What is an AI-native VC, and is FutureX Capital one?

At FutureX this takes the form of an in-house AI Lab: a research radar over papers, patents and developer signals; a knowledge graph of companies, technologies and value chains; tooling from pre-investment evaluation to exit support; and an AI knowledge base. Everyone from partners to interns works on that system, with 22 AI agents running around the clock across market intelligence, sourcing, research and portfolio tracking. Judgment comes out of a pipeline that has screened 1,500+ AI projects.

The seven-signal bubble framework is the working example: since March 2026 FutureX's own system has scored the seven signals every day, and the August 2026 reading lit six of them; liquidity triggered on August 17, when the 30-year US Treasury yield touched 5.31% (public market data).

The other half of being AI-native is publishing the tools and the judgments. FutureX-Skills is open source on GitHub; each update to the 24 research reports carries a date and a source grade; the debates page places leading practitioners' public disagreements next to FutureX's own position; and the founding partner publishes her investment diary in public, at no fixed cadence, only when she has a judgment to record. The practice turns judgment into a record that can be checked and challenged.

On August 26, 2026, Zhipu open-sourced GLM-5.3-Flash with inference served entirely on domestic Chinese chips (confirmed); FutureX reads it as comparable capability at roughly 1/40th the price, a reading recorded on the debates page and in the report "Frontier Models and AI Sovereignty 2026".