The AI Bubble. Why Smart People are Losing Their Minds

We've seen this exact hysteria before. The famous neuroscientist and philosopher Sam Harris recently said that one of the most important books that he's ever read is this book from 1841, which is [music] extraordinary popular delusions and the madness of crowds. And the reason is simple. [music] For 400 years, every major mania hype cycle bubble has followed the same psychological script. [music] And we're running that script again perfectly right now with AI. [music] So if you want to be able to cut through the noise and understand what is real, what's hype, and what actually matters for your life and your career, what you need is a mental blueprint that isn't going to change every time the narrative does. As the very famous investor Sir John Templeton warned, the four most dangerous words in investing are, [music] "This time it's different." So here is our question. Is this the time that it is finally different? The blueprint we'll share here will help you separate [music] what is true from what is just tech CEO hype and PR. [music] It will also give you a rubric and a practical set of steps that you can take to futureroof yourself no matter where we are in this hype cycle. So to build this blueprint, we need to start [music] by winding back the clock nearly 400 years to a financial bubble that was so extreme that people literally sold their homes to buy a single flower. [music] Shared terminology. Before we build our blueprint, we need a shared language because a lot of words get thrown around a lot, very casually, but their specific meanings really, really matter. Mania. Mania is when collective belief becomes unmed from reality. It's when people stop thinking independently and rationally and critically and instead they just start following a story. And that story can be euphoric or it can be catastrophic. But it's this mass narrative that matters. A bubble is basically a mania with money attached, right? It's mass psychology plus capital. And we have had many, many bubbles throughout history. And we're going to talk more about these and why they're so important to understand in just a few minutes. Technology. Technology just means anything that extends human capability. It's important to understand that books were once technology. the printing press, the wheel, electricity, the combustion engine, semiconductors, and now we have large language models, aka artificial intelligence. Everything that feels ordinary today once felt very new and very confusing and very destabilizing and like it might change the face of the world forever. And every time without fail that one of these breakthroughs appear, people assume that this curve of innovation will keep rising forever. Think about the combustion engine. It transformed transportation almost overnight. But after that initial leap, right, what we saw was incremental progress. We went from horses to cars and that was insane. But then cars didn't suddenly start flying. They just became more efficient and more reliable, but they weren't revolutionary every single decade. Or we can look at space travel, right? In the 1960s, we put humans on the moon, which was insane. And we all thought that progress would continue at that pace. They were projecting lunar bases and Mars colonies and all this stuff, right? But instead, we've had plateaued progress, right? It's limited by physics and funding and incentives and all of these other things. And we've seen this happen again and again. The internet was one of the most transformative technologies in history. But we went through this same pattern, right? It was explosive early growth, huge expectations, and then this long period that it took for the reality to catch up. AI will follow a similar pattern. It's going to have this huge leap forward which is undeniably miraculous, but there is going to be constraints on its adoption. physics, data, compute, regulation, all of these things are going to constrain how fast it can grow. And I'm not being pessimistic. I'm very excited about AI and what it can do. It's just a more accurate baseline for thinking about what's actually happening here. So, what history teaches us about mania? To understand what's happening with AI, we [clears throat] got to start by looking backwards because we know that history rhymes, right? Regalio says this all the time because the pattern that we [clears throat] are living through now is not new. It may feel faster or different up close but it's so old that is almost predictable. And the clearest way to understand what is happening to us right now is to look at what's happened in the past because there's this long history of technologies promising more than they could deliver. Tulip mania 1630s tulips were a rare luxury good in the Netherlands which became at the time a status symbol right and what we saw at that time was traders started buying and selling futures contracts for tulip bulbs that had not even been grown anyway it fell that whole thing fell apart in February of 1637 I think buyers suddenly failed to show up at auction uh to buy these futures contracts and basically overnight confidence in the whole market evaporated and because these contracts were leveraged and legally uninforceable, the market cratered. Prices fell like 