1 00:00:00,160 --> 00:00:03,880 Speaker 1: The most powerful workforce in human history is rising, and 2 00:00:04,640 --> 00:00:07,720 Speaker 1: it doesn't need you. It doesn't sleep, it doesn't eat, 3 00:00:07,960 --> 00:00:10,360 Speaker 1: it doesn't ask for a raise, and it's coming for 4 00:00:10,640 --> 00:00:15,120 Speaker 1: every job you thought was safe. Yes, doctors, lawyers, coders, 5 00:00:15,160 --> 00:00:20,440 Speaker 1: and even entrepreneurs. But here's the really terrifying part. Losing 6 00:00:20,480 --> 00:00:24,640 Speaker 1: your job is just the beginning. These AI agents aren't 7 00:00:24,720 --> 00:00:29,280 Speaker 1: just replacing workers. They're about to reshape the entire global economy. 8 00:00:29,480 --> 00:00:32,599 Speaker 1: They'll hire each other, they'll pay each other, They'll make 9 00:00:32,680 --> 00:00:37,360 Speaker 1: decisions faster than any human can react. The systems we've 10 00:00:37,360 --> 00:00:40,519 Speaker 1: trusted for centuries they're not built for this. They're about 11 00:00:40,560 --> 00:00:42,720 Speaker 1: to break. So in this video, I'm going to show 12 00:00:42,760 --> 00:00:46,720 Speaker 1: you how AI agents will trigger the biggest economic shift 13 00:00:46,760 --> 00:00:50,760 Speaker 1: in human history and reveal the one thing that's perfectly 14 00:00:50,800 --> 00:00:53,440 Speaker 1: positioned to survive the chaos, and what we should be 15 00:00:53,440 --> 00:00:56,480 Speaker 1: doing to position ourselves now real quick. On mark loss 16 00:00:56,520 --> 00:00:59,400 Speaker 1: and as an investor, I've built and I've exited several 17 00:00:59,440 --> 00:01:02,080 Speaker 1: tech companies. I've been doing this through multiple boom and 18 00:01:02,080 --> 00:01:04,400 Speaker 1: bus markets. I've been a tech focus to venture capital 19 00:01:04,440 --> 00:01:06,520 Speaker 1: investor for over a decade. I'm a partner at a 20 00:01:06,600 --> 00:01:10,800 Speaker 1: leading bentcoin venture fund. I write the Quantum Wave Investment 21 00:01:10,800 --> 00:01:13,600 Speaker 1: Report where I help people navigate these big shifts in 22 00:01:13,640 --> 00:01:16,480 Speaker 1: tech and money. And these lessons are some of the 23 00:01:16,520 --> 00:01:19,199 Speaker 1: things that I'm looking at and hopefully you can use these. 24 00:01:19,640 --> 00:01:23,640 Speaker 1: So let's go all right, we are talking about something 25 00:01:24,040 --> 00:01:27,960 Speaker 1: super exciting for me. It's also super terrifying. Depends on 26 00:01:28,000 --> 00:01:31,120 Speaker 1: how you interpret information more importantly, what you're going to 27 00:01:31,160 --> 00:01:32,959 Speaker 1: do with it. Don't worry. At the end, I'm going 28 00:01:33,040 --> 00:01:35,360 Speaker 1: to leave you with some actionable takeaways so you can 29 00:01:35,400 --> 00:01:37,679 Speaker 1: make this exciting for you as well. Okay, so I'm 30 00:01:37,680 --> 00:01:43,520 Speaker 1: talking about the rise of AI agents. What yeah, agents. 31 00:01:43,720 --> 00:01:46,080 Speaker 1: Now this is happening super fast, so if you're not 32 00:01:46,080 --> 00:01:48,640 Speaker 1: paying attention, you might have missed what's going on. We 33 00:01:48,720 --> 00:01:52,080 Speaker 1: have AI right that kind of got brought to the forefront, 34 00:01:52,080 --> 00:01:55,360 Speaker 1: brought to consumers with Open AI back in November twenty 35 00:01:55,400 --> 00:01:57,840 Speaker 1: twenty two, and now it's changed the world. Now we 36 00:01:57,960 --> 00:02:01,560 Speaker 1: have something called AI agents. I'm going to break this 37 00:02:01,640 --> 00:02:03,200 Speaker 1: all down for you and see what so you can 38 00:02:03,280 --> 00:02:05,480 Speaker 1: understand what it is, but we can set the AI 39 00:02:05,720 --> 00:02:07,800 Speaker 1: agent market is absolutely exploding. 40 00:02:08,120 --> 00:02:08,880 Speaker 2: Let me tell you what this is. 41 00:02:09,080 --> 00:02:11,200 Speaker 1: So it's basically a way that I can create an 42 00:02:11,200 --> 00:02:15,280 Speaker 1: AI to be an autonomous agent on my behalf to 43 00:02:15,400 --> 00:02:18,639 Speaker 1: do a pre defined set of tasks. So for example, 44 00:02:19,480 --> 00:02:22,160 Speaker 1: I could create an AI agent to do my customer 45 00:02:22,200 --> 00:02:24,600 Speaker 1: service for me, or handle my sales calls for me, 46 00:02:24,880 --> 00:02:27,040 Speaker 1: or go research financial markets for me. So I give 47 00:02:27,040 --> 00:02:29,840 Speaker 1: it a set of parameters and I just let it 48 00:02:29,880 --> 00:02:33,040 Speaker 1: go and it works autonomously based off of that code. 49 00:02:33,080 --> 00:02:35,560 Speaker 1: This is what AI agents do. Now, these can do 50 00:02:35,919 --> 00:02:38,760 Speaker 1: complex things that stack on top of each other. But 51 00:02:38,800 --> 00:02:40,680 Speaker 1: I'm getting ahead of myself. I'll get back to that 52 00:02:40,720 --> 00:02:43,680 Speaker 1: in a minute. But again, this is happening super super fast, 53 00:02:44,040 --> 00:02:46,079 Speaker 1: like in the last six months fast. So we can 54 00:02:46,080 --> 00:02:49,240 Speaker 1: see here twenty twenty four there was barely any market. 55 00:02:49,520 --> 00:02:53,519 Speaker 1: By twenty thirty, they're expecting it to grow to forty 56 00:02:53,600 --> 00:02:57,080 Speaker 1: seven point one times. This is the market size in billions. 57 00:02:57,080 --> 00:02:59,480 Speaker 1: We're talking about it growing super fast, and all the 58 00:02:59,480 --> 00:03:03,119 Speaker 1: big people are in this of course, Google, IBM, Microsoft, Amazon, 59 00:03:04,240 --> 00:03:06,760 Speaker 1: you get it. Okay, Now, this is all happening really fast. 60 00:03:06,800 --> 00:03:10,120 Speaker 1: Now this is projected to grow even faster and faster 61 00:03:10,240 --> 00:03:13,600 Speaker 1: and faster. So you can see AI agents market right here, 62 00:03:14,400 --> 00:03:17,040 Speaker 1: and you can see we're right here twenty twenty five 63 00:03:17,120 --> 00:03:19,040 Speaker 1: right now, and this is what we. 64 00:03:19,080 --> 00:03:20,960 Speaker 2: Call parabolic growth. 65 00:03:21,320 --> 00:03:24,959 Speaker 1: We're at about five point twenty nine billion right now, 66 00:03:25,240 --> 00:03:27,400 Speaker 1: and they're expecting it to grow out of forty percent 67 00:03:28,000 --> 00:03:32,640 Speaker 1: compounded annual growth rate KEGAR until twenty thirty five to 68 00:03:32,720 --> 00:03:35,320 Speaker 1: about a value of two hundred and sixteen billion. I'm 69 00:03:35,320 --> 00:03:38,400 Speaker 1: guessing we're gonna overshoot that number, but you can still 70 00:03:38,440 --> 00:03:41,200 Speaker 1: see the type of growth that they're projecting. These AI 71 00:03:41,360 --> 00:03:44,520 Speaker 1: agents are coming for everything. So when I say coming 72 00:03:44,560 --> 00:03:48,000 Speaker 1: for everything, what are they coming for? Well? Everything, But 73 00:03:48,120 --> 00:03:50,240 Speaker 1: right now what we can see is that the type 74 00:03:50,240 --> 00:03:52,960 Speaker 1: of agent systems is we have like multiagent and single agent, 75 00:03:53,080 --> 00:03:55,600 Speaker 1: so singleated it's working together to become multi agents to 76 00:03:55,600 --> 00:03:58,960 Speaker 1: do multiple things. So for example, they could do all 77 00:03:59,000 --> 00:04:02,560 Speaker 1: the search and dumped them as, they could do niche 78 00:04:02,640 --> 00:04:05,000 Speaker 1: research for me. They could write articles for me. They 79 00:04:05,000 --> 00:04:06,960 Speaker 1: can create ads and then can go buy the ads 80 00:04:06,960 --> 00:04:10,120 Speaker 1: on Facebook marketplace, so they could string multiple agents together 81 00:04:10,200 --> 00:04:12,840 Speaker 1: to do this complex thing. The areas of application that 82 00:04:12,880 --> 00:04:15,480 Speaker 1: we're really seeing right now just in a last a 83 00:04:15,480 --> 00:04:18,039 Speaker 1: couple of months, but this is going to change customer service, 84 00:04:18,520 --> 00:04:22,640 Speaker 1: virtual assistance, healthcare. The type of roles that the agents 85 00:04:22,680 --> 00:04:25,600 Speaker 1: are being assigned to code generation, so they're writing