Building Multi-Agent Applications with Deep Agents

Multi-agent AI systems can be built effectively using Deep Agents, which breaks down complex tasks across specialized workers. This approach utilizes two primary primitives: subagents and skills. Subagents are isolated agents that tackle specific tasks to prevent the main agent's context window from becoming bloated with intermediate steps. Skills offer a progressive disclosure pattern, where an agent is aware of many capabilities but only loads the full instructions when a specific skill is required, which is useful for managing large tool sets. These two patterns can be used separately or together to create more capable and efficient AI systems.