You know, you’ll find me an AI skeptic on a lot of the boldest claims. Here’s one I almost never see: for those who are curious, epistemically honest, and self-aware, AI is a godsend of a learning tool.
Over the last 48-72 hours, I’ve been doing a real deep-dive on the private credit crisis portion of the tripartite economic crisis scenario from my latest article, here.
AI Isn’t Taking Your Job. The Crash Might.
The real employment threat isn't automation from AI, it's what happens when the bubble meets private credit collapse and supply shock.
(I’m due for an update on that topic, and overdue on much more across my Substack.)
A hypothetical—Viewed from 2030, what would we have expected to see in 2025-2026?
(Assuming a private credit crisis, AI bubble collapse, and simultaneous supply and demand destruction (Iran War +) crashes the economy in 2026-2027.) Is that present? What’s nuanced? Where is there countervailing evidence or sentiment? What are the mechanics, triggers, transmission systems, etc.?
And wow, am I deep down the rabbit hole.
Now, I follow the macroeconomics and finance news as I can, and try to keep track of the analysts on FinTwit. This is threading those needles into a highly coherent tapestry. All while learning/exercising:
• Structured finance and credit markets literacy
• Systemic risk analysis
• Source criticism and epistemics applied to financial data
• Political economy of financial regulation
• Interdisciplinary synthesis
That’s usually reserved to formalized university or accredited learning vehicles. The fact I can design my own course and subject—so long as I’m vigilant about confirmation bias, check the sources, and produce original theses and critiques—is genuinely revolutionary for learning.