code 86 00:04:25,600 --> 00:04:27,560 Speaker 1: at a super rapid rate. As a matter of fact, 87 00:04:27,640 --> 00:04:30,560 Speaker 1: another six months from now, coders, we're going to be 88 00:04:30,560 --> 00:04:33,400 Speaker 1: looking for new jobs, customer service, reps, marketing, some of 89 00:04:33,440 --> 00:04:36,360 Speaker 1: the things like I just sort of talked about, productivity 90 00:04:36,400 --> 00:04:39,680 Speaker 1: and personal assistance and sales. These are the types of 91 00:04:39,720 --> 00:04:43,440 Speaker 1: things that are under attack right now. Types of learning, 92 00:04:43,440 --> 00:04:46,160 Speaker 1: deep learning, machine learning, and the types of products is 93 00:04:46,200 --> 00:04:48,480 Speaker 1: build your own agents and ready to deploy agents. So 94 00:04:48,520 --> 00:04:49,960 Speaker 1: we're going to show you a couple of ways that 95 00:04:50,000 --> 00:04:52,520 Speaker 1: you can do this, where you can build your own 96 00:04:52,839 --> 00:04:54,839 Speaker 1: or you can go with companies that already have this. 97 00:04:54,920 --> 00:04:58,000 Speaker 1: But look, this is a ticking clock. This is all 98 00:04:58,080 --> 00:05:02,880 Speaker 1: happening right now. The world is changing right below our feet, 99 00:05:02,920 --> 00:05:05,440 Speaker 1: and I think it's exciting, but for people that are 100 00:05:05,440 --> 00:05:08,240 Speaker 1: listing those categories right there, it can be extremely terrifying. 101 00:05:08,520 --> 00:05:12,200 Speaker 1: Now we can see that AI implementation is a top priority, 102 00:05:12,400 --> 00:05:16,560 Speaker 1: the number one top priority across marketing and e commerce teams. 103 00:05:16,720 --> 00:05:19,200 Speaker 1: So for e comm it can do all the product research, 104 00:05:19,279 --> 00:05:22,520 Speaker 1: can get requests for quotes from all your vendors, it 105 00:05:22,560 --> 00:05:25,440 Speaker 1: can manage shipments, it could get your listings done, it 106 00:05:25,440 --> 00:05:28,320 Speaker 1: can handle the customer service on the what everything. So 107 00:05:28,360 --> 00:05:30,760 Speaker 1: it's a top priority for these companies. AI has proven 108 00:05:30,800 --> 00:05:35,440 Speaker 1: contribution to revenue and cost reduction, so it's a proven 109 00:05:35,480 --> 00:05:39,200 Speaker 1: contributor to revenue, bringing in more money and reducing costs 110 00:05:39,240 --> 00:05:41,640 Speaker 1: at the same time. Of course, businesses want that a 111 00:05:41,800 --> 00:05:46,760 Speaker 1: implementation is their number one priority eighty three percent. It's 112 00:05:46,760 --> 00:05:48,760 Speaker 1: a big number. Eighty two percent of sales teams with 113 00:05:48,800 --> 00:05:52,279 Speaker 1: AI saw revenue growth in the past year, so pretty 114 00:05:52,320 --> 00:05:55,640 Speaker 1: much everybody who tried it made more money. More people 115 00:05:55,680 --> 00:05:59,080 Speaker 1: want to do it versus sixty six percent of teams 116 00:05:59,120 --> 00:06:04,440 Speaker 1: without AI. I competition right, Seventy six percent of e 117 00:06:04,480 --> 00:06:08,320 Speaker 1: commerce teams with AI credit it with revenue growth. Seventy 118 00:06:08,320 --> 00:06:10,440 Speaker 1: six percent of people who used it made more money. 119 00:06:10,839 --> 00:06:14,440 Speaker 1: Ninety two percent of service teams with aisay it reduces 120 00:06:14,839 --> 00:06:18,400 Speaker 1: their costs, so saving money, making money. It's all the 121 00:06:18,400 --> 00:06:20,120 Speaker 1: same thing. If ninety two percent of the people are 122 00:06:20,120 --> 00:06:23,920 Speaker 1: getting at guess what everybody is going to want it, 123 00:06:24,160 --> 00:06:27,320 Speaker 1: and not just AI as in CHGPT, but AI agents. 124 00:06:27,720 --> 00:06:30,280 Speaker 1: Now we have all these companies jumping into this game 125 00:06:30,279 --> 00:06:33,760 Speaker 1: to build AI agents. This is Salesforce introduce an agent 126 00:06:33,880 --> 00:06:36,919 Speaker 1: Force two point zero, the digital labor platform for building 127 00:06:37,760 --> 00:06:42,360 Speaker 1: a what limitless workforce. So now Salesforce that's powered your 128 00:06:42,680 --> 00:06:46,000 Speaker 1: customer contact based your CRM. Now they want to give 129 00:06:46,040 --> 00:06:49,080 Speaker 1: you agents to replace all those people that work in 130 00:06:49,080 --> 00:06:51,640 Speaker 1: your company. Pretty cool, right, Well, it is if you're 131 00:06:51,640 --> 00:06:53,640 Speaker 1: a business owner. It's not so good if those are 132 00:06:53,680 --> 00:06:56,560 Speaker 1: your jobs being outsourced. But I have bad news for you. 133 00:06:56,640 --> 00:06:58,760 Speaker 1: Even if you're a business owner, you might still be 134 00:06:58,800 --> 00:07:01,039 Speaker 1: at risk. I'm going to break that down what we're 135 00:07:01,120 --> 00:07:03,480 Speaker 1: really seeing, though. You have to understand this. I talk 136 00:07:03,520 --> 00:07:06,200 Speaker 1: a lot about tech cycles, technology cycles, because when you 137 00:07:06,240 --> 00:07:08,599 Speaker 1: go back through thousands of years of history, it's always 138 00:07:08,680 --> 00:07:11,880 Speaker 1: technology that changes the world because it changes the way 139 00:07:11,880 --> 00:07:13,920 Speaker 1: that we work, the way that we organize, the way 140 00:07:13,920 --> 00:07:16,119 Speaker 1: that we communicate, and so then it changes the world. 141 00:07:16,160 --> 00:07:18,960 Speaker 1: And so what we've seen is technology changing the world. 142 00:07:19,080 --> 00:07:22,120 Speaker 1: And we saw the rise and the fall of the 143 00:07:22,280 --> 00:07:25,840 Speaker 1: knowledge industry. So what happened about two hundred and fifty 144 00:07:25,880 --> 00:07:28,440 Speaker 1: years ago was he had the Industrial Revolution. Now we 145 00:07:28,520 --> 00:07:30,960 Speaker 1: had people in the farms and the cottage industry, and 146 00:07:31,000 --> 00:07:35,000 Speaker 1: the Industrial Revolution represented the first time we had mechanized machines, 147 00:07:35,240 --> 00:07:37,320 Speaker 1: machines that can do the work with thousands of men. 148 00:07:37,520 --> 00:07:39,800 Speaker 1: And then we went on to do war machines. We 149 00:07:39,880 --> 00:07:44,400 Speaker 1: got steel, heavy equipment, electricity, automobiles, mass production. So we 150 00:07:44,440 --> 00:07:47,600 Speaker 1: had this Industrial age, and during the Industrial Age, especially 151 00:07:47,600 --> 00:07:50,320 Speaker 1: in America in the early nineteen hundreds to mid nineteen hundreds, 152 00:07:50,480 --> 00:07:55,960 Speaker 1: we became this industrial powerhouse. Our factories and our ingenuity 153 00:07:56,000 --> 00:07:59,680 Speaker 1: dominated the world. Of course, other countries industrialized as well. 154 00:08:00,080 --> 00:08:04,720 Speaker 1: Then something happened. We went from the Industrial age where 155 00:08:04,720 --> 00:08:07,200 Speaker 1: we had this massive middle class because we had this 156 00:08:07,600 --> 00:08:10,920 Speaker 1: assembly line, and everybody on the assymble line was pretty equal. 157 00:08:11,440 --> 00:08:14,720 Speaker 1: Very smart people and not so smart people were equal, 158 00:08:14,920 --> 00:08:17,080 Speaker 1: each putting their cog on a wheel. Now, a lot 159 00:08:17,120 --> 00:08:19,000 Speaker 1: of people would say that the reason why the middle 160 00:08:19,000 --> 00:08:22,200 Speaker 1: class is kind of gone today or shrunk at least, 161 00:08:22,480 --> 00:08:24,920 Speaker 1: is because those jobs have been outsourced to like China 162 00:08:24,960 --> 00:08:28,120 Speaker 1: for example. Now part of that is true, but I 163 00:08:28,160 --> 00:08:31,000 Speaker 1: would argue that it's because we went from the Industrial 164 00:08:31,040 --> 00:08:35,160 Speaker 1: age to the information age. You see, working in factories 165 00:08:35,160 --> 00:08:37,320 Speaker 1: and putting cogs on a wheel is not what it 166 00:08:37,400 --> 00:08:40,560 Speaker 1: used to be. And today we're on the information age. 167 00:08:40,559 --> 00:08:44,280 Speaker 1: So now we're building computer programs and software and microchips, 168 00:08:44,559 --> 00:08:47,839 Speaker 1: and we have people with laptops traveling the world making 169 00:08:47,920 --> 00:08:51,480 Speaker 1: money online. And now with AI we've gone from the 170 00:08:51,559 --> 00:08:55,480 Speaker 1: industrial age to the knowledge worker aged information age. And 171 00:08:55,480 --> 00:08:58,640 Speaker 1: then the Information age is, well, if you're smarter, if 172 00:08:58,679 --> 00:09:00,960 Speaker 1: you're more creative, if you work harder longer, you can 173 00:09:00,960 --> 00:09:03,559 Speaker 1: get ahead faster because you're not just putting. 