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Crazy Wisdom

Episode #535: The Technological Adolescence: Can Humans Keep Up With AI's Puberty?

Episode #535 · March 2, 2026 · 58 min

MP3 · Apple Podcasts · Spotify

About this episode

Stewart Alsop sits down with Ulises Martins on the Crazy Wisdom podcast to explore how artificial intelligence is fundamentally disrupting professional careers, labor markets, and the pace of human adaptation itself. They discuss everything from Dario Amodei's concept of "technological adolescence" to the possibility that we're approaching a point where AI advancement accelerates beyond our ability to keep up, touching on topics ranging from the economics of software development and the future of warfare to generational differences in how people will respond to AI-driven change. Martins emphasizes that while we may not be able to predict exactly what's coming, we need to dramatically increase our efforts to learn and adapt—potentially doubling the time we invest in understanding AI—because this isn't optional change, it's disruption happening at an unprecedented speed. Connect with Ulises on Linkedin to follow his work in AI and generative technology.
Timestamps
00:00 — Stewart introduces Ulysses Martins, framing the conversation around accelerationism and the future of work.
05:00 — Ulises uses the parent-child analogy to argue humans will no longer play the dominant role as AI surpasses us.
10:00 — Both agree learning AI is non-negotiable, urging listeners to double their investment in staying current.
15:00 — Discussion shifts to software as media, the collapsing cost of building products, and the risk of big players like Anthropic making your idea obsolete overnight.
20:00 — Ulises raises ecology vs. cosmic ambition, questioning whether humanity should aim for civilizational-scale goals like the Dyson sphere.
25:00 — Stewart's ESP32 hardware project illustrates AI's current blind spots beyond software, while both predict physical-world AI will arrive as a byproduct of bigger industrial goals.
30:00 — Tesla's birthplace in Croatia sparks a reflection on human genius as luck versus deliberate investment, invoking the Apollo program as a model.
35:00 — The US-China AI race is compared to the Cold War Space Race, with interdependency acting as a brake on outright conflict.
40:00 — Drone warfare and AI reframe military power, making troop size irrelevant and potentially reducing total war.
45:00 — Agile methodology and generational shifts are linked, asking how Gen Z's values will shape the AI era globally.
50:00 — Argentine vs. American Zoomers are contrasted, with millennial expectations versus Gen Z's pragmatism explored.
55:00 — Ulises closes urging everyone to enjoy the ride, taking the infinite stream of change one episode at a time.

Key Insights

1. The Death of Traditional Career Paths: The concept of professional careers as we know them—starting as a junior and progressively advancing—is becoming obsolete due to AI's rapid advancement. This applies far beyond just software and SaaS companies, extending to all industries as robots and AI systems gain capabilities that fundamentally disrupt labor markets. The question isn't whether we'll adapt, but whether humans can adapt fast enough to keep pace with exponential technological change.
2. The Acceleration Imperative: People must dramatically increase their investment in learning about AI immediately. Whatever time you were previously dedicating to staying current with technology needs to be doubled or tripled. This isn't optional—it's comparable to the necessity of basic education. Unlike previous technological transitions where you had years to learn new frameworks or tools, the current pace demands immediate, intensive engagement or you risk becoming irrelevant.
3. Software as Media and the Collapse of Development Economics: Software has become media—easily reproducible and increasingly commoditized through AI assistance. The fundamental economics of software development are collapsing because if building software requires dramatically fewer development hours, the value and price of that software must necessarily decrease. Entrepreneurs need a new evaluation framework that assesses the risk of their ideas being replicated by AI or absorbed by major players like Anthropic or OpenAI.
4. The Parent-Child Analogy for AI Development: Humanity's relationship with AI will inevitably mirror that of parents with increasingly capable children. Initially, we understand and control what AI does, but as it advances, it will surpass human capabilities in most domains. Just as parents cannot control fully grown adult children who exceed their abilities, humans will need to reconcile with creating something superior to ourselves. Attempting to permanently control such systems may be both impossible and potentially pathologic.
5. The Kardashev Scale and Civilizational Ambitions: AI represents a civilizational-level technology that should redirect humanity toward grander goals like capturing stellar energy through Dyson spheres and expanding beyond our solar system. The competition between China and the United States over AI mirrors the Apollo program's space race but with higher stakes—potentially making traditional concepts like money less relevant if we successfully crack general intelligence. This requires thinking beyond planetary constraints.
6. The Changing Nature of Warfare and Geopolitics: AI and autonomous weapons systems are fundamentally changing warfare by making human soldiers less relevant, similar to how nuclear weapons reduced the importance of conventional military force. This shift may actually reduce bloody civilian casualties in conflicts between major powers, as drone warfare and AI-driven systems create new equilibriums. The geopolitical map may fracture into more sovereign states and city-states as centralized control becomes less effective.
7. Generational Adaptation and Unpredictability: Different generations will respond uniquely to AI disruption based on their values and experiences. Generation Z, having grown up during the pandemic without traditional expectations, may adapt differently than millennials who experienced unmet expectations. However, we must remain humble about our predictive abilities—we're not good at forecasting technological change or its timing. The best approach is maintaining openness, trying to understand developments as they unfold, and accepting that we cannot consume all information in an era of unlimited AI-generated content.
Episode transcript
Stewart Alsop III00:00

