Wall Street is panicking, but history tells a different story. 📉 We investigate the "AI Bubble" debate through the lens of economist Carlota Perez, whose theory of technological revolutions suggests we are in the necessary (and chaotic) "Installation Phase".

1. The $600 Billion Question: We break down the terrifying gap between infrastructure spending and actual revenue. Tech giants are pouring $600 billion annually into AI infrastructure (chips, data centers), but the revenue generated is a fraction of that. Critics call this a "mean-reversion bubble" destined to pop, while optimists argue it's the upfront cost of a new industrial revolution, similar to the railroad or fiber-optic booms.

2. The Productive Bubble: Not all bubbles are bad. We explain the concept of a "Productive Bubble"—one that leaves behind valuable infrastructure (like the internet) even after the crash. Unlike the 2008 financial crisis (which left nothing but bad debt), an AI crash would leave behind a massive grid of compute power that could fuel innovation for decades.

3. The Execution Year: As 2025 becomes the "year of execution," we analyze the shift from "primordial soup" experimentation to tangible deployment. With Big Tech locking down the supply chain and capital expenditures stabilizing, the market is moving from wild speculation to a "Product Science" war where only companies with real user value will survive the inevitable correction.