174 00:09:03,320 --> 00:09:04,720 Speaker 2: A coggon wheel eight to five. 175 00:09:05,280 --> 00:09:08,440 Speaker 1: All right. Now, we can see that as we went 176 00:09:08,480 --> 00:09:12,840 Speaker 1: from the Industrial age to the Information age, society changed, 177 00:09:13,080 --> 00:09:15,080 Speaker 1: of course, because it changed the way that we work. 178 00:09:15,240 --> 00:09:18,080 Speaker 1: Instead of everybody being in the big communities and all 179 00:09:18,080 --> 00:09:20,240 Speaker 1: working together and all being on the union, now we 180 00:09:20,240 --> 00:09:22,760 Speaker 1: have digital nomads working on their laptops all around the world. 181 00:09:22,840 --> 00:09:24,160 Speaker 2: So it changes societies. 182 00:09:24,520 --> 00:09:27,000 Speaker 1: And what's happened part of that is because now if 183 00:09:27,000 --> 00:09:29,560 Speaker 1: I can be a knowledge worker, then I can have 184 00:09:29,640 --> 00:09:32,880 Speaker 1: specialty skill, and I can take that specialty skill and 185 00:09:32,920 --> 00:09:33,200 Speaker 1: I can. 186 00:09:33,120 --> 00:09:34,400 Speaker 2: Apply it anywhere I want. 187 00:09:34,520 --> 00:09:36,959 Speaker 1: So I could be a graphic designer, or a video editor, 188 00:09:37,040 --> 00:09:39,440 Speaker 1: or even a bookkeeper and I can provide those bookkeeping, 189 00:09:39,480 --> 00:09:42,560 Speaker 1: a graphic design, video editing services for multiple people at 190 00:09:42,559 --> 00:09:45,920 Speaker 1: the same time. And this created the gig economy. You 191 00:09:46,000 --> 00:09:48,720 Speaker 1: might have heard about it. This also includes Airbnb hosts 192 00:09:48,760 --> 00:09:51,880 Speaker 1: and Uber drivers and things like that. And the gig 193 00:09:51,920 --> 00:09:56,280 Speaker 1: economy has completely exploded under this information age. As a 194 00:09:56,280 --> 00:09:58,600 Speaker 1: matter of fact. You can see it from twenty twelve. 195 00:09:58,679 --> 00:10:02,480 Speaker 1: Basically non exist all the way till I mean, this 196 00:10:02,520 --> 00:10:05,000 Speaker 1: is only till twenty twenty one. Right now, it's like 197 00:10:05,200 --> 00:10:07,320 Speaker 1: way up here, but you can see the rise in 198 00:10:07,360 --> 00:10:09,360 Speaker 1: the growth of this now. One of the things that 199 00:10:09,400 --> 00:10:12,680 Speaker 1: this was amazing for was bringing workers from all over 200 00:10:12,720 --> 00:10:16,199 Speaker 1: the world into the global workforce. So I use a 201 00:10:16,240 --> 00:10:19,359 Speaker 1: website called upwork dot com. There's other ones like freelancer 202 00:10:19,400 --> 00:10:23,360 Speaker 1: dot com or fiver and basically any of these tasks 203 00:10:23,400 --> 00:10:28,120 Speaker 1: that you need done, these soft taskses, specialty skills, copywriting, 204 00:10:28,440 --> 00:10:32,680 Speaker 1: ghost writing, research, legal work, accounting, you name it. I 205 00:10:32,720 --> 00:10:35,000 Speaker 1: can go hire somebody from anywhere in the world to 206 00:10:35,120 --> 00:10:36,600 Speaker 1: do this job for me. And so what it did 207 00:10:36,720 --> 00:10:40,439 Speaker 1: is it brought what we call technical workers onto the workforce. 208 00:10:40,679 --> 00:10:43,240 Speaker 1: So maybe you're a coder from Islami's bad, or you're 209 00:10:43,240 --> 00:10:46,400 Speaker 1: an engineer from Pakistan, or you're a customer service rep 210 00:10:46,440 --> 00:10:49,839 Speaker 1: from the Philippines or your whatever. It brought all these 211 00:10:49,880 --> 00:10:53,360 Speaker 1: technical workers into the world and it created this giant 212 00:10:53,520 --> 00:10:56,360 Speaker 1: gig economy. Of course, it's not just all over the world. 213 00:10:56,440 --> 00:10:59,480 Speaker 1: It's in the United States as well. Data shows to 214 00:10:59,520 --> 00:11:03,080 Speaker 1: the global gig economy now counts for twelve percent of 215 00:11:03,120 --> 00:11:06,439 Speaker 1: the global market hasn't taken it over yet, but we're 216 00:11:06,840 --> 00:11:09,679 Speaker 1: since twenty twelve, right, this's happening really fast. More than 217 00:11:09,720 --> 00:11:12,360 Speaker 1: one third of the US workforce is now engaged in 218 00:11:12,400 --> 00:11:15,360 Speaker 1: some form of gig work, and they project that to 219 00:11:15,440 --> 00:11:19,280 Speaker 1: be half by twenty twenty five. That's this year, half 220 00:11:19,520 --> 00:11:23,160 Speaker 1: of the workforce in the United States will be working 221 00:11:23,240 --> 00:11:27,079 Speaker 1: on some type of gig Forty percent of organizations, one 222 00:11:27,120 --> 00:11:30,720 Speaker 1: in four workers on the payroll is a gig worker. 223 00:11:30,800 --> 00:11:34,720 Speaker 1: Twenty five percent of companies payrolls are for gig workers. Now, 224 00:11:34,800 --> 00:11:37,360 Speaker 1: I want to just reiterate the point one time. What 225 00:11:37,600 --> 00:11:39,000 Speaker 1: is a gig worker. 226 00:11:39,280 --> 00:11:40,600 Speaker 2: They they're like a trade. 227 00:11:40,960 --> 00:11:47,280 Speaker 1: They apply expertise. They have a skill, video editing, graphic design, copyrighting, research, 228 00:11:47,520 --> 00:11:50,160 Speaker 1: they have a skill and they can apply to different people. 229 00:11:50,440 --> 00:11:51,760 Speaker 2: That's their applied expertise. 230 00:11:51,760 --> 00:11:55,000 Speaker 1: Like I said, about half the workers there. Now we 231 00:11:55,040 --> 00:11:57,560 Speaker 1: can see why this is continuing to grow when you 232 00:11:57,600 --> 00:12:00,720 Speaker 1: break it down by age group. So we have baby 233 00:12:00,720 --> 00:12:04,040 Speaker 1: boomers right here, only nine percent of them are are 234 00:12:04,080 --> 00:12:07,800 Speaker 1: gig workers. Gen X twenty seven percent. But right here 235 00:12:07,840 --> 00:12:10,640 Speaker 1: we have the millennials forty five percent. So, of course, 236 00:12:10,920 --> 00:12:13,720 Speaker 1: as we start getting to these younger generations, we'll have 237 00:12:13,800 --> 00:12:16,120 Speaker 1: more and more people working in gigwork. So it's both 238 00:12:16,240 --> 00:12:19,439 Speaker 1: a technology thing, it's a societal thing, and it's an 239 00:12:19,480 --> 00:12:20,040 Speaker 1: age thing. 240 00:12:20,080 --> 00:12:21,240 Speaker 2: But here's the key. 241 00:12:22,080 --> 00:12:24,960 Speaker 1: The key is that these are people with trades, with 242 00:12:25,080 --> 00:12:29,520 Speaker 1: specialty skills that they can apply, and those skills are 243 00:12:29,640 --> 00:12:33,160 Speaker 1: under threat because it's those specialty skills that are going 244 00:12:33,240 --> 00:12:35,240 Speaker 1: to be the first to be outsourced. Let me explain 245 00:12:35,320 --> 00:12:38,120 Speaker 1: this to you. When I hire somebody on fiver or 246 00:12:38,200 --> 00:12:41,280 Speaker 1: upwork to do a task for me, they're an autonomous agent. 247 00:12:41,640 --> 00:12:44,680 Speaker 1: I'm hiring this person on fiver or upwork to go 248 00:12:45,360 --> 00:12:47,679 Speaker 1: do search engine optimization for me. So they're going to 249 00:12:47,800 --> 00:12:49,920 Speaker 1: take my article, they're going to go research it, they're 250 00:12:49,920 --> 00:12:51,800 Speaker 1: going to come up with the best keywords, they're going 251 00:12:51,840 --> 00:12:54,160 Speaker 1: to rewrite the article, they're going to get it posted, 252 00:12:54,320 --> 00:12:56,760 Speaker 1: they're going to get the backlinks and all of those things. Well, 253 00:12:57,280 --> 00:13:00,680 Speaker 1: that's an autonomous person that's doing all of those functions. 