AI Economics for Operators
Pricing, capital, unit economics, vendor strategy, and the market structures behind AI operating decisions.
Artificial intelligence is both a technical system and an unusually capital-intensive market. This topic tracks the money underneath the models: token prices, inference costs, funding rounds, valuations, acquisitions, monetization, procurement, and the margins hidden behind headline benchmarks.
The operator’s question is always explicit: who captures the value, what does adoption actually cost, and which assumptions make a build, buy, partner, or investment decision rational? Company news appears here when it reveals a durable economic mechanism—not simply because a large AI company made another announcement.
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Claude Code's 'Raise' Costs You 20% More a Unit
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OpenAI's Ohio Lease Pays It $688M a Gigawatt
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71% of Alphabet's Pretax Profit Was Paper Gains
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Nvidia Now Takes 47 Cents of Every Capex Dollar
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Tencent's Hy4 Charges 5x GLM for a 2% Edge
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Anthropic's Song Exposure Equals 17 Days of Revenue
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One Robot Round Equals 10 Average Physical AI Deals
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Cursor's Router Ships a Commit for $4.63
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$26.5B Chases 6% of Businesses on Open Weights
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Anthropic Rents Megawatts at 8x Its Own Silicon