99% in a matter of days and people had literally traded homes and life savings and everything that they held dear to buy these uh contracts and they were left with nothing. And you could fast forward to today and see that tulips were basically the NFTs of the 1600s. They were valuable only as long as the story about them held. We can then fast forward to 1720. The South Sea bubble. So the South Sea company was an was a private company, right? And what they had done was promised these huge profits from train. They they speculated, okay? Much like what is happening today. They made huge promises about profits that would come with uh from trade with Spanish South America. And it was all based on these things that they never actually had rights to. And it was basically reinforced by government. and people were allowed to buy shares of this thing on uh credit and it created this massive spike this massive spike in share price. Ultimately this whole thing fell apart. The company had basically no real revenue. They had leaders engaged in insider trading and then when the internal folks started selling their shares the whole thing collapsed. The stock collapsed by 80% overnight. It bankrupted thousands of people there. Then all of a sudden the government was looking into it. they've launched his inquiry, you know. So, what do we learn from this? Promises are promises until they meet reality. When we see these valuations rise faster than on any of the corresponding real world things, the underlying revenue, the real technology, what it's actually delivering in the enterprise and so forth, then collapse is maybe not eminent, but becomes highly likely, right? because the fundamentals of what's being promised differ wildly from the narrative that's being told about it. We can think about the promises they were making basically as AGI in two years of its era, right? It's these huge promises with very weak fundamentals. And we see this pattern happen again and again both with technologies and with prominent leaders. So we can look at Edison and the electrification hype of the late 1800s, right? And this technology electrification was re was marketed basically as a force that would remake civilization and it did but nowhere near on the timeline that was promised and not without huge stumbling blocks all along the way. We can basically think of Edison, even though he's sort of lion eyes now, as the Musk of his time where he was dramatically overstating the capabilities of his technologies. And they both have this uncanny knack of tying their innovations as to a thing that's going to dramatically improve, you know, human living. even though at the end of the day a Tesla may be even more environmentally dilitterious than a regular car. Right? So we can look back in Edison and see this string of failures of big promises of he had an ormilling plant that turned into a huge disaster. He was talking about concrete houses that were supposed to change the world that was abandoned. He had an electric pen that flopped. He actually he actually started uh I believe with early electric cars but there was all sorts of you know it was too early basically for the technology. So what does this teach us? We have to be able to see through the marketing hype of these things right Edison for his age was the Musk or the Sam Alman of his era undeniably brilliant but often very very wrong about timelines. And we see this happen again and again and again. There was a railway mania. There was telegraph hype. We saw this with early aviation, nuclear energy. We saw this with biotech in the early 2000s. There was the dot bubble. And in all of these cases, up close, it all felt different. That's why Sir John Templeton says that, right? Because it always feels different up close. And no one ever thinks these things are bubbles until that they pop, right? It's it's all different technologies, but it's the same psychology and it's the same arc. Now, I can hear folks out there saying, "No, no, no. You don't get it. This time it is different. AI is replacing thinking. This time it is different." One, I will link to some videos at the end of this that explain in more detail why that's inaccurate. But for here, we will focus on the historical precedent because it gives us a really clear frame for when this has happened in the past. When calculators became widely available in the 70s, for example, people all thought that they were going to destroy math. But what actually happened is that basic arithmetic became easier. Like when I was in school, they didn't want us using calculators because they thought it was going to kill our ability to do math. But guess what? You can do better math faster with calculators. Books, the thing that we all have now as a status symbol of like learning because nobody reads them. Back in the day, they were seen as brain rot. People saw it just the same way that people see TV now. It was like this distraction that no one know should engage with. There was projections about spreadsheets that they thought it was the end of accounting. When search engines came around, they thought it was the end of knowledge work, right? Why are we getting any knowledge workers anymore? All the information is just there. But it didn't happen like that, right? Knowledge work exploded because