AI Boom Faces Dot-Com Reckoning

The crash thesis is more credible as a warning about capital allocation than as a prediction that AI itself will fail.

• –Frontier-model costs, data-center spending, energy demand, and debt create a fragile infrastructure boom.
• –A market correction would likely punish overvalued startups and hardware suppliers before reducing demand for useful AI products.
• –Developers should prioritize measurable productivity gains, durable revenue, and portable architectures over hype-driven experimentation.
• –Companies with strong inference economics and clear customer ROI are better positioned to survive tighter funding.
• –History suggests transformative technologies can be real while investors remain disastrously early or wrong about timing.