Couple random thoughts... Frontier labs appear to be 6-7 months ahead with internal models, and are reportedly seeing signs of accelerating their own cycle times, potentially pulling further away. Open weights models are becoming highly capable and the range of tasks they can reliably accomplish is rapidly increasing the surface areas within enterprises that they can be used for The vast majority of token spend is accruing to frontier model providers The price per token and price per task for an increasing number of use cases is plummeting AI potentially represents a China shock for white collar employment, except instead of concentrated losses in a handful of industries and geos its widespread throughout most companies and touches almost every geographic region. Technological diffusion is about more than capability and cost. The spread of FDEs shows the challenge of scaling implementation. Gross margins on inference are much healthier than people expected 12-18 months ago. The AI industry is fundamentally making long term fixed dollar commitments and funding them via selling tokens in the spot market. Yes at certain levels of the stack certain parties are duration matched via contracted revenue, but the industry in aggregate is selling spot tokens against long term fixed costs. The balance sheets of the core funding sources for the AI buildout remain healthy, if less so than a year or two ago. And increasingly third party capital is being mobilized in quantities never before seen. Because the buildout is now financed out of risk capital and not internal funds, it is subject to the vicissitudes of human emotions, not simply math. A surplus of capital today at attractive prices does not imply an availability of any capital at any price tomorrow. This means there is path dependency risk from reflexivity and exogenous shocks.