#economics
Wiki 18
- AI Bubble Pale Horses Checklist of warning signs that the AI bubble is deflating, tracking which have fired
- AI Is Too Expensive Zitron's May 2026 follow-up to the subprime-AI thesis — Microsoft sunk $87B into OpenAI, hyperscalers need $3-6T to break even, enterprises blow through token budgets, Zillow is AI Chernobyl
- AI Subsidy Economics How every link in the AI chain runs on subsidies, from GPU sales to consumer subscriptions
- AI Token Budget Explosion Enterprise customers exhausting annual AI token budgets in months — Uber, ServiceNow, Salesforce, Stripe, Zillow — with no usable per-task measurement and no SLA
- Business Idiot Zitron's framing for the executive class whose job structure rewards an impression of work — exactly what LLMs are best at producing
- Emad Mostaque at TechBBQ: The Internet Will Go Offline (Trending Topics) Emad Mostaque's 2026 TechBBQ talk as reported by Trending Topics, on AI attacks, owning your cognition, labor losing value, and $1.50/hour robots
- Enshittification Doctorow's term for the three-stage decay of platforms, once held in check by antitrust, competition, and worker power
- From Open Source Software to Open Source Strategy Bill Gurley on open source as a corporate weapon, from Android and Kubernetes to autonomous vehicles and the fight over open-weight AI
- Knife-Catching Compute The Dario Amodei dilemma — order compute years ahead and risk bankruptcy if revenue doesn't materialise, or buy at last minute and pay spot prices that destroy margin
- LLM as Average Democratizer The argument that LLMs' main economic impact is making "average" output cheap, lifting the floor without raising the ceiling
- Open and closed models are on different exponentials Nathan Lambert on coding agents proving users pay a premium for top closed models, while open models take the larger, slower diffusion market
- Open models in perpetual catch-up Nathan Lambert on why the roughly six-month gap between open and closed models holds steady, plus trends in adoption, specialization and China
- Some Simple Economics of Open versus Closed AI Christian Catalini's a16z essay using innovation economics to argue open weights change where AI investment goes and who profits, not how much
- Speculative growth A temporary, unsustainable overvaluation can leave a permanent real legacy — if it installs enough capital to push the economy into a self-sustaining higher-capital equilibrium before the correction arrives
- Speculative Growth and the AI "Bubble" Caballero's (MIT) formal argument that an unsustainable AI valuation can leave a permanent real legacy — the bubble pops and the capital stays — if the correction arrives late enough
- The Rise of the Bullshittery Marius on a market that pays for performance over substance — Frankfurt's bullshit, LinkedIn grift, LLM-cheap content, Graeber's bullshit jobs, and the cost to careful work
- The Subprime AI Crisis Is Here Zitron's case that AI demand is subsidy-driven, with a predicted collapse sequence and warning signs
- What comes next with open models Nathan Lambert on why open models should stop chasing the closed frontier and build small, specialized models that closed agents call as tools
Sources 1
- The Subprime AI Crisis Is Here Full article pasted by user. See wiki summary for distilled content.