Larry Li, Founding Partner of AMINO Capital and 2025 Forbes Midas List Honoree, joined a deep-tech and AI investor panel at SuperReturn Japan, addressing how to spot scalable opportunities amid industry hype and flashy demos. He stressed that AI and hard tech’s future lies with those prioritizing structural understanding over spectacle, outlining three key points: infrastructure is fast commoditizing, eroding model-layer moats; real value lies in workflows, real-world deployment and customer reliance rather than demos; and focused, resilient founders will lead the sector. Li concluded that competitive edge stems from grasping the technical, economic and human fundamentals of long-term sustainability.
Sue spoke at the Women’s Venture Capital Summit 2026, delivering a presentation titled “The Agentic Revolution in FinTech – Where Do Investors See Opportunities in AI, Crypto, and Beyond?”. She joined over 400 LPs, GPs and industry leaders at the event hosted by With Intelligence - Women's Summits to discuss the future of venture capital and the next wave of AI-driven opportunities.
At Web Summit, Larry Li, Brett Gibson and Kelsey Cheng noted that venture capital’s key changes are structural rather than ostentatious. Core insights: AI as a baseline, advantage in speed, clarity and agile execution; abundant software vs. scarce data, true moats in workflow-level fresh private data; early founder quality indicators (velocity, obsession, insight depth) surpass pitch decks; shifting success metrics to durability, revenue and multi-path liquidity. Competitive edge lies in identifying overlooked value, with a concluding quote from Schopenhauer. Matt Stapleton participated.
AMINO Capital Founding Partner Larry Li spoke at the London Global WealthTech Summit, highlighting that intelligence—not standalone software—creates core value, with intelligence defined as the combination of software and data. He traced value creation evolution across eras: machines drove the Industrial Age, code the Information Age, and data now leads the Intelligence Age. Li noted that 80% of an AI firm’s costs go to data acquisition and cleaning, versus just 15% to algorithms. He emphasized that industry digitization is key to leadership, while building a data layer enables platform status, with multicultural complementary teams acting as a critical catalyst.
