A reflection on how the role of the data generalist has evolved over five years, particularly in light of AI advancements. The core argument remains: generalists are valuable because they define problems in ambiguous environments, not just solve them. The key shift is that AI now fills many specialist roles, amplifying the generalist's reach and reducing the need for deep specialization or heavy coordination overhead. Generalists are now connectors of capabilities — human and AI — navigating wicked learning environments where the problem itself is often unclear.
Sort: