<p>The Internet of AI Agents has been proposed as a natural evolution of the Internet of Things and the Artificial Intelligence of Things: a decentralized ecosystem in which autonomous agents interact, cooperate, and learn collectively. Yet, connectivity alone is not sufficient to support large-scale populations of agents acting on behalf of humans, organizations, machines, and other agents. As agentic systems grow in size, autonomy, and operational relevance, the central challenge shifts from enabling communication to governing collective behavior. This editorial argues that the next frontier of networked and distributed intelligence is the emergence of a <i>Society of Agents</i>: a structured population of autonomous AI agents whose interactions are shaped by shared protocols, roles, norms, memory, trust mechanisms, accountability structures, and governance processes. The analogy with human societies is not intended anthropomorphically, but structurally: human societies scale intelligence through language, institutions, collective memory, roles, incentives, and causal accountability; agent societies will require computational counterparts of these mechanisms. We identify shared societal memory and causal governance as two foundational capabilities for this transition. Shared memory enables cumulative collaboration beyond ephemeral message exchange, while causal governance makes distributed agentic operations traceable, auditable, and accountable. We formulate this transition as a scientific manifesto: the next generation of networked intelligence should be designed not merely as collections of increasingly autonomous agents, but as governed computational societies grounded in shared memory, causal accountability, institutional mechanisms, and human oversight. We outline architectural layers, research challenges, and emerging examples of multi-agent orchestration for governable collective agency.</p>