Massive capital expenditures exceeding $1 trillion across hyperscalers in 2026, funded partly through debt amid power and chip constraints, continue driving trader focus on whether returns from large language models will justify the outlays. Warnings from the Bank for International Settlements and analysts highlight risks of an investment pullback if productivity gains lag expectations, echoing prior tech cycles. Recent frontier model releases from OpenAI, Anthropic, Google, and Meta sustain competitive momentum and developer adoption, while safety discussions among labs signal internal caution. Key near-term catalysts include Anthropic’s planned November IPO at extreme valuation multiples and OpenAI’s delayed listing, alongside any shifts in enterprise spending or regulatory scrutiny that could alter funding flows.