Abundance founder: AI could shift investing from statistical arbitrage to fundamental analysis

Discussing Abundance, the guest said machine learning and AI have mostly been used to identify statistical patterns, while reasoning systems could potentially analyze fundamental questions—for example, a company’s competitive moats and the durability of its growth. He said such systems and agentic capital allocation remain exceptionally hard to build; obvious opportunities get priced in quickly, and their alpha decays fast.

Asked about hardware and a race for compute, he said Abundance had thought about hardware but expected to build advantages in other ways too. The company allocates capital in public markets and in other areas where, in his view, returns may be larger, more durable, and more impactful. He did not specify those other areas.

The guest also described his goals for the company: after leaving Instacart, he wanted to build a company with the potential to become a trillion-dollar business and, in five to six years, hopefully a multi-trillion-dollar one, while benefiting humanity. These were ambitions and an assessment of potential, not achieved results. He said AI is redrawing business boundaries: companies may focus not only on a product such as SaaS but also on outcomes and new kinds of holding companies.