way and for all the reasons I mentioned earlier like there will be a meaningful amount of disruption in particular to these existing established businesses.
(43:24) Um, and so I actually I don't know if I I understand the rationale for why investors and venture capitalists are plowing a bunch of money into the space. Um, so you know, I'll give an example. Um, and this is happening I would argue like it seems like just everywhere, right? So you see it in the late stage where you know, uh, OpenAI is valued at some like large amount of money. Um, anthropic is raising.
(43:51) So you have that at the foundation model level and that one feels honestly maybe a little bit I don't know if I'd say riskier but like somebody's got to win and the revenues are scaling in a meaningful way. Profitability maybe a different story um but the revenues are scaling massively um and so it kind of makes its way throughout all stages of um the tech sector. And so I'll give an maybe my favorite example.
(44:16) Um so maybe a little bit of background before I do though. Um these startups that latch on, right? Because there's so many people out there saying, "What is this AI thing? Um how do I use it?" Like I've never seen any time in technology where you could just basically walk up to anybody on the street and you could have like a conversation and they're going to have like questions and thoughts and curiosity around AI.
(44:43) Like I've just I've never seen that before. Like it's it's like it's very top of mind for a lot of people. Like you know I take my kids to the pool down the street and I'm like chatting with a neighbor about it. You know it's like it's just it's everywhere. Um, and so because there's so much attention there, um, you have these startups that come out of nowhere and like scale like super fast.
(45:06) So I think notable examples are like, you know, products like Lovable or Cursor, uh, if you're a developer. Um, there's kind of these stories, right, where it's like, hey, we went from zero to 100 million in annual revenue in like 8 months. And it's like no one's ever seen that before ever. Um and so some of that's maybe because of the fiat debasement.
(45:32) Um but uh but uh you know it people have never seen that before. And so what that means is if you're a venture capitalist that is in the business of identifying you know one out of 10 one out of 20 companies where you think it could be a home run. your your spreadsheets, you can make your spreadsheets make sense if that one business instead of scaling to, you know, 50 million in annual revenue scales to 150 million in the same amount of time, right? So like the spreadsheet math I think actually kind of makes sense. So what they do is you have these
(46:08) bigger funds, you know, like that have a billion dollars that they have to deploy. um they'll still write checks into, you know, the open AIs of the world and that's like, you know, stroke a $100 million check or whatever, but they're also getting involved in the earlier stages, too. And so it creates it kind of reminds me of the co era um I I dare say hysteria um where early stage businesses that had traction like people were ripping massive checks into these. And so like I heard from one of my existing investors that you know a uh a startup that
(46:46) graduated or like this is not a rare occurrence uh but a startup that graduates from like the last uh Y cominator badge which is a big you know really well-known accelerator that fetches a premium for the startups that go through it.
(47:06) It's like she was saying, "Oh yeah, like you know, this individual like uh raised at a $45 million valuation after like three weeks of work, like barely had a product that was raising at like a $45 million valuation. And like I have friends that have raised at 50, 60, and like some of them didn't even have any paid customers. So like there is a level of froth in the market.
(47:29) Um, so what that means is if you're an early stage founder, you kind of need to know like, hey, the model is nine out of 10 of us are going to fail. One out of 10 of us is going to make it work and that will return the fund for the venture capitalist and that's the way that the game is played. And if you don't like it, don't raise VC.
(47:50) Um, but I actually think that the money is in some instances probably not being allocated well. But I understand the rationale. I do. Um, I will say the thing that irks me is and once again I kind of understand this logic as well, but I think it's kind of it's kind of a maybe a slight of hand is you have these startups. I think cursor might be one of them.
(48:15) No, no, you know, not hating on cursor because I think they built a good product, but they basically it's a land grab. So, they're competing with, you know, Cloud Code and Cursor and all these other all these other like code tools. So, what Cursor does is they give away a bunch of credits.
(48:35) So, you sign up and they're like, "Here's $200 in free AI credits to use so that you can get up and running." It's a great idea, right? because people use those credits when they're writing code and and then they learn to like your product and they learn how it works and then they're less likely to go try the other product down the street. Well, what happens is, you know, maybe if your cursor, and I don't know the numbers, so I'm just using hypothetical examples, you might be doing a 100 150 million in annual revenue, but you might be spending 50 of that, 75 of it on
(49:06) literally your open AI bill, right? So, in the old world, software margins might have been like 80% 90%. in the new world in land grab mode you might actually have a negative like a negative your margin like you may actually be losing money.
(49:28) Um and so you know in the old world they would still kind of do this with sales and marketing and other things but I've never seen I've never seen this maneuver that I'm seeing now where you're basically just paying the anthropics and the open AIs of the world this monster bill, right? And that's topline revenue, but you're but you're paying massive costs coming in the front door going right out the back door. Yeah.
(49:51) So everybody goes, "Oh my gosh, they're they're killing it. My startup is not nearly like and yeah, sure, maybe your startup isn't actually that successful." Sure. But like what they're doing is they're kind of more like a 50 million AR business, not a 100 million AR business. Um when when you think about it. Um but you know, topline's topline. So I I get it.
(50:11) Once again, I understand why they're doing it. It's a competitive space, but these are some of the shenanigans that um are currently um happening in the market. Um yeah, on the topic of hysteria is crazy how quickly people develop amnesia like both on the investor side, but on the founder side too because like raising at insane valuations puts a lot of pressure on you and sort of handcuffs you in the future if you don't get the traction that was expected of you.
