Why $1B Exits are Dead

What It Covers

a16z's David George and VenCap CIO David Clark analyze how AI is reshaping venture capital fundamentals, covering the collapse of the $1B exit benchmark, supply constraints preventing a bubble, value capture uncertainty across the model stack, and why top-tier exits now require $32B+ to qualify as top 1%.

Key Questions Answered

• •Exit threshold inflation: The top 1% venture exit threshold has increased 10x in roughly 24 months — from $10B (2020–2024) to $20B (early 2026) to $32B currently, with Wiz setting the floor. If OpenAI and Anthropic IPO by September, that threshold could exceed $100B, making $1B exits structurally irrelevant as a success benchmark.
• •AI revenue vs. diffusion gap: Anthropic and OpenAI are already adding more monthly revenue than Meta, Google, or Microsoft individually, potentially reaching $200B combined run rate by year-end — yet real-economy diffusion sits below 5%. Investors should treat current revenue figures as early signals, not ceilings, particularly across legal, finance, and non-tech enterprise functions.
• •Token path as investment filter: The primary lens for evaluating AI companies is whether they sit in the "token path" — directly involved in AI inference and consumption. Enterprise software budgets are already being reallocated toward AI costs, creating pressure on legacy SaaS vendors. Investors should prioritize companies that capture value within the inference layer rather than adjacent to it.
• •Supply constraints as bubble prevention: Data center capacity at scale is unavailable until late 2028 or early 2029, with the US already roughly one year behind projected build-out schedules. This scarcity across compute, power, and hardware components makes a near-term AI bubble unlikely. The scenario that could reverse this is an unexpected algorithmic breakthrough producing dramatically smaller, less token-intensive models.
• •Defensibility half-life is shrinking: 40% of companies on Forbes' AI 50 list dropped off within a single year. Investors should avoid anchoring on first-mover advantage — Google was not the first search engine, Facebook was not the first social network. Portfolio construction should prioritize backing the strongest founder in a space over predicting which specific application layer captures durable value.