This article explains when to use sub-agents versus agents as tools in multi-agent systems built with the Agent Development Kit. It highlights key differences in how each handles tasks, context, and state, providing practical examples for better architectural decisions.

The article discusses the role of memory in artificial agents, emphasizing its significance for enhancing learning and decision-making processes. It explores various memory models and their applications in developing intelligent systems capable of adapting to dynamic environments. The integration of memory mechanisms is highlighted as essential for creating more effective and autonomous agents.