(50:38) Yeah. And and I think a lot of founders will basically um you know a lot of founders look at it and say you know when I when I take a VC check this is the path that I am signing up for right um some decide you know maybe part of the way through you know if they don't have the revenue and the traction it's like switch to profitability um you know make the business profitable you know it's not going to grow as fast um it's not going to return the fund like the like the VCs want, but it is um but you still at the end of the day have a business that employs people and you're still delivering our product into the world, you know. Um so, which is, you
(51:17) know, no shame on that, but but when you get on the treadmill, you need to know you're getting on the treadmill. Yeah. I mean, on that topic of bringing a product to the world, how what effect is AI going to have on what products look like moving forward? Like to my point earlier, like not only does it seem like VCs are in this arms race and pouring a bunch of capital and a lot of that's being misallocated just because of just nature of spray and prey.
(51:46) But then on the execution of the startups like do you like how many startups out there do you think have like the right idea of how to implement AI and bring AI products with new UX, new UI to market? Does that make sense? Yeah, definitely. So um this is a really good question. I think maybe the I think all of us are honestly figuring it out as we go.
(52:17) There are certain patterns that um that have been we'll call it proven in some ways to work right. So like you know this idea of AI um being a chat-like experience it's like for certain jobs to be done right for certain use cases that's a great that's a great way of interacting with AI.
(52:39) I think we're going to see a lot of different approaches in the future and I actually think a meaningful feels like almost 50% of the innovation is actually on design and so you know a startup when they hire like a product designer someone who helps build out the UX like I mean we just went through um a hiring process and we brought on a product designer a few weeks ago she's amazing Um, but like there's a lot of people that have an old world like view and they haven't spent time playing around with products. They haven't spent time like learning AI for themselves. To be able to kind of
(53:18) understand like at the end of the day I'm like building a user experience that sits on top of this core piece of technology that like has certain things that it needs to function. um a lot of uh designers in particular just haven't spent the time. Um but the ones that do I think will really kind of pave some interesting paths.
(53:41) And so I think the the thing that I and I'll kind of maybe like present a like a highlevel uh way of thinking about this, but I mentioned earlier that these agents are kind of like little digital employees. Well, if that is true, right, or even remotely close to true, um the user experience may actually need to end up feeling a bit more like you are working with like a co-orker, right? Um maybe these agents, this sounds so cheesy and I can't believe I'm saying it, but like maybe these little agents need to have little cheesy names, right? Maybe you need to be able to like
(54:19) tag that the name of that agent like you tag them when you're like, you know, using Slack or Microsoft Teams, right? Um, and so, you know, and and like how do these agents or little employees interact with each other? Like when do they hand off data from one thing to the next? like let's make sure that this agent has enough information in its digital brain and like if one agent has different information and another agent has another set of information and they aren't sharing well then you run into these issues and
(54:53) then there's also this concept of like oh maybe an agent like maybe there's a boss agent too right that kind of like is scanning right and it's like are these things working. Like maybe you need like little one-on- ones with your with your little with your little employees like, "Oh, let's check in, see how they're doing.
(55:18) " So anyway, the reason why I bring this up is because that's kind of like those are almost like Lego building blocks, right? But there's like these user experiences on top of that that will need to be built. I just I'm like, it's going to look different. And so that's why to get back to the original comment that I made, um I think we're all just trying to figure this out. Mhm.
(55:36) What have you seen that's been Have you seen like a Oh, these guys are doing it right. This makes sense. UX. Yeah. You know, I think some of my favorite tools that I like playing around with are, you know, uh Replet. Replet's pretty great. I'm a big fan of Replet. Um I like, uh Vzero, which is another similar tool.
(56:03) Um, I've been really having quite a bit of fun with Claude Code, but that's more for like a developer like experience because it kind of sits in your terminal. Um, honestly, I feel like the the number of products that do it poorly is significantly higher than the ones that do it well. Um, I'm trying to think of just there's this one product that I that I used for a little bit.
(56:25) It was called Howy and it was almost like this little meeting assistant, but it would interact only through email. Right. So, it was almost like Calendarly if you've ever used that before, but it was like there was no user interface. Right. So, I think we'll see more of that. But honestly, like I I I'm constantly trying new tools just because I I feel like once again, we're all trying to figure this out. Yeah.
(56:48) What um how do you approach UXUI formable? I think we we definitely lean on uh the concept of so there's a few things that we that we talk a lot about. One is this concept of like a primitive or it's like a building block, right? And so in the world of we'll call it marketing.
(57:07) Um like if you're trying to collect leads and get back to them, right? Uh you may have a form and that's like a primitive. Um you may uh need to send an email, that's another primitive. Um, and so there these like Lego building blocks, so to speak, that you need to construct together.
(57:25) And I'm of the opinion that all of those primitives, there's an old world primitive and then there's a new world primitive. The new world primitive is like they're still probably called the same thing, but they are actually an agent. So like the product that we're working on, um, the initial product, it's it's a it literally looks like a multi-step form.
(57:44) like if you've ever used type form before. And so you you fill it out almost like you're filling out a form, but it's actually an agent behind the scenes. And so because it's an agent, it it is literally as you're filling it out, it's like it's kind of reasoning on the fly about what should we do, right? So someone enters their email, we're like, "Hey, uh we can enrich that information, right? So we can figure out a little bit more about you. Um you fill it out, maybe we show you questions and we don't show you other questions." And then at
(58:12) the end um we can actually have like another agent that goes is there anything else that we need to ask. It's like oh yeah there might actually be because you have gave us this job that we need to do. So at the end it might ask you a couple final follow-up optional questions.