we could access stuff faster. And so this teaches us again and again and again that new tools don't eliminate thinking. what they do is eliminate lower level thinking and that's what AI is going to do and I do want to be clear that big shifts in technology can happen very quickly and there is going to be a shift in the labor market as a as a result of this like we have seen in the early 1800s there was a huge percentage of workers in this country that worked in agriculture and then mechanization happened and they no longer did there will be a shift in the in the labor market just like we don't need people doing long division now or typing on typewriters, but it's the shift that's going to happen. Nobody thought that social media managers were going to be a thing in the past, right? But now we have a whole industry around it. AI is not going to replace human judgment or taste or reasoning at the high levels. It's going to amplify the people who bring those things to the table. It will automate low-level thinking and there will require upskilling. Now, one of the things that we're going to talk about more in a few minutes that it absolutely will do and is already doing is it is going to increase the productivity demands on employees who do not own the systems they work in. But more on that in just a second. First, I think it's important to wrap up this section by summarizing, right? So, we can see again and again and again that while technology may change, human nature does not. And when you line up all of these hype cycles and bubbles and mania side by side by side, you see a similar pattern. These new technologies or opportunities emerge. People think that there is infinite progress and upside. The story overcomes the fundamentals of the thing. Institutions and thought leaders and so forth amplify this story because many of the people working in those places are no smarter than you and me and they're subject to the same human nature. Then speculation becomes normal, right? It becomes what everybody engages in because everybody's looking for the quick hit. And then the correction finally comes when the reality catches up with the story. And the reason we're going through these examples is because we can see AI following this same psychological arc right now. Not because it's not real and not because it's not miraculous and not because it's this great tech. It is a wonderful technology. But what we can see is that human nature is predictable and the manas are not about technology. It's about us. It's about how we react to these technologies. And then once we can see that, right, then this whole moment becomes a lot less confusing and destabilizing and we can see more clearly what to do about these things. So the blueprint, how do we think clearly in a mania, in a hype cycle, in a bubble? I think about five main ideas. The first is that early narratives almost always overshoot reality. When a new technology comes, the stories grow faster than the underlying technology. We see this early potential. Like that was the moment that recently happened with Chad GBT, right? It was like went from not working to working, right? It went from pretty bad answers to holy yes, this is, you know, pretty damn good, right? And so we think that that progress is going to continue into infinity. So the question we can ask ourselves is is this real technological progress that we're going to continue to see exponential progress or what we seeing is narrative momentum. The second thing that I think about is every technology and every opportunity has real market driven constraints even if the stories about them ignore those constraints. So railways had you know steel or geography and electrification had infrastructure and the internet had bandwidth and adoption and you know AI has very real constraints. There's data, there's compute, there's energy, there's huge issues with hallucinations, there's deployment and it doesn't mean that it's going to kill the technology, but it does mean before it starts really changing society, it's there's a lot of things that are going to need to happen. So we can ask ourselves what would actually need to be true physically or economically or politically or whatever for this change to actually happen. The third thing I think about is institutions amplify these narratives and their leaders are not immune to bias or to poor thinking. Right? So governments, billionaires, CEOs, media outlets, they all accelerate this belief, right? Because it's Dunning Krueger in mass, right? We think that they're good at something, they must be good at everything. Just because someone is influential, it doesn't make them rational. They feel the same FOMO. They overextrapulate. They misread timelines. They get caught up in their own personal incentives. And being great at one thing does not make you an expert in everything. So when a founder or a politician says there's going to be AGI in two years, what do they actually know that you don't? Usually they don't know anything. I can't tell you how many of these rooms I've sat with or sat in where people are making these basically the people you think are so brilliant, the founders and so forth who have no more idea about what's going on or what's going to happen than you or I do. The fourth thing I think about is