Welcome to the Crazy Wisdom Podcast. This podcast is for you. If you have an insane drive to find the truth of things, it's not the good answers that we seek, but the good questions. I interview a range of different guests from many different fields, all with the intention to uncover the simple truths that are hidden in plain sight. Most people don't want to go there. I go there, my guests go there, and you benefit. Please let me know if you enjoy these episodes and as always, subscribe on itunes, Spotify, or wherever you listen to the podcasts.

Stewart Alsop III00:35

Welcome to the Crazy Wisdom Podcast. I've got Ulysses Martins here and we did not do the intro in the right way because I was supposed to ask you what you were doing before so I could intro you, but we've already collaborated on speaking events, so he runs events in Buenos Aires and just really excited to finally get together with you and talk more about your worldview about where we're headed. Because we had to pretty trippy conversation the last time we talked about the future and it's going to get pretty accelerationist. What do you think?

Ulysses Martins01:06

So, first of all, I'm really glad we're doing this and thanks for welcoming me. You know, I have been reading a lot like any other day and there was this, you know, news about that IO Amodei, you know, the CEO of Anthropic, and he was referring to this technologic adolescence and so on. But there was something that caught my eye on that publishing, and I think it's interesting. And if we keep going this fast now, what we know as a professional career, right, this idea that you start as a junior and you keep growing, it can be corporate America or it can be anything or a startup. Yeah. I think that, you know, this idea, we are already seeing this with probably the MBAs, right? And some, you know, postgraduate degrees that maybe people are not getting too much value out of that anymore. Right? Now, if we keep going at this space, I'm thinking, hey, maybe, you know, we should kind of rethink the entire thing. I brought a couple of articles related to this, right? One was related to the IT industry alone, like it's being completely rewired. And somebody even told me, hey, software SaaS, companies, stocks are going down. I saw the news anyways, and I'm like, oh boy, it's way bigger than software, right? So robots are coming. We know that those are coming, right? And I saw a couple of things that, you know, people don't realize. Things like, hey, this robot can lift your car, right? So imagine the implications of Having such power, like, hey, before, it's like, okay, something happened with the car. Of course, you cannot push it down long. You cannot lift the car. You have a lot of limitations from the physical standpoint as a human. If you want to kind of break a wall, I mean, you cannot do anything. I mean, you need to go and get a tool to do something, even, even a fix, a con to, to grab a branch or whatever. Now, if you, if you were to have something like that, that powerful, it's like, that's interesting. But, you know, just to go back a little bit to what I'm seeing, I'm seeing, and somebody asked me about, you know, if this is going to be a change. It's not change. This is a disruption. And how many people realize disrupt means changes a lot really fast? So, long story short, what Amore said of these professional careers, he also mentioned this in an interview, and I am very fond of that. The job market, we adapt. Now, do we adapt that fast? That's the question. So let's say that for a second, we as humans on labor, white color, blue color, let's say that we adapt. Can we adapt that fast? Right? So that's like two questions I'm posing to the audience over here and to you as well. Hey, first of all, are we going to be adapting or not? Let's assume that we are question number one. Now, can we adapt that fast? Right? So I don't know.

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