AI's Economics Don't Make Sense

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A detailed critique of the economics underpinning generative AI, arguing that subscription-based pricing for LLM services was fundamentally deceptive and unsustainable. GitHub Copilot's shift to token-based billing is used as a case study showing that AI companies have been subsidizing massive compute costs for years, training users to consume far more than their subscriptions cover. The piece breaks down the broken unit economics of AI data centers (using a 100MW theoretical model and Stargate Abilene as examples), estimates that $156.8B in annual compute revenue is needed just for data centers currently under construction, and argues that OpenAI and Anthropic have no credible path to profitability. The author contends that hiding true token costs from users was a deliberate strategy to grow adoption, and that the transition to usage-based billing will expose just how expensive and often unjustifiable AI tooling really is.

#github

#llm

#genai

#openai

#anthropic

Apr 28•49m read time•From wheresyoured.at

Table of contents

The Core Economics of Generative AI Are Broken Monthly AI Subscriptions Are All Part of AI’s Subsidy Scam, A Deliberate Attempt To Separate Generative AI From Its Actual Costs Can The Average Company Afford To Move To Token-Based Billing? Anthropic Estimates Users Spend $13-$30 a day ($7K+ a year) On Claude Code, As Large Organizations Spend Hundreds of Thousands or Millions A Year The Economics of AI Data Centers And Compute Do Not Make Sense AI Data Centers Are Expensive To Build, Expensive To Run and Make Very Little Actual Revenue Stargate Abilene Is A Disaster — $2.94-per-GPU-per-hour, $10 Billion In Annual Revenue, Years Behind Schedule, One Tenant That Loses Billions of Dollars A Year If OpenAI Fails To Raise $852 Billion In Revenue, Funding, and Debt Throughout The Next 4 Years, The Stargate Data Center Project Will Kill Oracle Anthropic Is Just As Bad As OpenAI, Committing To Up To 10GW ($100BN+ Annual Revenue) In Compute From Google and Amazon There Needs To Be $156.8 Billion In AI Annual Compute Revenue To Support The 15.2GW of AI Data Centers Under Construction, and $1.18 Trillion To Support All 114GW Announced Generative AI Is Unprofitable and Unsustainable, And Only Getting More Expensive LLMs Are A Ripoff, And Customers Have Been Lied To