The a16z Show

David George × Sarah Wang × Alex Immerman × Santiago Rodriguez

AI’s rally is being driven by earnings rather than multiple expansion, with the S&P 500 below 20 times earnings while growing about 15%.Capex is projected to rise from $416 billion in 2025 to about $780 billion in 2026 and exceed $1 trillion annually from 2027; enterprise adoption remains concentrated in pilots, with inference-cost declines and workflow deployment as catalysts.

Jen Kha × David George × Aram Verdiyan

AI is making capital itself compound advantage, pushing venture’s power law beyond prior tech cycles as compute improves products and inference demand remains unlimited.Only 20 of 3,000 US VC firms produced consistent 3x net returns over two decades, supporting concentrated LP portfolios and 5–10%+ late-stage sizing in category-defining companies.Meanwhile, traction is harder to parse and pre-ChatGPT software LBOs face repricing, leaving diffusion, liquidity, and power access as key risks and catalysts.

David George × Gavin Baker

AI demand accelerated through July and August, with usage concentrated among possibly sub-10 million heavy users and no leader identifying a worsening quantitative metric.Nebius suggests nine-to-ten-month paybacks on $50B-per-gigawatt builds, supported by 50-60% customer prepayments; undersupply through ’28 could lift token prices, while shifting capacity to training could cut lab revenue from $480B to $120B.

Ben Horowitz × Martin Casado × Raghu Raghuram × Erik Torenberg

a16z’s new AI infrastructure fund captures a founder migration into hardware, with top-founder hardware pitches rising from roughly 3–5% to “north of 20% or 30%.”Hyperscaler capex, booked-out GPUs and resale premiums support opportunities across chips, power and cooling, while grid shortages, regulation and uncontrolled agent spending remain constraints.

Martin Casado × Sarah Wang × Matt Bornstein

Cursor’s interface-over-model thesis challenged Microsoft’s Copilot despite its VS Code, OpenAI weights, 100 million developers, and enterprise distribution.Rejecting a $25–50M ARR self-serve ceiling, it built enterprise sales reaching over 50% of the Fortune 500, where margins matter; its IDE-to-agent-to-model shift still faces model releases such as Opus 4.5 and an unnamed acquirer’s potential compute-distribution-data fit.

Elena Burger × Angela Strange × Gabriel Vasquez

AI is reversing a16z’s international sourcing flow toward Silicon Valley, where borderless founders can compound differentiated talent, government-backed validation, and enterprise access across countries.With 40% of a16z’s investments in international founders, the test is whether diaspora networks and 3–6 months of Bay Area immersion create durable customer and talent advantages.

Travis Kalanick × Ben Horowitz × Erik Torenberg

Atoms is applying full-stack industrial AI to food, mining, and transport, with production, logistics, robotics, and infrastructure unified as an “atoms-based computer.”Its 50% production-cost reduction, 50¢–$1 robotic delivery, and mining productivity now above humans support a path to lower-cost meals and faster deployment, while execution depends on management capacity and overcoming industrial regulation.

Erik Torenberg × Jake Paul × Geoff Woo

Anti Fund is pairing growth capital with Jake Paul’s scarce distribution advantage, backing names including Anduril, SpaceX, OpenAI and Anthropic as Woo argues that attention, not capital, is increasingly constrained.Paul’s experiment-measure-concentrate playbook and resilience underpin the partnership, while creator monetization, political and education ambitions, platform limits and the possibility of rapid AI imitation remain important variables.

Erik Torenberg × Benedict Evans

Agentic coding has crossed unmistakable product-market fit, with customers pulling products from vendors’ hands.Foundation models appear headed toward commodity economics absent durable differentiation, while today’s token scarcity meets $1 trillion–$2 trillion of capex and “100x, 200x” efficiency gains.Cheaper development should create more software, but the unresolved question is which SaaS incumbents survive and whether models capture infrastructure-like returns.

David George × David Clark

OpenAI and Anthropic now add more monthly revenue than Meta, Google, or Microsoft despite AI diffusion below 5%, making “in the token path” George’s rule for application winners.Five frontier labs could lower token prices, but Chinese models reportedly offer 80% of frontier capability at 10% of the cost; scarce capacity lasts through early 2029, with algorithmic breakthroughs the key reversal risk.