(58:33) So as a result of your business you're able to collect this really rich information and then you can feed that really rich information into like your follow-up email. So, your follow-up email is way more personalized because you were able to collect this like amount of information that helps you deliver a super personalized email. And so, we talk a lot about these primitives.
(58:49) To get back to my point, um, and these primitives are actually kind of like agents. So, instead of trying to convince the world that you should be using agents, we're like, no, no, no, there's an existing pattern. There's forms, there's emails, there's these things, and we're just we're infusing them with AI um and rebuilding them as an agent first.
(59:07) So you don't you still think about your world through this lens of these existing Lego building blocks that you're used to. So that kind of constructs things. Um but then you have this kind of coordination that needs to happen like this intelligence layer above those primitives where maybe you have a world where in the future I can describe like the funnel that I'm trying to build.
(59:31) Hey, I like I want to collect leads and I want to, you know, get back to them really quickly and then I want to enroll them in like a, you know, some type of like drip sequence where they get an email like 3 days later and 5 days later. And um and an agent should be able to construct those different primitives or building blocks, put them all together, connect them all, and you don't have to do it yourself.
(59:49) Even better, um, there can be another agent or another piece of your code, we'll call it, that has knowledge about your business. Maybe it's scraped your website. Um, and it understands your pricing and packaging. It understands a ton of voice that you're trying to use. It understands these things about your business.
(1:00:08) And it literally gives that information to every single one of those little agents. So, all of a sudden, your emails are smarter because it knows about your business. your forms are smarter because it knows about the job that you're trying to do, but also it knows about your business. Um, and so there's this intelligence layer on top of these primitives that we believe will, you know, be really transformational when it comes to assembling the Lego building blocks.
(1:00:34) And then there's almost like another level where you'll have another thing that sits above it and it will analyze everything. It'll analyze your entire marketing funnel and go, "Hey, there's drop off rates here. there's drop off rates here. You're not converting as well as you could be. Uh would you like us to make some changes? Like heck yeah, of course. Click. Right. It applies the change.
(1:00:54) I don't need to go in and click 18 buttons over and over again. Um and so it's like I honestly don't know exactly what the user experience for that looks like, but I feel like I have at least, you know, maybe I'm being foolish, but I feel like I kind of have an idea about what the world will look like in the future.
(1:01:13) And it's it's instead of humans being like the first thing that you plug in to solve a problem, it's going to be these little digital employees. Um unless you need that extra uh unless the variance in the task is, you know, too high and um and uh you know uh and and sometimes you'll send a person in to learn more about it so that you can then build an agent to put it in there instead. Yeah.
(1:01:36) So it's almost like people are people are gap filling the work of the agents instead of agents gap filling the work of the humans. Mhm. Right. But right now people are it's like human plus agent or human plus AI. And I'm like no no no it's AI plus human. Yeah. No. This got me thinking I just like think about how I could use this at TFTC. Just one just thinking of a meeting I had earlier this morning.
(1:02:05) One of our goals is newsletter has been word of mouth. Haven't really spent any time like focusing on building that funnel and pushing people towards that. We've put a little bit more effort into it in recent months with like an a read at the end of a of a podcast or whatever. But like we can make the newsletter experience number one much bigger by actually trying to grow it.
(1:02:30) And then number two much more hopefully insightful by if we had a forum where people were getting onboarded to sign up for the newsletter like what interests you most about Bitcoin? What topics do you are are you most interested if you've been reading like what topics that we cover um make you the happiest? I'm just thinking of examples here like that's something if we could use your tool to implement that I don't have to hire a marketing expert per se to build these funnels like Formable could do it for for us. And as I'm thinking through that it's like okay me
(1:03:01) as a business owner that really empowers me and allows me to do things for cheaper and hopefully increase our audience and ultimately revenues here at the media business. And I like to think I have agency and we're trying to lean into these tools so it'll be good for our business. And the the broader question I'm getting at is like is this AI revolution truly a 10,000 flowers will bloom situation or you going to have like a crazy not even paro but crazy distribution of companies that exist and succeed versus those that simply don't exist. And what's the
(1:03:37) nature of working going to be like? I think my short answer is it's almost like chaos is a ladder. We would we would sometimes my co-founder and I would say this a decent amount. You know, chaos is a ladder. It's an opportunity, right? I think there's the first part which is chaos. And I'm like, yeah, that's that's that's going to happen.
(1:03:58) Like, you know, you see it in every other part of our our world, right? just like total nonsensical. Uh like you read the news and you're just like I can't believe like I if it was like you know maybe a few years ago I never would have believed it but now it's like ah this is normal this is this is pure chaos.
(1:04:22) Um and uh and so I think that in some ways it will apply here as well, right? And so you know but but with that chaos there is opportunity. Um and I think I am of the opinion and I try to be an optimist. Um, you know, I try to be realistic about the situation at hand, but I I tend to, you know, envision a a bright and interesting future. I think I just like to follow um I love to tinker.
(1:04:52) I love to try things. I love to learn new things. And so, um I think yeah, being an optimist is kind of part of that job, right? Um but to but also um there is a reality that like things are going to look very different. Um, and I don't necessarily think that change will happen all at once.