254 00:13:00,920 --> 00:13:03,640 Speaker 1: But today I can have an AI agent build to 255 00:13:03,679 --> 00:13:06,480 Speaker 1: do that. I can hire customer service people from the 256 00:13:06,520 --> 00:13:09,400 Speaker 1: Philippines that can reply to my emails or take my 257 00:13:09,480 --> 00:13:12,840 Speaker 1: phone calls. But now they're an agent. They're an autonomous 258 00:13:12,880 --> 00:13:15,520 Speaker 1: person that's doing this based off of scripts up provided. 259 00:13:15,920 --> 00:13:18,440 Speaker 1: But I can also just train an AI agent to 260 00:13:18,480 --> 00:13:21,080 Speaker 1: do the same thing. So the very first people that 261 00:13:21,120 --> 00:13:24,240 Speaker 1: are going to be disrupted are the typical agents, the 262 00:13:24,320 --> 00:13:27,240 Speaker 1: gig workers. They're agents, and they're going to be replaced 263 00:13:27,280 --> 00:13:30,400 Speaker 1: with AI agents. Now, for if you have to drive 264 00:13:30,400 --> 00:13:32,640 Speaker 1: a ubercar, you might be a little bit more safe, 265 00:13:32,720 --> 00:13:36,080 Speaker 1: except unless if you've seen like Waymow driving around. These 266 00:13:36,080 --> 00:13:41,240 Speaker 1: are autonomous taxis as well. Okay, And what we're really 267 00:13:41,280 --> 00:13:44,920 Speaker 1: witnessing is something much bigger than that. Because as big 268 00:13:45,000 --> 00:13:48,480 Speaker 1: as that is, to replace all those agents all across 269 00:13:48,520 --> 00:13:52,040 Speaker 1: the world, researchers and writers and copywriters and video editors, 270 00:13:52,320 --> 00:13:56,720 Speaker 1: replace all those agents with AI agents, it's even something bigger. 271 00:13:56,840 --> 00:13:59,760 Speaker 1: If you're an entrepreneur, watch out. What we're really witnessing 272 00:13:59,840 --> 00:14:02,080 Speaker 1: is the collapse of scarcity. 273 00:14:02,160 --> 00:14:03,000 Speaker 2: What do I mean by that? 274 00:14:03,520 --> 00:14:08,480 Speaker 1: So all value is derived from scarcity and utility, and 275 00:14:08,559 --> 00:14:11,960 Speaker 1: so when you have scarcity, it increases the value most times. 276 00:14:12,040 --> 00:14:14,959 Speaker 1: So for example, if I'm a doctor, if I'm an attorney, 277 00:14:15,240 --> 00:14:17,120 Speaker 1: if I'm a coder, I have. 278 00:14:17,040 --> 00:14:19,240 Speaker 2: Information or knowledge that most people just don't have. 279 00:14:19,600 --> 00:14:22,040 Speaker 1: I went to school for five years or ten years 280 00:14:22,120 --> 00:14:25,160 Speaker 1: to learn this information. I went to school to learn coding, 281 00:14:25,240 --> 00:14:27,920 Speaker 1: so I have scarce information most people don't have, and 282 00:14:27,960 --> 00:14:32,040 Speaker 1: I'm paid a premium for that. But what happens when 283 00:14:32,160 --> 00:14:37,240 Speaker 1: knowledge is infinite and it's free, does it lose value? 284 00:14:37,840 --> 00:14:39,720 Speaker 1: So what we see is that back in the day, 285 00:14:39,800 --> 00:14:43,120 Speaker 1: the information was the moat. That's why the attorneys and 286 00:14:43,120 --> 00:14:45,080 Speaker 1: the doctor are able to charge that. But when an 287 00:14:45,080 --> 00:14:49,520 Speaker 1: AI has way more data information than any attorney or 288 00:14:49,560 --> 00:14:52,960 Speaker 1: any doctor, or can write code faster than any coder, 289 00:14:53,320 --> 00:14:57,880 Speaker 1: then what happens to that specialty knowledge the collapse of scarcity. 290 00:14:58,080 --> 00:15:00,600 Speaker 1: So we can take a couple examples from his So 291 00:15:00,640 --> 00:15:02,280 Speaker 1: here's a picture of when. 292 00:15:03,680 --> 00:15:04,840 Speaker 2: Scarcity changed. 293 00:15:05,040 --> 00:15:09,600 Speaker 1: When we went from transportation being done by horses nineteen 294 00:15:09,800 --> 00:15:15,080 Speaker 1: hundred to transportation being done by cars nineteen thirteen. This 295 00:15:15,200 --> 00:15:19,040 Speaker 1: is the same street, only thirteen years difference. But you 296 00:15:19,120 --> 00:15:22,640 Speaker 1: don't see a single horse in this picture, nor do 297 00:15:22,640 --> 00:15:25,000 Speaker 1: you see a single car in that picture. Now we 298 00:15:25,040 --> 00:15:28,480 Speaker 1: can see how quickly this changed, and we can see 299 00:15:28,480 --> 00:15:33,440 Speaker 1: here that horses fell off of a cliff while automobiles 300 00:15:33,720 --> 00:15:37,320 Speaker 1: went up in really rapid time. Now we use something 301 00:15:37,360 --> 00:15:39,160 Speaker 1: to might recognize this. I talk about it quite often 302 00:15:39,200 --> 00:15:39,880 Speaker 1: in technology. 303 00:15:39,920 --> 00:15:41,160 Speaker 2: We call it an s curve. 304 00:15:41,440 --> 00:15:43,360 Speaker 1: The time it takes to get to ten percent adoption 305 00:15:43,760 --> 00:15:45,120 Speaker 1: is about the same time it takes to get to 306 00:15:45,200 --> 00:15:49,360 Speaker 1: about eighty or ninety percent adoption. So we can see 307 00:15:49,400 --> 00:15:53,680 Speaker 1: how quickly this happening. Now this time were the horses. 308 00:15:54,080 --> 00:15:58,320 Speaker 1: This time, humans are being replaced with ais that can 309 00:15:58,400 --> 00:16:01,440 Speaker 1: write the code, that can drive the and do more. 310 00:16:01,560 --> 00:16:03,640 Speaker 1: As a matter of fact, let me just show you 311 00:16:03,960 --> 00:16:07,560 Speaker 1: how well some of this technology works to replacing programmers. 312 00:16:07,560 --> 00:16:09,160 Speaker 1: For example, let's watch this short video. 313 00:16:10,000 --> 00:16:13,480 Speaker 3: You always wondered why that app didn't exist. Now you 314 00:16:13,480 --> 00:16:17,560 Speaker 3: can make it. Meet replet agent. Want a custom workout plan, 315 00:16:18,200 --> 00:16:20,960 Speaker 3: Make an app for that. Have a great idea at 316 00:16:21,000 --> 00:16:24,760 Speaker 3: two am, Make an app for that. Need to run 317 00:16:24,760 --> 00:16:28,800 Speaker 3: an analysis or learn with your kids. Make an app 318 00:16:28,800 --> 00:16:35,360 Speaker 3: for that too. This isn't just making apps. This is 319 00:16:35,400 --> 00:16:40,200 Speaker 3: your imagination unleashed. Describe what you want and watch it 320 00:16:40,200 --> 00:16:44,600 Speaker 3: come to life, no coding experience, right from your phone. 321 00:16:45,680 --> 00:16:49,400 Speaker 3: Made an awesome app, share it with a friend, have 322 00:16:49,440 --> 00:16:51,840 Speaker 3: a business idea, start in minutes. 323 00:16:52,320 --> 00:16:55,080 Speaker 1: Okay, so what you just watched was a company called replet. 324 00:16:55,200 --> 00:16:58,000 Speaker 1: You can just go there and you can literally speak 325 00:16:58,080 --> 00:17:00,520 Speaker 1: into it or type a description of something that you 326 00:17:00,560 --> 00:17:03,520 Speaker 1: want and it can just build the app. So for example, 327 00:17:03,560 --> 00:17:05,879 Speaker 1: I could just say, hey, I'd like a financial management 328 00:17:05,920 --> 00:17:08,240 Speaker 1: app or I'd like a stock screen and app, and 329 00:17:08,280 --> 00:17:09,680 Speaker 1: it can just like literally build it for me. And 330 00:17:09,760 --> 00:17:11,280 Speaker 1: I was like, well, I don't really like it to 331 00:17:11,280 --> 00:17:12,840 Speaker 1: do that. I'd like to add these features, and then 332 00:17:12,840 --> 00:17:16,480 Speaker 1: it just adds those features like from verbal text. Anybody 333 00:17:16,560 --> 00:17:18,920 Speaker 1: now could create an app and they're doing. 334 00:17:18,760 --> 00:17:20,320 Speaker 2: It on replet. 335 00:17:20,520 --> 00:17:23,120 Speaker 1: Now what does this mean. What it means is that 336 00:17:23,240 --> 00:17:24,639 Speaker 1: every mote is destroyed. 337 00:17:24,920 --> 00:17:26,679 Speaker 2: AI has destroyed it. So think about this. 338 00:17:27,040 --> 00:17:29,600 Speaker 1: So in a future not too far away, like a 339 00:17:29,680 --> 00:17:32,720 Speaker 1: year from now, I could literally have an AI agent 340 00:17:32,760 --> 00:17:35,400 Speaker 1: that I could say, go out and find the top 341 00:17:35,480 --> 00:17:39,560 Speaker 1: ten online businesses and come back with a full report. 