Keep pulling the thread on Claude Code.
The rise of powerful agentic AI models in early 2026 fundamentally changed usage patterns, moving the primary economic unit from predictable per-seat subscriptions to variable, high-volume per-token API consumption. This transition unlocked massive revenue streams for foundation model companies but also introduced significant cost volatility for their customers.
The industry is transitioning from a period where providers absorbed massive inference costs to subsidize user adoption to an era defined by compute and token scarcity. This shift is driven by unsustainable costs and overwhelming demand, forcing a market-wide recalibration of AI's true price.
Anthropic has emerged as a dominant force, reportedly surpassing OpenAI in business adoption and achieving a staggering $47 billion annualized revenue run rate and a near-trillion-dollar valuation. The company is on the verge of becoming the first profitable major foundation model lab.
The new reality of expensive AI is forcing adaptation across the ecosystem. Providers are moving to usage-based billing, enterprises are scrapping "token maxing" incentives for ROI-focused metrics, and a market for lower-cost alternative models and infrastructure optimizers is rapidly growing.
Governments are moving beyond abstract policy discussions to direct intervention in the AI sector. The White House's involvement in Anthropic's Mythos release, motivated by compute scarcity, and political debates around data center moratoriums and token taxes signal a new phase of strategic government oversight.