(1:05:19) Um, you know, gradually then suddenly, right? Um, or actually I I think it'll be maybe a little bit more of a gradual change. Um, because you know, those bigger businesses that are sitting on their hands right now, they won't lose all of their revenue overnight, but it'll just kind of go, right? It'll be this like gradual decline. Um, unless you're CHEG and then if you sell, you know, if you do quizzes, online quizzes, you're totally cooked, right? Um, so, uh, so yeah, where am I going with this? Um, so I think like here's what I would encourage you like forever whoever who
(1:05:54) is still listening to my diet tribes. Um, the way that I would encourage you all to think about it is maybe keep two things in mind. one is that these AI companies in particular um are honestly in the business of narrative like they're in the narrative business right and so you know a year and a half ago was like AGI is here right and and it's like that's wonderful if you're going out and trying to raise a mountain of cash right it's like that's a great that's a great idea say AGI is near Um, turns out a Yeah. two weeks until AGI, right? Um, and so on one hand they
(1:06:42) will hype this, right? They will hype it and then there are moments where you actually I feel like you see their true colors where they will like in other areas underell it. So, it's almost like they're kind of uh uh like they they it's almost like I I can't parse these companies because one minute they're saying AGI is near and then the next minute they're like kind of almost like walking that back and it's like why is that right? And I think that there's like two things that are true, right? One is like obviously AI is changing the game. Um I think that AGI is not near unless you're fundraising.
(1:07:18) Um but on the other end there is meaningful disruption that will take place that they are not going to tell you about. Right? And so that organization that maybe had I I mean this is happening in customer support right now for sure. Right? You have these chatbot products that have come out that are way better at answering questions than people because once again they have knowledge about the business and they can hold it in their little digital brains way better than a human can.
(1:07:48) And so as a result, it's like customer support is one of the first things that's just going to be roasted by AI. And we're seeing it like there, but you don't see a lot of it in the news. You will see more of it. Um, and that's like a huge amount of of, you know, there's a lot of people that are employed in customer support.
(1:08:09) Like there are a lot of people that are out in, you know, rural America that work a remote customer support job. Well, you know, maybe there's fewer because of outsourcing, but um but like you know, and and they're, you know, they're working this job and they're for most part, you know, happy with the situation that they're in.
(1:08:28) It's like AI comes in, bang. It's almost like uh uh growing up in Maine, we had these uh mill towns, right? So, you had these paper mills. Um and uh you had these paper mills and um they started outsourcing everything. And my grandfather, he uh he would um haul lumber and he would haul uh uh wood chips um to these paper mills.
(1:08:54) Um and you know, I remember being five, six years old and him complaining about outsourcing happening. Like I would go on trips with him in, you know, his tractor trailer truck. I would be in the back, take naps, and then he would take lumber from Maine, drive it across into Canada. They would process it, he'd bring a load back, and it infuriated him. Right.
(1:09:14) And he and he would constantly talk about it with my dad. Um, and so I think like there's going to be some element of that that happens, but it's going to happen in white collar work, which is like kind of wild to think about. Um, yeah. Yeah. Oh, it's wild to think about because I mean there are I mean I I think an overwhelming majority of people in these white collar jobs are asleep at the wheel when it comes to this stuff.
(1:09:44) I I think they're I don't know if it it's definitely a form of cognitive dissonance where they don't want to believe and especially for white collar workers around our age, millennials who have struggled enough to get to where they are. They I'm we it's pop culture or popular culture right now. It's like the millennial trajectory.
(1:10:03) You go to school, you get a degree, you get a good high school, good college, right? Major, get a degree. And then that hasn't panned out well. And a lot of the people who hasn't panned out as well as they expected are in these white collar jobs already not very happy with their position in life and about to get a double whammy with this.
(1:10:22) I'll give you another example. Um, so, um, there's this guy that I follow on the internet and he basically built, um, I don't know exactly how he built it, but imagine like if AI was in Excel, right? So, imagine all these uh, financial analysts that are really good at writing I don't know, I hate Excel, but like macros, I guess. Yeah. Vlookups.
(1:10:46) Yeah, VLOOKUPs, macros, whatever. Right. It's like he built this tool and it's like the people that are using it are freaking out because it's like the analyst jobs. And so it's not only happening to like you know um the the the low end it's like you know somebody who works in like I don't know Goldman Sachs or whatever you know some financial business that I'm unaware of right it's like analyst bye um and so you know and right now we don't see the I don't you know like because the models are not perfect not
(1:11:25) everything can be solved by AI obviously And I think that even in the future like not everything will be solved with AI. But once again, if you think about it, AI first then human. It just like the the amount of labor when you go from human first then AI to AI then human. It's like there's going to be a meaningful delta.
(1:11:50) And so I really think, you know, I I'm an optimist and I am optimistic on the future and I'm a technologist for a reason. Um, but that doesn't mean that there isn't some type of short-term chaos. Yeah. But moving on from the chaos to the the optimism, like for teams out there that are building, like it's incredibly powerful. It's exciting. It's fun.
(1:12:15) We're having a ton of fun at TFTC implementing the stuff and working on particularly the videos. It's um it's been something that we've really been somewhat addicted to over the last three months. is just getting better and easier for us as we get the process down and the reception is still pretty pretty remarkable once we get it out there. I was watching one uh earlier today and I I'm going to follow up with you after and be like tell me your secrets cuz I haven't I haven't spent much time here but I'm just like absolutely loving I think you you guys had one video that got like you know 20,000 retweets or something crazy like that. Mhm. Yeah. I
(1:12:50) think the uh the 19 the the going off the gold standard one that was the most so far. Amazing. Like such a and it was such a great video. Obviously it's like oh it's a little AI generated in there but it was like the storytelling was amazing. Yeah.