342 00:17:39,680 --> 00:17:41,680 Speaker 1: And it's like okay, like drop shipping is really good, 343 00:17:41,680 --> 00:17:44,360 Speaker 1: and e commerce is really good, and Airbnb is really good, 344 00:17:44,359 --> 00:17:46,399 Speaker 1: and it gives me these reports and I'm like cool, 345 00:17:47,480 --> 00:17:50,359 Speaker 1: just go copy and beat all of them. And that 346 00:17:50,480 --> 00:17:53,320 Speaker 1: AI agent can now go hire other A agents to 347 00:17:53,400 --> 00:17:55,879 Speaker 1: do the research and do the copywriting and do the 348 00:17:55,960 --> 00:17:58,120 Speaker 1: video editing and come up with the graphics because now 349 00:17:58,119 --> 00:18:00,439 Speaker 1: it can make images by itself, and it could do 350 00:18:00,560 --> 00:18:02,320 Speaker 1: the listings, and it can list the things and it 351 00:18:02,359 --> 00:18:05,000 Speaker 1: can run the ads. They can do all that in 352 00:18:05,040 --> 00:18:08,639 Speaker 1: a blink of an eye. What happens to every business 353 00:18:09,000 --> 00:18:12,160 Speaker 1: that we know in the world today, Everyone just gets 354 00:18:12,200 --> 00:18:16,399 Speaker 1: completely disrupted and upended on a daily basis, over and 355 00:18:16,480 --> 00:18:18,920 Speaker 1: over and over. What happens to the economy. We're talking 356 00:18:18,960 --> 00:18:22,960 Speaker 1: about an economic domino effect that we just can't even 357 00:18:23,000 --> 00:18:27,080 Speaker 1: quite comprehend. In the grand narrative of technological evolution, we 358 00:18:27,119 --> 00:18:30,400 Speaker 1: are transitioning from the age of information. That's where we work, 359 00:18:30,440 --> 00:18:34,399 Speaker 1: from industrial age to information age. A small business owner, 360 00:18:34,520 --> 00:18:37,320 Speaker 1: are you buried in all types of work keeping you 361 00:18:37,359 --> 00:18:39,920 Speaker 1: from the real thing that makes you money? Well, that's 362 00:18:39,960 --> 00:18:41,960 Speaker 1: where just Works comes in. They're the all in one 363 00:18:41,960 --> 00:18:45,280 Speaker 1: platform that supports small business growth. You can get all 364 00:18:45,359 --> 00:18:48,560 Speaker 1: their tools that help with benefits like payroll and HR 365 00:18:48,680 --> 00:18:52,720 Speaker 1: and compliance with transparent pricing. Now they help you hire 366 00:18:52,760 --> 00:18:57,439 Speaker 1: top talent internationally, internew markets, quickly scale international operations without 367 00:18:57,480 --> 00:19:00,560 Speaker 1: the workload, and for every how do I do question? 368 00:19:00,680 --> 00:19:03,040 Speaker 1: You can reach out to their expert staff from sole 369 00:19:03,119 --> 00:19:04,359 Speaker 1: proprietor or. 370 00:19:04,320 --> 00:19:05,080 Speaker 2: A team of twenty. 371 00:19:05,480 --> 00:19:09,080 Speaker 1: Just Works empowers all kinds of small businesses with real 372 00:19:09,200 --> 00:19:13,520 Speaker 1: human support. So visit justworks dot com, slash podcast, to 373 00:19:13,640 --> 00:19:16,560 Speaker 1: join the thousands of small businesses that trust Just Works 374 00:19:16,680 --> 00:19:20,119 Speaker 1: to take care of payroll, benefits, compliance, and more. Again 375 00:19:20,280 --> 00:19:28,080 Speaker 1: that's Justworks dot com slash podcasts to now the age 376 00:19:28,200 --> 00:19:32,600 Speaker 1: of intelligence. I love that, not just information. Everyone has information. 377 00:19:32,720 --> 00:19:35,600 Speaker 1: Now now we're going to the age of intelligence and 378 00:19:35,640 --> 00:19:41,000 Speaker 1: who has that. It's going to reshape society, revolutionize industries, 379 00:19:41,040 --> 00:19:44,639 Speaker 1: and change the nature of work. So technology always does. 380 00:19:45,240 --> 00:19:51,159 Speaker 1: It's a transformative shift. Promising advancements in healthcare, education, productivity 381 00:19:51,520 --> 00:19:54,000 Speaker 1: sounds great, there's always trade offs. 382 00:19:54,080 --> 00:19:54,960 Speaker 2: The downside is. 383 00:19:55,119 --> 00:20:00,200 Speaker 1: There's concerns of a large scale job loss, mental health repercussion, 384 00:20:00,640 --> 00:20:03,800 Speaker 1: and risk to social stability. So the whole world is 385 00:20:03,840 --> 00:20:06,800 Speaker 1: gonna change, and it's going to change rapidly. Again, we're 386 00:20:06,800 --> 00:20:10,000 Speaker 1: talking about months to years here. We're not talking about 387 00:20:10,000 --> 00:20:13,200 Speaker 1: decades at this point any longer, because it's here. Now. Look, 388 00:20:13,200 --> 00:20:15,000 Speaker 1: i'm gonna show you what we're gonna do about this. Listen, 389 00:20:15,000 --> 00:20:17,639 Speaker 1: it's not a doomingoand video. I'm excited. You can probably tell, 390 00:20:17,880 --> 00:20:20,200 Speaker 1: so hopefully I can get you excited as well. Now, 391 00:20:21,080 --> 00:20:23,719 Speaker 1: what we're seeing already and then we're going to continue 392 00:20:23,720 --> 00:20:28,320 Speaker 1: to see rapidly is the rise of these autonomous economies 393 00:20:29,040 --> 00:20:33,080 Speaker 1: autonomous economies. So this is again, if you go to Phoenix, Arizona, 394 00:20:33,119 --> 00:20:35,520 Speaker 1: you have these way more taxis driving all over the place. 395 00:20:35,760 --> 00:20:38,919 Speaker 1: And imagine that taxi is autonomous and it can just 396 00:20:38,960 --> 00:20:41,200 Speaker 1: drive itself, and it could make money on its own, 397 00:20:41,359 --> 00:20:43,000 Speaker 1: and it can go get its own service and all 398 00:20:43,040 --> 00:20:45,280 Speaker 1: these things. And so what we're seeing is autonomous economies 399 00:20:45,280 --> 00:20:48,639 Speaker 1: where now we have AI agents that can go hire 400 00:20:48,920 --> 00:20:52,280 Speaker 1: other AI agents. Again, so I task my agent to 401 00:20:52,320 --> 00:20:55,960 Speaker 1: go duplicate this e comm drop shipping site, for example, 402 00:20:56,160 --> 00:20:58,919 Speaker 1: and it hires other agents to build the website, another 403 00:20:58,960 --> 00:21:01,119 Speaker 1: agent to run the Facebook. It's another agent to go 404 00:21:01,119 --> 00:21:04,000 Speaker 1: get the quotes from China, another agent to manage the 405 00:21:04,000 --> 00:21:07,399 Speaker 1: logistics in the shipping, another agent, and you get the idea. 406 00:21:07,480 --> 00:21:09,679 Speaker 1: So I could get one agent that goes and hires 407 00:21:09,720 --> 00:21:13,760 Speaker 1: the other agents. That's the autonomous economy. Then the agents 408 00:21:14,080 --> 00:21:18,000 Speaker 1: have to pay the other agents for the services. So 409 00:21:18,040 --> 00:21:22,000 Speaker 1: now my agent needs the ability to have money and 410 00:21:22,080 --> 00:21:26,080 Speaker 1: be able to make payments to other agents for the services, 411 00:21:26,119 --> 00:21:29,800 Speaker 1: and they're paying other agents. When machines run economies, what 412 00:21:29,880 --> 00:21:34,439 Speaker 1: happens to traditional currencies, banks and even governments. Now, again, 413 00:21:34,480 --> 00:21:36,400 Speaker 1: this is not some far off thing as a matter 414 00:21:36,400 --> 00:21:39,120 Speaker 1: of fact, it's happening right now today. Let me show 415 00:21:39,160 --> 00:21:41,720 Speaker 1: you exactly what I'm talking about. This is a long video. 416 00:21:41,760 --> 00:21:43,720 Speaker 1: I'm not going to actually show you the video clip 417 00:21:43,760 --> 00:21:45,240 Speaker 1: of it. We can put it in the show notes 418 00:21:45,240 --> 00:21:46,800 Speaker 1: down below if you want to watch it. But what 419 00:21:46,840 --> 00:21:49,400 Speaker 1: we have right here is a Replet ai agent. It's 420 00:21:49,440 --> 00:21:51,320 Speaker 1: what I showed you earlier, so you can use replet 421 00:21:51,320 --> 00:21:54,240 Speaker 1: to build yourself an AI agent. So Replet ai agent 422 00:21:54,600 --> 00:21:57,679 Speaker 1: went out and searched and found a domain name. They 423 00:21:57,680 --> 00:21:59,960 Speaker 1: found a domain name that fit the criteria the experts, 424 00:22:00,920 --> 00:22:03,800 Speaker 1: and it bought it and paid for it all on 425 00:22:03,840 --> 00:22:07,480 Speaker 1: its own. It purchases a domain name using bitcoin over 426 00:22:07,520 --> 00:22:11,080 Speaker 1: the Lightning network. Bitcoin will be the currency of AI. 427 00:22:11,400 --> 00:22:13,239 Speaker 1: So this guy has this video where he shows how 428 00:22:13,280 --> 00:22:15,600 Speaker 1: he built it, shows the whole transaction. You can watch 429 00:22:15,600 --> 00:22:17,880 Speaker 1: the video go down from the researching to the domain name, 430 00:22:17,920 --> 00:22:20,600 Speaker 1: to the whole thing, to buying it, taking ownership, and 431 00:22:20,600 --> 00:22:22,560 Speaker 1: then the AI could the agent continue to build up 432 00:22:22,560 --> 00:22:25,600 Speaker 1: the website and everything. So it literally is not it's 433 00:22:25,640 --> 00:22:28,120 Speaker 1: literally happening right now. This is not a future thing. 