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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Four deals that reshaped AI in one week
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Meta's $2B Manus Bet: the AI agent race just got real
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n8n 2.0: The Automation Platform Finally Grows Up
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The Four O's: Reading the Signs of an AI Bubble
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SpaceX Eyes $1T IPO as DeepSeek Chip Scandal Grows
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ChatGPT ads, data, and the new AI SEO frontier
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Nano Banana Pro and the Google AI Ultra Edge
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GPT-5 Codex Mini: When Small Context Wins at Code
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Nine Signals Shaping the AI Power Curve
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AI capital flood meets Copilot relaunch