(1:13:08) I think that's what we honed in on is just using it to tell tell stories and really storyboarding. That's what most most of the time is generating. You have to iterate through the generations and thank god I don't have to do that. That's Trevor, Elijah's job to do that. And they I think they're definitely have moments where they're beating their head on the table because the generation isn't what they need.
(1:13:30) But once the end product's there, it's like, holy crap. A lot of our time spent on storyboarding and deciding what story to tell. Um, which is fun. That's I like to think I'm somewhat of a creative person, but I can I've never been able to manifest that outside of conversations and and writing. like I I love movies and I I like art, but I can't draw. I can't produce a movie.
(1:13:52) But now we can sort of start that process with AI. I mean, one of my favorite things to do, and this is such a like easy example, right? Um is, you know, I have a bunch of kids, right? I have four kids, uh uh seven and under, and you know, one of the favorite activities is to do coloring pages.
(1:14:13) And it's like I will generate coloring pages for the kids, right? And so I'll ask him, "What do you want?" They're like, "I want a princess riding a a pony uh jumping over this thing." And it's like it gets really wild really quickly. It's like it generates it. I print it off. I give it to them and they're like coloring. They're having a great time. Yeah.
(1:14:32) And we have um we've been uh in the car rides, we've been using chat GBT voice. We named our GBT Daryl. And uh if the kids the boys ever have a question in the back of the car, we just pop Daryl open, give them the context. Say Daryl. Yep. We've got a five and a three-year-old here. They're very curious and they're they're looking to learn.
(1:14:51) And um my my oldest son, two weeks ago, we were playing with Daryl. He's like, "How long does it take to to count to 100 trillion, Daddy?" And I was like, "I don't know. Let's ask Daryl." And the answer blew my mind. I was like, "Ah." But then like it went from there. His cousin was in the car. And similar to the um to the coloring pages, um we asked Daryl to to craft a story for my oldest boy and his cousin who's a girl, like a heroic story of them traveling through a forest and in 10 seconds had a 5minute story and his parents in the car was like, "Oh, we get five minutes of relative silence." And uh it was fun and
(1:15:24) they were they were amazed like the fact that they were the main characters in the story. It's like it's so much fun. You know, I my son loves uh insects and so you'll turn on the little video mode and you'll like pull up an insect. He comes in, he's like got this thing on his, you know, on his arm or whatever. What is it? Like uh I don't know. Let's find out. Right.
(1:15:46) Yeah. And it's like untapped. That's actually one thing the uh the school my boys go to now. They actually I'm happy to see that they've put feelers out there to the parents like we're looking to before we're thinking on AI. We're putting together like an AI board or um committee to help us implement it in the school. I'm like, "Thank God." Yep.
(1:16:10) You're thinking about this cuz that's like think positively, optimistically, like the potential for this to really accelerate human knowledge is unbounded. It really It really is. It really is. you almost have to like teach yourself when um like historically, you know, there would be these questions that I would have or it'd be like how do I do X, right? Or is it possible to do X, right? And before if I were to Google it, right? It's like I'm probably not going to get something interesting because it's such a like particular thing unless it's you know how do I change my door or something you know like a lot of people search for but usually it's like this kind of longer
(1:16:54) tail thing right and uh and now it's just like you almost have to teach yourself I I should just ask that question right and and then it will kind of prime my thinking with some ideas which I can then used to dig deeper and I see it with kids.
(1:17:19) I see it with myself, you know, it's like, is it possible to even build this into my product like, uh, yeah, you could probably do it this way or that way or the other way. It's like, that's actually a great idea. I'm going to go use that, right? So you almost kind of have to have like a there's a level of you know people would always say um in in for software engineers in particular like you should go Google like if you ever have a question about code go Google it and then if you can't figure it out come back and ask me.
(1:17:42) It's almost like we've kind of entered this phase where it's not just for software engineers anymore. It's like you have a question, ask, you know, ask one of these AIS um first to prime it and then if you still can't figure it out, um you know, go another level deeper. Um you know, as someone who's homeschooled, um the world has just will massively change in education as well.
(1:18:09) Um and uh we we homeschool our children and a lot of it was we were kind of teetering on like should we do you know maybe like some private schooling or something versus homeschooling and you know at the time I was playing around with AI and I was like time out no we homeschooling because when you have these superpowers in your in your hands um obviously I don't want my kids to be um playing around on screens all day um but like if you selectively use it.
(1:18:37) It is a massive accelerant. And you know, the homeschooler, at least the homeschooled parent is always kind of trained or learns um that the most important thing about homeschooling is the personalized instruction. And so if you apply that with AI, it's like it just makes it even more. You know, it's like personalization on steroids.