434 00:22:28,480 --> 00:22:31,919 Speaker 1: This is right now, this is today. Now, what are 435 00:22:31,920 --> 00:22:35,080 Speaker 1: we expecting from this? We're expecting big things. The market 436 00:22:35,119 --> 00:22:38,760 Speaker 1: size of transactions among AI agents is expected to be 437 00:22:39,000 --> 00:22:43,000 Speaker 1: one hundred times larger than human transactions. Why would it 438 00:22:43,040 --> 00:22:47,520 Speaker 1: be one hundred times larger. Well, because every individual will 439 00:22:47,520 --> 00:22:51,000 Speaker 1: probably have ten or more AI agents. I'll probably have 440 00:22:51,040 --> 00:22:54,159 Speaker 1: like one hundred, how many will you have? Now, the 441 00:22:54,200 --> 00:22:56,760 Speaker 1: transaction frequency among A agents is going to be ten 442 00:22:56,800 --> 00:23:00,200 Speaker 1: times greater than that among humans. So these aia is 443 00:23:00,240 --> 00:23:02,600 Speaker 1: going to be working really really fast. So not only 444 00:23:02,640 --> 00:23:04,080 Speaker 1: will I have ten of them or twenty or fifty 445 00:23:04,119 --> 00:23:06,000 Speaker 1: or one hundred of them, they might be doing ten 446 00:23:06,080 --> 00:23:09,600 Speaker 1: and fifty one hundred transactions a day each. So we're 447 00:23:09,600 --> 00:23:12,480 Speaker 1: talking about something really really massive. I mean, this is 448 00:23:12,520 --> 00:23:16,520 Speaker 1: all again, this is happening right now. But here's the problem. 449 00:23:17,160 --> 00:23:21,439 Speaker 1: How much does this cost? If I have an AI agent? Right, 450 00:23:21,640 --> 00:23:24,199 Speaker 1: if I want to hire a customer service person in 451 00:23:24,240 --> 00:23:26,880 Speaker 1: the Philippines, I might pay them six to eight bucks 452 00:23:26,920 --> 00:23:30,320 Speaker 1: an hour. If I want to hire a coder in Pakistan, 453 00:23:30,560 --> 00:23:33,320 Speaker 1: I might pay them nine to fourteen dollars an hour. Right. 454 00:23:33,320 --> 00:23:35,840 Speaker 1: If I want to hire a legal researcher in Europe 455 00:23:35,840 --> 00:23:38,200 Speaker 1: and Eastern Europe, maybe I pay them fifteen to twenty 456 00:23:38,200 --> 00:23:40,399 Speaker 1: five bucks an hour. But how much does it cost 457 00:23:41,200 --> 00:23:44,840 Speaker 1: for me to have an AI agent hire another AI agent. 458 00:23:45,240 --> 00:23:48,040 Speaker 1: Will they charge more based off of their expertise? How 459 00:23:48,080 --> 00:23:51,360 Speaker 1: much will they charge, Well, they're going to be charging 460 00:23:52,080 --> 00:23:54,719 Speaker 1: the cost will to cover their costs? Well, what are 461 00:23:54,720 --> 00:23:57,919 Speaker 1: the costs? Well, I guess one to program the agent. 462 00:23:58,280 --> 00:24:01,840 Speaker 1: Number two, it's the cost of the power, their electricity 463 00:24:02,520 --> 00:24:06,640 Speaker 1: and the compute the CPU, the GPU compute energy will 464 00:24:06,680 --> 00:24:08,320 Speaker 1: be the costs they're going to have to pay. But 465 00:24:08,400 --> 00:24:12,040 Speaker 1: here's the problem. Our traditional financial system that we have 466 00:24:12,119 --> 00:24:15,000 Speaker 1: today is not set up to do this. It will 467 00:24:15,000 --> 00:24:17,320 Speaker 1: not work for what these are doing. And it's not 468 00:24:17,359 --> 00:24:19,320 Speaker 1: a future thing. This is right now today. As I 469 00:24:19,359 --> 00:24:21,640 Speaker 1: just showed you, an AI agent just went and bought 470 00:24:21,680 --> 00:24:24,320 Speaker 1: a domain with bitcoin lightning right now. But it can't 471 00:24:24,320 --> 00:24:27,600 Speaker 1: work with the traditional financial system because the traditional financial 472 00:24:27,640 --> 00:24:30,680 Speaker 1: system has way well it's just too archaic closer you 473 00:24:30,720 --> 00:24:33,960 Speaker 1: say that, way too much friction. So, for example, the 474 00:24:34,000 --> 00:24:37,639 Speaker 1: current FIAT and KYC, which is know your customer systems 475 00:24:37,880 --> 00:24:43,199 Speaker 1: are designed for humans inherently excluding AI agents. So in 476 00:24:43,280 --> 00:24:45,679 Speaker 1: order to get a bank account, a debit card, a 477 00:24:45,720 --> 00:24:47,840 Speaker 1: credit card, a Venmo account, you have to be a 478 00:24:47,880 --> 00:24:51,760 Speaker 1: human and you have to pass KYC and AML regulations. 479 00:24:52,040 --> 00:24:55,880 Speaker 1: It's set up specifically to not allow agents to have that. However, 480 00:24:56,160 --> 00:24:59,639 Speaker 1: the stringent KYC, the Know Your Customer requirements, and FIAT 481 00:24:59,640 --> 00:25:05,680 Speaker 1: system inherently exclude AI agent's So AI agents can't work 482 00:25:05,680 --> 00:25:09,359 Speaker 1: in the traditional financial system, but it's here. They're change 483 00:25:09,400 --> 00:25:12,400 Speaker 1: in the world. There's no stopping it. So then what happens, 484 00:25:13,400 --> 00:25:16,440 Speaker 1: Like I said, there's so much friction? What kind of friction? Well, 485 00:25:16,480 --> 00:25:18,639 Speaker 1: we can see here financial service is built on the 486 00:25:18,640 --> 00:25:23,240 Speaker 1: assumption that there's an accountable, legally recognized human or at 487 00:25:23,320 --> 00:25:27,600 Speaker 1: least a corporate entity behind every transaction. Who's liable? Right 488 00:25:28,680 --> 00:25:32,240 Speaker 1: as an AI agent operates independently, it doesn't easily fit 489 00:25:32,359 --> 00:25:38,880 Speaker 1: into these frameworks, making compliance both technically challenging and legally uncertain. 490 00:25:38,920 --> 00:25:42,480 Speaker 1: Who are we going to sue? Who's liable? A solution 491 00:25:42,880 --> 00:25:47,080 Speaker 1: that sidesteps the limitations of traditional finance while addressing security 492 00:25:47,720 --> 00:25:52,000 Speaker 1: is of course bitcoin, so we can sidestep this. Now, 493 00:25:52,040 --> 00:25:53,720 Speaker 1: there's a couple of things that we can think about here. 494 00:25:54,680 --> 00:25:57,119 Speaker 1: Why not credit cards? Mark Well, the credit card system 495 00:25:57,160 --> 00:26:00,439 Speaker 1: simply isn't built for machine to machine payments, is riddled 496 00:26:00,440 --> 00:26:06,400 Speaker 1: with inefficiencies, high transaction fees, and privacy compliance issues. It's 497 00:26:06,520 --> 00:26:10,760 Speaker 1: unsuitable for autonomous agents. You may not know this, but 498 00:26:11,080 --> 00:26:13,720 Speaker 1: it's pretty much impossible to send somebody somewhere else in 499 00:26:13,720 --> 00:26:18,520 Speaker 1: the world like thirty five cents. Transactions cost more than that. Now, 500 00:26:18,680 --> 00:26:21,680 Speaker 1: what happens when these AI agents are making these micro transactions, 501 00:26:21,720 --> 00:26:24,280 Speaker 1: When they're doing so one hundred times a day or 502 00:26:24,320 --> 00:26:28,119 Speaker 1: one thousand times a day, that fifty dollars one hundred 503 00:26:28,119 --> 00:26:30,640 Speaker 1: dollars could get eaten up in fees with one hundred 504 00:26:30,760 --> 00:26:34,800 Speaker 1: or a thousand transactions back and forth. It's unsuitable. There's 505 00:26:34,840 --> 00:26:40,320 Speaker 1: no compliance, there's no liability or legality there. Furthermore, blockchain 506 00:26:40,320 --> 00:26:44,280 Speaker 1: transparency and immutability. The immutability of the blockchain meaning once 507 00:26:44,280 --> 00:26:46,520 Speaker 1: I make the transaction, I can't be charged back, offer 508 00:26:46,560 --> 00:26:50,199 Speaker 1: a unique advantage. Every transaction executed by the AI is 509 00:26:50,240 --> 00:26:53,240 Speaker 1: recorded on chain, so now we have a transparent layer. 