“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z

Vijay Pande’s move from managing nearly $4 billion at a16z to a lean, AI-heavy firm making only a handful of concentrated biotech bets signals a broader shift toward specialization, proprietary data, and operating leverage over volume. For CIOs and technology leaders, the key implication is that AI’s biggest value in regulated industries will come from building tightly controlled, domain-specific data assets and workflows that improve R&D efficiency, decision quality, and trial outcomes rather than from generic models or mass experimentation. This suggests IT organizations should prioritize data infrastructure, governance, and automation that can support high-conviction use cases with defensible datasets and measurable business impact.