(1:18:55) Yeah. Especially with with the memory with the agentic brain that exists like Yeah. And it is scary too. It's like how much information do we give these models? like can open source models and products like Maple get the parody so you feel more comfortable Yep. doing all this. But that's why I think the big scary thing is uh is really around like the training, you know? It's like I if there's one area that I feel like some amount of maybe the free the free market maybe the free market figures it out. Um but the thing that I really think um should
(1:19:33) exist and should be transparent is you know they basically have these I guess I was listening to I think it was Sam Alman chatting about it but they basically have these big documents that have these very maybe convoluted rules around like if this happens don't right it's like it's kind of the teaching document for the foundation model I want to know what that is and I think we have I think that they're um that those companies have a responsibility to tell us, you know, because because the you know, if we were if if anybody was
(1:20:10) concerned about social media censorship, like this is that on this has the potential to be that on steroids. So, publish how you like get that out in the open. Like I think that that makes sense. I think you can keep some of these other trade secrets. Sure. But like that we we we should know how the algorithm works.
(1:20:34) Yeah, I have a feeling that's going to be hard to get unless you have the free market come and somebody position themselves as we're going to be the company that does this and you should use us because of this. Y um but tying this uh tying the bow on the overarching conversation like a lot of how we view a 1031 and me personally as a Bitcoiner businesses transforming is on the capital side on the on the reserve asset side with Bitcoin like let's just expand on how you view Bitcoin's role in not only business formation but like how you run a
(1:21:08) business into the future particularly if you're leveraging this unbounded leverage with AI. There's there's a lot of places that I could go. Maybe I'll start with um the I'll start with the tech maybe. Um uh the first is like the idea of agents um exchanging some amount of currency between each other very quickly.
(1:21:33) Um I can see that happening. I was never like super bullish on this idea of like I get I pay per amount of minute I consume. Like I was never a big fan of that but like with agents cuz like I think humans kind of are always like oh I'm paying more and I'm paying more and and there's this psychological roadblock I think to that model.
(1:21:54) Nick Zabo is the mental cost of microtransactions. Yeah. Yeah. But when agents are doing it they don't really care, right? because they're not like I don't I I think maybe maybe they will care. I don't know. So, so I think that from a technological level um I think we can see more of that in the future. Um or we will see more of that in the future.
(1:22:19) It feels like that's coming and you know Stripe and all these other ones are doing it with you know different stable coin rails and other things like that. Um for you know I I kind of I'm a big fan of like these Bitcoin treasury companies. Um, I think that they're kind of, you know, Bitcoin treasury maxis, right? Um, and so, you know, they recognize that there's an opportunity in the market and so like in some ways the actual business is is the sideeshow to the main show and the main show is like, you know, intelligent leverage, etc., right? Micro Strategy has done an amazing job there, and I'm a huge fan of what they've done. Um but I
(1:22:51) think most businesses um will um still maintain their normal business operations. Um they you know won't go public but any profitable business um will have an opportunity to you know store their energy or store their capital in a way where it's you know not debased and I think that that will be a wonderful thing for the world.
(1:23:14) I think that that will present new opportunities for startups amid their growth journey. So like one of my friends who I will not mention his name um uh started a VC backed startup um grew it. I mean the thing's profitable and over the past few years like he's accumulated a war chest like he's accumulated a lot of Bitcoin and and it's like absolutely thrilling and it's changed the way that he thinks about how he grows his business.
(1:23:47) So like in the past you kind of you basically only had like maybe one option and it was let's throw money at trying to reignite that growth in a more meaningful way but it's like but when you're able to store your uh capital in a better way you can you know Bitcoin's a hurdle rate. Are you gonna hire that um are you gonna hire that, you know, super senior leader that wants a ton of money and may not work out or you could just shovel that into, you know, Bitcoin? Shove that extra uh profit into Bitcoin and play the long game. I think that it's going to be a wonderful thing for businesses. Um I think the the big
(1:24:27) question mark is, you know, profitability. Um because I think, you know, if you're in my shoes, you know, we we hold a very small sliver um uh in Bitcoin and I'm happy about that and I'm proud of it. Um but the reality is is like when uh when you uh like we actually want to beat the hurdle rate, we want to bit beat the Bitcoin appreciation rate.
(1:25:00) If we don't, we're cooked, right? And so in some ways you kind of have to think about um like there's a lot of areas that I feel like I could deploy the capital and and beat the Bitcoin hurdle rate. That may not always be true, but like it's true now. Um but like for certain capital that I wouldn't deploy, I should think about storing it um in a way that is uh is wise and thoughtful.
(1:25:27) you know, like I uh I was in the I was in the process of shutting my business down and I had a bank account at uh SVB, Silicon Valley Bank, and I had some money in it and then that whole SVB thing blew up and it was like, huh, okay, you know, like this was never something I thought about before. Now you have to think about it a little bit, right? Um, and like every entrepreneur is just like, I put my money in SVB.
(1:25:55) I maybe put it in a in a savings account that yields, at the time I think it was like, I don't know, 3% or 2% or something. Um, but you know, that's what they did. Um, and then all of a sudden, you know, the financial world kind of blew up. Um, so anyway, I digress, but I think for for businesses, especially profitable ones, um, you know, Bitcoin is going to be an amazing recalibration moment.
(1:26:28) Um, it will recalibrate how they think about businesses, how they think about capital allocation. Um and I think that that will be a wonderful thing for the world because you know there's nothing you just when when fiat is melting um the I just think you end up making stupid capital allocation decisions because you you intuitively know that the ice cube is melting.
(1:26:54) Um, and so yeah, I'm really excited to see how things change and I hope to, you know, do a little bit of writing and and kind of talk a lot about it a little bit more. Um, for even like an early stage startup because I think that while we have to be we have to think about this different, um, it kind of feels weird that startups that are encouraged to embrace technology in every part of the business like, well, that part's off limits.