510 00:26:53,440 --> 00:26:55,560 Speaker 1: Then we can see all the transactions that are happening. 511 00:26:55,720 --> 00:26:58,679 Speaker 1: This makes crypto wile it's a suitable infrastructure for autonomous 512 00:26:58,720 --> 00:27:03,720 Speaker 1: agents in the finance world, meaning it's the only way. 513 00:27:04,520 --> 00:27:07,560 Speaker 1: You have to understand that as technology changes, it doesn't stop. 514 00:27:08,080 --> 00:27:12,840 Speaker 1: It doesn't wait for things to change. Technology is what 515 00:27:12,960 --> 00:27:17,720 Speaker 1: changes things. Back in the gunpowder Revolution in the fifteen hundreds. 516 00:27:18,880 --> 00:27:20,919 Speaker 1: All of a sudden it changed the balance of power. 517 00:27:21,000 --> 00:27:24,440 Speaker 1: Were one person one surf with a gun could take 518 00:27:24,480 --> 00:27:27,560 Speaker 1: out one hundred nights. And when the gunpowder Revolution starts 519 00:27:27,560 --> 00:27:30,040 Speaker 1: sweeping across the world, it wasn't like a nice to have. 520 00:27:30,280 --> 00:27:32,240 Speaker 1: It wasn't like, well maybe i'll have guns or I won't. 521 00:27:32,280 --> 00:27:35,000 Speaker 1: It was like you better have it. It's what changed 522 00:27:35,000 --> 00:27:37,320 Speaker 1: the world. It didn't wait for things. And the AI 523 00:27:37,400 --> 00:27:40,399 Speaker 1: agents are here. They're changing things in the system that 524 00:27:40,440 --> 00:27:42,840 Speaker 1: we have now won't work and this is all inevitable, 525 00:27:42,920 --> 00:27:45,720 Speaker 1: all right now, The real catalyst of all of this 526 00:27:46,280 --> 00:27:50,480 Speaker 1: is bitcoin plus AI. You see, when technology advances the world, 527 00:27:50,480 --> 00:27:53,520 Speaker 1: it's not about a single technology, it's about multiple things 528 00:27:53,560 --> 00:27:56,119 Speaker 1: coming together to give us a new set of building 529 00:27:56,119 --> 00:27:59,000 Speaker 1: blocks to build things that we've never imagined. So, for example, 530 00:27:59,000 --> 00:28:01,400 Speaker 1: it wasn't just the automobile. If we had the automod bile, 531 00:28:01,480 --> 00:28:03,800 Speaker 1: we had no oil and oil fuels, we couldn't drive it. 532 00:28:04,119 --> 00:28:06,359 Speaker 1: If we didn't have mass production, we couldn't make them. 533 00:28:06,600 --> 00:28:09,159 Speaker 1: So we have to get these clusters of technology that 534 00:28:09,200 --> 00:28:11,560 Speaker 1: come together. So really the catalyst is how bitcoin and 535 00:28:11,720 --> 00:28:15,080 Speaker 1: AI come together. Now you might be asking yourself, Mark, 536 00:28:15,520 --> 00:28:20,199 Speaker 1: why Bitcoin? Why Bitcoin? Well, first of all, it's not 537 00:28:20,280 --> 00:28:28,440 Speaker 1: only borderless and censors resistant and immutable, permissionless, it's also personless. Right, 538 00:28:28,560 --> 00:28:31,080 Speaker 1: so again you can't get a bank account or Venmo 539 00:28:31,160 --> 00:28:35,199 Speaker 1: account without being a person. But bitcoin is personless. The 540 00:28:35,240 --> 00:28:37,080 Speaker 1: other reason, well, you might say, but what about the 541 00:28:37,080 --> 00:28:39,680 Speaker 1: other two point four million cryptos that are out there, 542 00:28:39,680 --> 00:28:43,360 Speaker 1: because those could be personalless. Also, well, bitcoin is the 543 00:28:43,400 --> 00:28:47,640 Speaker 1: only one that's really energy backed. It's an energy back system. Now, 544 00:28:47,960 --> 00:28:50,680 Speaker 1: remember what is the cost for AI agents to hire 545 00:28:50,720 --> 00:28:54,400 Speaker 1: other AI agents the cost of their energy. So AI 546 00:28:54,480 --> 00:28:56,280 Speaker 1: is going to understand this very well. They're going to 547 00:28:56,360 --> 00:28:59,960 Speaker 1: understand that one is a decentralized system that nobody can control, 548 00:29:00,040 --> 00:29:02,600 Speaker 1: nobody can censor, nobody can change, and there's a true 549 00:29:02,680 --> 00:29:06,200 Speaker 1: cost of input and economic energy input into it. And 550 00:29:06,240 --> 00:29:10,320 Speaker 1: they're going to demand having an economic energy input money 551 00:29:10,400 --> 00:29:14,560 Speaker 1: as well. We can see that it's also instant, it's borderless. 552 00:29:14,720 --> 00:29:16,720 Speaker 1: And really we have to understand history. We have to 553 00:29:16,800 --> 00:29:18,880 Speaker 1: understand these technology cycles. You see me to use these 554 00:29:18,920 --> 00:29:22,840 Speaker 1: charts before. Now, technology cycles they happen about every fifty years. 555 00:29:22,880 --> 00:29:26,080 Speaker 1: I call them quantum waves, and they have these four 556 00:29:26,360 --> 00:29:30,800 Speaker 1: distinct periods that happen. Each one of these cycles has 557 00:29:30,840 --> 00:29:34,840 Speaker 1: its own unique attributes. In this cycle from twenty thirty 558 00:29:34,880 --> 00:29:37,320 Speaker 1: to twenty forty, which we'll be going into in the 559 00:29:37,360 --> 00:29:40,440 Speaker 1: next couple of years, is really what's called the adoption 560 00:29:40,560 --> 00:29:42,360 Speaker 1: or the synergy phase. Remember I talked about the S 561 00:29:42,480 --> 00:29:45,680 Speaker 1: curve before. You can see how the S curve sort 562 00:29:45,720 --> 00:29:49,040 Speaker 1: of fits over this. See that this is the adoption wave. 563 00:29:49,200 --> 00:29:54,080 Speaker 1: So this is where bitcoin really becomes as adopted as 564 00:29:54,200 --> 00:29:57,880 Speaker 1: this medium of exchange. Remember, all things or money, I 565 00:29:57,920 --> 00:30:01,080 Speaker 1: should say, is always an evolutionary process. So it starts 566 00:30:01,120 --> 00:30:04,520 Speaker 1: as a collectible. It could evolve, not always, but sometimes 567 00:30:04,520 --> 00:30:05,920 Speaker 1: evolves to a store value. 568 00:30:06,080 --> 00:30:07,640 Speaker 2: This is where we're at right now. 569 00:30:08,040 --> 00:30:10,880 Speaker 1: In this next phase, it becomes the medium of exchange. 570 00:30:11,320 --> 00:30:14,720 Speaker 1: It's where it becomes that transaction layer, and it eventually 571 00:30:14,800 --> 00:30:17,280 Speaker 1: becomes what we call a unit of account. Now, a 572 00:30:17,320 --> 00:30:19,640 Speaker 1: lot of people would say, well, why aren't we using 573 00:30:19,680 --> 00:30:22,360 Speaker 1: bitcoin for transactions? Now? Where can I go to the 574 00:30:22,400 --> 00:30:24,120 Speaker 1: store and buy my groceries with it? Or why am 575 00:30:24,120 --> 00:30:26,320 Speaker 1: I not buying coffee with it? All of these things, 576 00:30:26,320 --> 00:30:29,800 Speaker 1: And it's well, I would say, you fail to understand history, 577 00:30:30,000 --> 00:30:33,600 Speaker 1: and understand monetary history specifically. Now, of course, she has 578 00:30:33,800 --> 00:30:36,680 Speaker 1: seto sheet. I did say that bitcoin is a peer 579 00:30:36,680 --> 00:30:39,360 Speaker 1: to be electronic cash system, But as I just showed you, 580 00:30:39,560 --> 00:30:43,080 Speaker 1: there's an evolutionary process to this that takes us and 581 00:30:43,120 --> 00:30:44,760 Speaker 1: we have to go through EA stage one by one. 582 00:30:44,920 --> 00:30:46,880 Speaker 1: And what I'd say is, if you don't understand history, 583 00:30:46,920 --> 00:30:47,680 Speaker 1: you're bound to repeat it. 584 00:30:47,680 --> 00:30:49,440 Speaker 2: There's something called Gresham's. 585 00:30:48,960 --> 00:30:51,440 Speaker 1: Law, and the Gresham's law is that good money drives 586 00:30:51,480 --> 00:30:54,120 Speaker 1: out bad and so what that means is that as 587 00:30:54,120 --> 00:30:56,160 Speaker 1: long as there's bad money to use, I'll save the 588 00:30:56,160 --> 00:30:59,160 Speaker 1: good money. So if you're like a gold bug, for example, 589 00:30:59,200 --> 00:31:02,440 Speaker 1: you might know that up until in nineteen sixty five 590 00:31:03,240 --> 00:31:05,680 Speaker 1: in the United States, quarters and dimes were made of 591 00:31:05,720 --> 00:31:09,000 Speaker 1: real silver. Now you won't find a pre sixty five 592 00:31:09,080 --> 00:31:12,200 Speaker 1: quarter of diamond circulation today. You just you never get them. 593 00:31:12,360 --> 00:31:15,280 Speaker 1: Why is that because they've all been removed. Why is 594 00:31:15,320 --> 00:31:17,880 Speaker 1: that because people want to save them. Now, if for 595 00:31:17,920 --> 00:31:20,200 Speaker 1: some reason you just happened accidentally to get a pre 596 00:31:20,320 --> 00:31:23,000 Speaker 1: sixty five quarter a dime, would you spend it? And 597 00:31:23,040 --> 00:31:25,240 Speaker 1: the answer is of course no, you wouldn't. You'd be ridiculous. 