Organizing Context in a Multi-Agent Harness

Deepagents introduces context modes for supervisor-managed subagents, addressing the trade-off between context isolation and reuse in multi-agent workflows. Traditional isolated subagents receive only a task description in a new context window, which supports independent judgment and prevents unnecessary information from entering the supervisor’s context but can require repeated investigation. Forked subagents instead inherit the supervisor’s conversation history, allowing them to continue work with prior evidence and decisions while benefiting from prompt caching and reduced tool use. The framework recommends fork mode for workers and memory agents that depend on existing conversation context, while isolated mode is better suited to reviewers and researchers that need to assess work independently or investigate self-contained questions. Context modes can be combined with specialized tools, prompts, and permissions to tailor subagents for implementation, verification, research, or long-term memory tasks.

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