Anthropic spends 2.3x payroll on compute — how close the rest of the market gets by 2029

Anthropic：当AI成本超过工程师薪酬

Anthropic's 2026 inference and training spend is roughly $10B, or $2M per employee — 2.3x its all-in payroll. The top 1% of software companies spend $89k per engineer per year on AI; the median spends $137. Tunguz lays out three scenarios through 2029: Bear (token deflation wins, AI spend stays at 41% of salary), Base (top-1% trajectory tapers to 140%), and Bull (the market reaches Anthropic's 230% ratio, $596k per engineer). Bull drivers are agentic workflows that Goldman Sachs expects to drive a 24x token-consumption increase by 2030. Bear counterweights are 10x/year token-price declines and open-weight models closing the quality gap at a fraction of the cost. The post does not prescribe which scenario to model for 2027.

Why it matters: Tunguz uses Anthropic's financials as an anchor to map stratified AI spend across the industry and projects three convergence paths to 2029. Solid data with a clear thesis, but it's industry analysis rather than hard news — caps at 78.