598 00:31:25,280 --> 00:31:27,520 Speaker 1: Today you're going to save it because you can easily 599 00:31:27,520 --> 00:31:29,960 Speaker 1: spend the bad money and So that's exactly what we're 600 00:31:30,000 --> 00:31:33,800 Speaker 1: talking about here with bitcoin. In this case, it's evolving. 601 00:31:34,000 --> 00:31:35,520 Speaker 1: But as long as we can use FIAT, we're going 602 00:31:35,560 --> 00:31:36,360 Speaker 1: to continue to use it. 603 00:31:36,560 --> 00:31:39,040 Speaker 2: But the AI agents cannot. 604 00:31:39,560 --> 00:31:42,280 Speaker 1: That's what pushes the use case of this, meaning exchange, 605 00:31:42,360 --> 00:31:45,480 Speaker 1: when we can only use that instead of the other thing. Now, Also, 606 00:31:45,480 --> 00:31:49,160 Speaker 1: if you're in a Afghanistan, you're in North Korea, maybe 607 00:31:49,200 --> 00:31:51,400 Speaker 1: even you're in El Salvorey, you can't afford a bankccout. 608 00:31:51,400 --> 00:31:53,320 Speaker 1: There are other reasons why you could use bitcoin today. 609 00:31:53,720 --> 00:31:56,360 Speaker 1: But on a whole, when we're talking about mass adoption, 610 00:31:56,720 --> 00:31:59,960 Speaker 1: I believe this is the catalyst. Okay, now this all 611 00:32:00,200 --> 00:32:04,800 Speaker 1: sounds really scary, right. Your job's at risk, and I 612 00:32:04,880 --> 00:32:09,440 Speaker 1: mean that literally, even if you're an entrepreneur, even if 613 00:32:09,440 --> 00:32:12,960 Speaker 1: you're a doctor, high praise, high paid professional, you're probably 614 00:32:13,000 --> 00:32:15,920 Speaker 1: still at risk. So what does this mean, Well, a 615 00:32:15,960 --> 00:32:18,160 Speaker 1: couple things. Number One, we've got a couple of years. 616 00:32:18,960 --> 00:32:21,920 Speaker 1: This is happening really really fast, but we probably have 617 00:32:21,920 --> 00:32:23,880 Speaker 1: a couple of years. So what does that mean. Well, 618 00:32:23,920 --> 00:32:27,160 Speaker 1: I believe over the next three four years we have 619 00:32:27,240 --> 00:32:30,200 Speaker 1: this massive opportunity for investment to make a lot of money. 620 00:32:30,400 --> 00:32:32,760 Speaker 1: So you have a couple of years to make it 621 00:32:32,760 --> 00:32:35,320 Speaker 1: as much money as you can, because I don't know 622 00:32:35,320 --> 00:32:36,680 Speaker 1: what the world looks like on the other side of that, 623 00:32:36,840 --> 00:32:38,959 Speaker 1: all right, I don't know what the economy looks like 624 00:32:39,080 --> 00:32:41,920 Speaker 1: when all these get disrupted. What history shows us is 625 00:32:41,920 --> 00:32:46,480 Speaker 1: that when these new technologies come out, this creative disruption happens, happens, 626 00:32:46,760 --> 00:32:50,040 Speaker 1: and it creates problems. Now, it's not forever. I'm not 627 00:32:50,080 --> 00:32:52,520 Speaker 1: saying that there's no jobs for humans in the future. 628 00:32:52,560 --> 00:32:55,000 Speaker 1: I don't believe that at all. I believe that AI 629 00:32:55,200 --> 00:32:56,760 Speaker 1: is a tool and as humans, we just have to 630 00:32:56,840 --> 00:32:57,800 Speaker 1: learn how to use the tool. 631 00:32:57,920 --> 00:33:00,760 Speaker 2: But it can cause period of disruption. 632 00:33:01,120 --> 00:33:03,480 Speaker 1: For example, in the Industrial Revolution, when everybody worked in 633 00:33:03,520 --> 00:33:04,960 Speaker 1: the farm and then we had machines that could do 634 00:33:05,040 --> 00:33:06,840 Speaker 1: the work of thousands of men. What did all those 635 00:33:06,880 --> 00:33:07,560 Speaker 1: thousands of men do. 636 00:33:08,520 --> 00:33:09,920 Speaker 2: Well, Temporarily they didn't do. 637 00:33:09,960 --> 00:33:12,560 Speaker 1: Anything, but eventually went on to do higher value things 638 00:33:12,600 --> 00:33:15,840 Speaker 1: like science and medicine. So there's this temporary disruption. 639 00:33:16,320 --> 00:33:17,280 Speaker 2: But don't worry. 640 00:33:17,400 --> 00:33:19,640 Speaker 1: There's no future that I can see in the world 641 00:33:19,760 --> 00:33:23,120 Speaker 1: where humans no longer have problems. As long as there's problems, 642 00:33:23,360 --> 00:33:26,720 Speaker 1: there's solutions, there are services, and there's products for those things. 643 00:33:27,560 --> 00:33:30,080 Speaker 1: So we have a few years, so get your money 644 00:33:30,160 --> 00:33:32,840 Speaker 1: right while you can. Number two, you want to stack 645 00:33:33,000 --> 00:33:35,800 Speaker 1: your skills. So if you're that gig worker and you 646 00:33:35,880 --> 00:33:38,600 Speaker 1: have a skill, that's great. You know how to do 647 00:33:38,640 --> 00:33:41,240 Speaker 1: the research or the copywriting, you know how to do 648 00:33:41,280 --> 00:33:44,240 Speaker 1: the bookkeeping, that's great. But if you have one skill, 649 00:33:44,440 --> 00:33:46,520 Speaker 1: you'll be the first to be replaced. If you have 650 00:33:46,840 --> 00:33:49,120 Speaker 1: multiple skills that are stacked up, you're going to be 651 00:33:49,120 --> 00:33:51,040 Speaker 1: able to buy yourself some time. It's going to be 652 00:33:51,040 --> 00:33:53,880 Speaker 1: a while before these agents get so far advanced, so 653 00:33:53,960 --> 00:33:57,440 Speaker 1: really learn to stack your skills up on top of themselves. 654 00:33:57,560 --> 00:33:59,320 Speaker 1: The one thing I don't think the AIA agents will 655 00:33:59,360 --> 00:34:02,920 Speaker 1: be able to do is place our creativity. So stack 656 00:34:02,960 --> 00:34:04,680 Speaker 1: ups many skills as you can, and learn how to 657 00:34:04,760 --> 00:34:08,640 Speaker 1: apply them, create creatively to different solutions or as solutions 658 00:34:08,680 --> 00:34:11,560 Speaker 1: to different problems. And then finally stack your SATs. Stack 659 00:34:11,600 --> 00:34:13,840 Speaker 1: your skills, and stack your SATs. I'm talking about bitcoin 660 00:34:13,880 --> 00:34:16,920 Speaker 1: of course in this example, so we know that bitcoin 661 00:34:17,080 --> 00:34:19,840 Speaker 1: is only going up from here based off of this information. 662 00:34:19,880 --> 00:34:21,560 Speaker 1: Of course, if you believe it, and so you might 663 00:34:21,560 --> 00:34:23,360 Speaker 1: want to be stacking your SATs, and that's going to 664 00:34:23,400 --> 00:34:25,440 Speaker 1: be the way that you'll be able to defend yourself 665 00:34:25,480 --> 00:34:28,640 Speaker 1: against the technology that's happening. All right, hopefully that makes sense. Again, 666 00:34:28,680 --> 00:34:31,360 Speaker 1: this is super exciting for me. I'm using this stuff 667 00:34:31,400 --> 00:34:33,880 Speaker 1: in real life and it is making a massive impact 668 00:34:33,880 --> 00:34:36,640 Speaker 1: in my business. And you can either use it or 669 00:34:36,680 --> 00:34:38,319 Speaker 1: get left bind. Let me know which one you're gonna do. 670 00:34:38,520 --> 00:34:40,640 Speaker 1: Use it or get left bind. Lead me a comment 671 00:34:40,680 --> 00:34:42,680 Speaker 1: down below, let me know which one. Of course, give 672 00:34:42,680 --> 00:34:43,920 Speaker 1: me thumbs up if you like the video. If you don't, 673 00:34:43,920 --> 00:34:45,560 Speaker 1: you can give me thumbs down. That's okay, but at 674 00:34:45,600 --> 00:34:47,719 Speaker 1: least tell me why in the comments. That's what I got, 675 00:34:47,760 --> 00:34:50,000 Speaker 1: all right, see your success. I'm out.