Building Multi-Agent Applications with Deep Agents

Building multi-agent AI systems can be achieved by breaking down complex tasks using a framework called Deep Agents. This approach utilizes two main primitives: subagents and skills. Subagents are specialized, isolated workers that tackle specific tasks to prevent the main agent's context window from becoming bloated. Skills offer a pattern of progressive disclosure, where an agent's capabilities are defined in separate files and only loaded into context when needed. The framework allows for these patterns to be used individually or together to create more sophisticated AI systems.