u/Karzov

Memory (HBM) demand is directly tied to AI capex. If the capex cycle unwinds, Micron will suffer from oversupply and falling prices. The author explicitly includes MU as a “shovel-maker” to short. GPU depreciation cycles also affect memory replacement demand. Same thesis—after the AI IPO pop, institutional pullback will crater demand for HBM and other AI memory. Micron’s high margins are unsustainable as competitors (Samsung, SK Hynix) add capacity. Short MU as a proxy for the AI memory bubble. The timing aligns with the broader capex unwind in late 2026–2027. Memory cycles are notoriously volatile; a sustained AI inference boom could keep demand elevated. Also, geopolitical factors (China restrictions) may limit supply, supporting prices. Government backstop for AI infrastructure could delay the bust.

AI infrastructure capex as % of GDP is at an all-time high (12.5%), exceeding dot-com peak. Historical capex cycles always end with shovel-makers crashing. Financing is shifting from cash to debt to IPOs, a sign of liquidity stress. Inference efficiency (RouteLLM, adaptive thinking) reduces compute demand, and GPU depreciation lifespans are artificially inflated but will reverse via deferred tax liabilities. As OpenAI/Anthropic go public and ROI becomes visible, institutional money may pull back, killing capex demand. The author plans to short after the IPO pop (late 2026). Nvidia is the dominant shovel-maker, highly concentrated (3 customers = 54% of revenue), and faces competition from ASICs and China. Short NVDA on the thesis that the AI capex bubble will burst, leading to severe demand degradation and multiple compression. The trade is timed for late 2026–2027 after the IPO euphoria fades. Government backstop for AI (too big to fail), sustained enterprise demand, GPUs not becoming obsolete as fast as expected, or inference efficiency gains failing to materialize (routing errors). Also, NVDA may continue to grow if AI becomes a durable capex cycle.