The end of the zero-interest-rate period compressed lending margins, but it had a silver lining. It forced fintech companies to become 'full-stack' by acquiring bank charters and building significant revenue streams from customer deposits, ultimately making their business models more durable.

Despite massive private market dry powder, deal volume has slowed because sellers and their bankers are stuck on pricing from the low-interest-rate era. Buyers, facing higher financing costs, cannot make the numbers work, creating a market stalemate or "quagmire."

The dot-com bubble wasn't pricked by a single event but deflated from a confluence of pressures. A series of disappointing earnings from unprofitable companies, concurrent Fed tightening, expiring insider stock lockups, and the end of Y2K-driven IT spending all contributed to the collapse.

The AI build-out increases real interest rates by demanding vast amounts of capital, crowding out other investments. Simultaneously, it pushes up nominal rates by creating inflationary pressure on physical resources like labor, energy, and materials needed for data centers.

Unlike past cycles triggered by economic fundamentals like job losses, the recent CRE downturn was driven by capital markets (i.e., interest rate hikes). Because underlying property performance remained strong, lenders could confidently "extend and pretend," providing stability and preventing a catastrophic crash and broader economic contagion.

The macro trend of rising bond yields creates a specific, acute risk for the AI sector. Many AI startups are funded by floating-rate private credit, and their debt service costs will explode as rates rise. This is compounded by high CapEx and an inability to scale revenues proportionally, creating a potential crash.

The biggest risk to capital-intensive AI ventures isn't a lack of demand but losing access to cheap financing. The current boom is built on borrowing long-dated money at low rates (e.g., 6%). A shift to a higher yield environment (8-10%) would make funding massive, negative cash-flow projects untenable.

Once considered safe due to low CapEx and recurring revenue models, the technology sector now shows significant credit stress. Investors allowed higher leverage on these companies, but the sharp rise in interest rates in 2022 exposed this vulnerability, placing tech alongside historically troubled sectors like media and retail.

Recent financial distress in large, private equity-owned software companies is being misattributed to the threat of AI. The actual cause is over-leveraging when interest rates were low, followed by an inability to service that debt as rates rose and growth slowed. It's a credit problem, not a technology disruption problem.