(1:27:17) It's like that doesn't make sense, you know? It's like no this digital transformation exists everywhere and we and we should be thoughtful around how we do that and where and that applies to your balance sheet as well. Yeah, completely agree. I mean, if we've seen it within the 1031, like the companies that have taken a portion of their raises, use it to buy Bitcoin.
(1:27:42) like the amount of companies that you were describing it earlier. You raise typically 18 months of runway in some cases 24 months. Um in extreme cases 36 months, but there's a number of companies that raised well beyond uh that that sort of threshold, that typical threshold that's thrown out there and have not had to go back to market because the Bitcoin Treasury has worked in their favor and they're able to use that as working capital down the line. And not only that, like there are we're investing in Bitcoin companies run
(1:28:13) by Bitcoiners who understand the hurdle rate. And so I think we have an anomalous portfolio in the sense that we have companies focused on profitability and growth alongside each other to make sure that they can stack as much Bitcoin as possible. Yeah, I I really think the number one benefit um is not price appreciation over time.
(1:28:37) I actually think it's that it rewires how you think about building a business and that will make you a better founder. It will make you a better operator. And then maybe the second is like it it there's a little bit of a hedge like you can create a little bit of a hedge against the basement in particular.
(1:28:56) And then thirdly, think about price appreciation last. I like that. I like that framing. And I know you said that like a lot of particularly other VCs that's that's the thing that blows my mind. They'll the if we're like in a deal with a VC that's not focused on Bitcoin or quote unquote crypto and the founder has to go to them and be like, "Yeah, we're going to take a portion of this raise and put it in Bitcoin." They get a lot of questions. Um and it blows my mind by that.
(1:29:26) To your point, we're in this digital transformation age. um and you're having a company focus on all areas of the business that are going to be disrupted by this digital transformation except for the balance sheet. It just doesn't make sense. But on that note, obviously you're well connected and know a lot of founders.
(1:29:45) Do you do you get the feeling that people are waking up to this? I think it's still super early. Yeah, I think it's super early. Um so like you know if you look in the public markets I think the public markets are kind of indicative of of um of the private markets right so like you know the most notable example as of late is you know Figma right Figma went public they had um I think it was like less 5% or less in Bitcoin and you know I think Dylan Field I think I think that's his name the CEO like was super involved in like NFTTS and all this stuff right um and obviously
(1:30:24) apparently is a Bitcoin fan I think that that's generally that feels like what will become a new de facto standard is like 5% or less for for for a business in the in kind of this uh fast growing um you know venturebacked um world, right? I I I I don't think it Yeah.
(1:30:52) because you're you're you literally the game the game the the way that you grow is like you you're okay being unprofitable you're trying to beat the hurdle rate meaningfully right um so you just have to think about it differently but like I said if you're profitable and you you know I met um I was at a Bitcoin Treasury conference um last week and I stopped by and I I met an individual and his father that um run a uh like a self storage facility and it's like they're buying like I think he said I mean this is public so I think I saw it on Twitter it's like you know 10 grand a week or 10 grand a month and they just you know they run a you know a
(1:31:29) self- storage facility in somewhere in in the states and but it's like that's awesome that's absolutely fantastic and there's going to be a lot more of those and those who get on earlier are going to be very happy that they did and that's what I and that's what I think you're an incredible advocate for it cuz everybody's going to be a Bitcoin treasury company just like everybody is an internet company to a certain extent at some point and we're obviously in the early stages that very early stages of
(1:31:59) that transition um and obviously our core focus my core focus here at this business at 1031 is on Bitcoin specific industry but that's something at 1031 particularly we talk about a lot is like when do we sort of begin to cross that chasm and I think advocates like you who are Bitcoiner building a business that really doesn't have anything to do with Bitcoin and is on the cutting edge of this AI revolution like the more Luke Thomases that exist in the world that are really putting this message out there and sort of derisking it for others um is extremely important.
(1:32:38) Yeah, it's going to be it's going to be a fun time, but you know, we're we're still obviously early innings. Um and uh you know, it's like I said before, I really think the number one unlock is that it rewires how you think about capital allocation. I've seen it with my friends.
(1:32:59) I have personally experienced this for myself, right? So, it's it's like a lot of Bitcoiners experience this personally and then they're like, would this actually work in a business context? It's like absolutely, absolutely. Um, and so I just think that that is the nugget is it's like it's almost like if you were to, you know, there's this concept of, you know, like uh CEO coaching, founder coaching, right? It's like holding a little bit of Bitcoin on your balance sheet, even a small amount is like hiring a coach.
(1:33:28) It teaches you to be more thoughtful. It's like, what is that worth? Priceless. It's priceless. It really is. I love you describing it that way. It's a founder coach founder coach. Yeah. Doesn't mean I'm not going to spend money, but it does mean that um that I'm going to view it through a through a through a different lens. I'm going to think twice. Weigh the opportunity cost, if you will.
(1:33:58) The opportunity cost. What um any final thoughts, final pieces of advice as we wrap up here? So many things I could probably say, but I think if you've made it this far, thank you. Um, if you have comments, uh, shoot me an email, bluke formable.ai. Um, or leave a comment on the YouTube video or whatever, and I will, uh, read it and weep.