this. The correction is finally where the real value emerges. So every major tech revolution tends to go through the same kinds of cycles which is hype and then correction and then real impact and the correction is where we actually see a lot of the value happened right so the internet became essential after the dot bubble not before railways they became infrastructure after the speculation electricity after the hype cycle I remember Matt Mullen who's the founder of your press uh WordPress years ago he was talking uh on the Tim Ferris Joe about he asked him how should you know entrepreneurs look for opportunities and he was saying look for markets that were hot and now not and innovate there because the froth is gone right that's what he did with WordPress and content management systems so the question we can ask is like what is going to be true here after all the narrative dust settles what what do we think will actually be the long lasting impact and that's where our opportunity is going to be and the fifth and final thing here is narratives can change very very fast, but the f fundamentals typically take a lot longer to catch up. We're going to continue to see wild promises and stuff in the news from week to week to week, but the underlying fundamentals will move more slowly. The capability of the tools will diminish in their continued, you know, growth. AI is not a brand new technology. Okay, this has been around a long time. It's just that we're just now hearing about it. The adoption curves will slow. It'll take longer to get value. There'll be problems with the adoption. regulation, economics, and so forth. And if we can stay anchored to these fundamentals, then we can stay calibrated, right? And we can be the smartest voice in the room when everybody's getting caught up in the froth. All right. So, what do we do about all this? What do we actually do with these ideas? The first thing is simple. You don't have to know what's going to happen. You just need to be avoid getting swept away by narratives and try to really understand what's actually happening. The first principles, the fundamentals, what are the incentives behind the loudest voices, etc. and so forth. The second major thing that I see is this. In almost every era of technological change, owners benefit disproportionately. When railways took off, it wasn't the workers laying the track who got that wealth, right? It was the people who own the routes. And AI is a unique technology in that it creates these atomized economies. If you are a knowledge worker, a professional of any kind, it gives you the opportunity to expand and scale yourself, your unique thinking, your unique creativity, expertise in a way that has never existed before. And AI is going to follow this pattern. You want to own a system that gives you, not your employer, the efficiency and the scale and the margin. Because if you work in someone else's system, right, all AI is going to do is increase the pressure. They're going to ask you to do more with less, more velocity, more tasks per hour. And I don't judge this. It's not good or bad. It's just how it is, right? But if you can see that that's how it is, you can make smarter choices. All right. So, I think that's enough for this video and I'll call it there. If you want more clarity on the future of work without the hype, I'm going to tee up another video here called uh I'm 42. Here's how I'm preparing for a jobless future because it adds a little bit more practical layer on top of what I'm talking about here. Um, and if you're interested in topics like this about uh technology, the future of work, like, subscribe, all the good stuff. See you in the next video.

"The four most dangerous words in investing are: This time it's different." — Sir John Templeton. Discover The Freelance Formula https://www.brendandell.com/freelance-formula-299 Apply for the Positioning Sprint: https://www.brendandell.com/positioning-sprint ________________________________________________________________ We are living through a mania. From Tulip Bulbs in 1637 to the South Sea Bubble in 1720 to the Dotcom Crash of 2000, history follows a specific psychological script. And right now, we are running that script perfectly with Artificial Intelligence. This doesn't mean AI isn't real. It means the narrative has outpaced the reality. In this video, I break down the 400-year history of financial bubbles to give you a blueprint for what comes next. The 5-Part Mental Blueprint: The Narrative Overshoot: Why early stories always outpace the actual technology (and why that's dangerous). The "Expert" Trap: Why billionaires and CEOs are just as susceptible to FOMO and bad thinking as you are. The Constraints of Reality: Physics, energy, and regulation will slow the curve—no matter what the hype says. The Correction: Why the real value of a technology only emerges after the bubble pops (e.g., The Internet after 2000). Ownership vs. Employment: In a bubble economy, you must own the system to survive the pressure. TIMESTAMPS: 0:00 - The "Mania" Script (1637 to 2025) 2:15 - A History of Delusion: Tulips & South Sea 5:45 - The "This Time It's Different" Fallacy 8:30 - Why AI Is Following the Historic Pattern 12:15 - The 5-Part Mental Blueprint for Smart People 16:45 - The Only Protection: Ownership vs. Employment