Dor Sasson argues that the 2026 AI pricing crises at Anthropic, OpenAI, and GitHub were infrastructure failures: usage was checked after invoicing rather than before inference. He proposes synchronous entitlement checks with asynchronous settlement, borrows banking concepts such as holds, double-entry bookkeeping, and credit sources, and outlines four patterns for selling AI at scale.
A discussion of SemiAnalysis's ClusterMAX 3.0 ranking of managed GPU cloud providers, covering the evaluation criteria, the security problems found across neoclouds, the scarcity of compute as inference providers turn profitable, the strategic position of frontier labs that now resell compute, Nvidia's acquisitions of Poolside and Hugging Face, the separation between buyer-focused rankings and investment research, and the spread of heterogeneous silicon from Huawei and others.
David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez from a16z walk through 25 charts from their State of Markets presentation, covering why markets are rising on earnings rather than multiple expansion, the roughly $780B hyperscaler capex race, the new age of atoms in physical infrastructure, enterprise AI adoption gaps, agent economics and falling inference costs, consumer AI and marketplace disruption, the bifurcation of SaaS, the rise of mega private companies, and the sectors they are most excited about next.
Ampersand presents the critical need for a new payment infrastructure for AI agents, moving beyond traditional human-centric rails to address machine-speed transactions and stringent enterprise compliance requirements. The presentation highlights how agents require access to paid tools via a "skill file" and demonstrates agentic e-commerce, culminating in a crucial demo of real-time sanctions screening for wallet addresses.
A deep dive into the current AI boom, exploring why demand for intelligence is likely underestimated and the outcome won't necessarily be winner-take-all. The discussion covers the rapid economics of AI infrastructure, the risk of an AI shortage over a bubble, the potential for orbital compute and re-industrializing America, and NVIDIA's central role as the "central bank of AI" in a multi-model future.
a16z's new Machine Age Fund addresses the unprecedented demand for AI infrastructure, shifting the bottleneck from models to the foundational hardware. The discussion highlights surging Hyperscaler CapEx, component supply crunch extending to 2028, and the exponential compute needs driven by reasoning and agents. It explores how AI turns engineering problems into capital/compute challenges, identifying opportunities for new infrastructure companies in chips, power, and data center redesign, and the emergence of experienced "systems founders" to rebuild the computing stack for this new era.