(1:34:26) Um, but, uh, I think if you, if you're skeptical about AI, I understand. Um, and I think that, um, the reason why you're skeptical is probably because you see a lot of hype. And that is true. But what is also is true is that there is substance. And if you want to learn, and the analogy I always use is I feel like sometimes I'm in a room and there's like $100 bills to use the the fiat uh world as an example.
(1:34:55) It's like AI opens your eyes and you kind of realize that there's like a bunch of money lying on the floor and you're like, well, like I I guess I could pick it up. Like I guess I could pick it up because if I don't, like maybe someone else will. Um, and so AI kind of presents that opportunity whether you're a small business or a bigger business. I think small businesses per your comment earlier around how you're using it actually have a way bigger advantage.
(1:35:16) There's just so much more that you can do. And I feel like the only way that um uh to jump in is to just tinker. Like start playing around with chatbt for a little bit or Grock or whatever your tool of choice is. then upgrade and start using AI in like workflow tools whether it's Zapier there's product called Nadn relay gum loop those ones where basically you can start building out business workflows that kind of consistently um do things for you that's like the next leg um and while you're playing with those tools they will kind of introduce you some to
(1:35:55) some of the more advanced concepts as you're tuning the you know tuning the Um, and then then you'll be able to kind of build this uh worldview or mental model around how to use agents and how that how they can work for you. And then I think all of a sudden you'll start to notice more areas where uh things could be um transformed.
(1:36:20) I will say the other last thing is that you can actually sounds so bad and weird. Um ask chat GPT how to use it if it has recommendations. Explain your business. Ask it if it has recommendations. Throw in images of like little whiteboard diagrams of your business process and stuff like that. Ask it. It'll probably come back with some ideas that will help you um uh come up with some creative inspiration.
(1:36:44) Yeah, I will say I mean I know we're wrapping up, but I think it's important just to give an example of how we're leveraging it on the backend business process side, but we use NAD for a couple things right now. um for the newsletter. We just a scaffold to get a scaffold of the newsletter every day. We're we've used it. We're currently like iterating on it. Should go live again next week.
(1:37:09) But Ed, when I write the newsletter, um Ed usually I'm like, "All right, I'm ready to write a newsletter." he goes in and manually like creates a new post, make sure the ads are there like and then we have this section um which is basically a short summary of a section of a podcast that we recorded within the last week with a quote and a link back to the podcast and it's been a manual process of we'll record this on Riverside. We'll get the transcript. We'll put that in Dropbox.
(1:37:34) Then we'll take the transcript from Dropbox. We'll put in cloud code that we we've built this prompt that we've been iterating on for for months now at this point. And then we'll get a couple of podcast sections that we can choose from to put into the newsletter and that's sort of the manual process and AI is sprinkled in obviously transcription and um the the prompt claw code.
(1:37:57) But now with N8N, we can automate that. Like Logan can put the transcript in the Dropbox and that triggers the the flow where we just go in. It's like what section you want, click. And then you can even connect it to Ghost and it'll create the post for you and that will save ad like 15 minutes a day. Yep. Perfect example. Yeah.
(1:38:23) And it's it works and it's one that works like the power is that you you have this kind of digital brain thinking on your behalf, but you still have guardrails on it, right? You're like, "No, no, no." Like after this happens, I want you to put it over here, right? So, you still feel like you have control. Um, but you have a little bit of the magic sprinkled in parts of the process where it's most relevant.
(1:38:47) And that I think is the the big nugget is like that's why I always recommend like play around with chatb sure then upgrade this these workflow tools because like you'll still have some control but you'll be able to infuse the magic so to speak um at different parts of the workflow but you'll still have the feeling of control and that's really important because that's where people go off the rails is they think like oh if I have this agent talking to this other agent and like all of a sudden like if it one mistake like it makes one mistake the whole thing blows up, right? So with these you have some level
(1:39:19) of control and that control like businesses want predictability and so that's why infusing some element of control with the magic is kind of like the key that picks a lock at least for step two and whatever step three is we'll figure out as AI gets better. Yeah. Well hopefully as AI gets better we'll continue these conversations.
(1:39:45) I know you're a busy man and uh it took you a couple years to let me know that you're ready to come on. So hopefully it doesn't take two more years, but I would be happy to come back on anytime. Um uh this is all, you know, I'm I'm in the thick of it right now with the new business. Um learning every day and uh always happy to share um what I'm learning. Uh hopefully it's right. Um but always happy to share my learnings.
(1:40:11) Well, I I want to sincerely uh thank you because you've been extremely generous with sharing your learnings with me over the years and it's it's helped me really think about how to approach this transformation as it's happening and I think it's helped us uh improve our business. So, thank you. Appreciate it. All right, we'll do it again.
(1:40:30) Let's go enjoy our Friday nights with our families. I can hear my boys playing downstairs and uh we're going to win. It's going to be okay. Absolutely. Never do. Peace and love, freaks. Thank you for listening to this episode of TFTC. If you've made it this far, I imagine you got some value out of the episode. If so, please share it far and wide with your friends and family. We're looking to get the word out there.
(1:40:54) Also, wherever you're listening, whether that's YouTube, Apple, Spotify, make sure you like and subscribe to the show. And if you can leave a rating on the podcasting platforms, that goes a long way. Last but not least, if you want to get these episodes a day early and add free, make sure you download the Fountain podcasting app. You can go to fountain.fm to find that.
(1:41:17) $5 a month gets you every episode a day early. Adree helps the show, gives you incredible value. So, please consider subscribing via fountain as well. Thank you for your time and until next time.

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