The Economic Supercycle

Change represents both a risk and an opportunity, depending on your career stage, you might be more or less risk-averse. And yet, at this stage, risk aversion might only work against you, as we’re witnessing the development of a whole new market attached to an economic paradigm; thus, you better embrace it if you still have at least a decade ahead of you in terms of career.

So, let me paint how this might play out before understanding the career choices that might make sense in this phase.

What I’m writing applies to you as much as it applies to me, so this is as much a letter to my future self as a career compass for you!

I’ll tackle this in three pieces, then put all together in a massive guide…

The AI Paradigm Shift

There is good news: we’re still in “1the 1995 moment” of AI development.

Thus, as a parallel, we haven’t even figured out yet what the “search-like” industry of the AI era would be, able to scale to the billions.

That’s existing news, as it’s an exciting time, the Wild West of AI, the Gold Rush moment.

This is still the “Aildorado moment” where whoever is selling the “picks and shovels”—the essential tools and infrastructure needed for others to participate in the rush, is the one who’s getting the most out of it.

However, the whole ecosystem is developing, and the foundational layers (hardware and AI models) that today are winners-take-all might also be commoditized in the next 20 years.

In the meantime, they might become multi-trillion-dollar companies.

Thus, the good news is this is an exciting time when we’re all still trying to figure things out.

By the same token, this also comes with a lot of instability.

Therefore, it’s worth setting the underlying structure that might drive what I’ve bubbled as an economic supercycle, not different from how the microchip transformed the entire global economy.

The Phases of the AI Paradigm

I’ve explained already in AI Supercycle that might play out in three main cycles:

• Cycle 1: A layer on top of every existing industry (known knowns) – defined by linear technology and market expansion.
• Cycle 2: An enhancer for many developing/complementary industries (known unknowns) – defined by linear technology expansion, only partially linear market expansion, and non-linear market expansion.
• Cycle 3: The foundation for creating whole new emerging industries viable (unknown unknowns) – defined as fully non-linear technology/market expansion.

Each cycle will touch a specific part of the existing ecosystem, destroy some parts, and keep others. Initially, it is to amplify, redefine, and create something entirely new.

As I’ve explained in AI Supercycle, this is an economic paradigm that will play out in 30-50 years.