Are your subagents re-reading the same files the supervisor already read? LangChain just shipped a feature to fix exactly that waste. Title: Organizing Context in a Multi-Agent Harness URL: 📝 Overview The deepagents framework now supports "forked subagents" — you can choose whether a subagent inherits the supervisor's full conversation history or starts from a blank context. ❗ Problem it solves Fully isolated subagents had to redo investigation and context-gathering the supervisor already completed, wasting both tokens and latency. ⚙️ Methodology Two modes are offered: Isolated Mode (fresh context) and Fork Mode (inherits the supervisor's full state). Fork Mode stays cost-efficient thanks to prompt caching. 🔧 Use cases ・Worker agents: use fork to continue fixing work the supervisor started ・Reviewer agents: use isolated for an unbiased evaluation ・Researcher and memory agents also pick modes based on their role 📊 Results No hard benchmark numbers are given, but the post reports reduced duplicate context-gathering and tool calls. I think this is a genuinely new lever for designing subagent roles well. #MultiAgent# #LangChain#