TL;DR: Keep working on long tasks in the background while still answering the user right away. LangChain proposes async subagents for this, since in the standard ReAct loop a single long tool call blocks everything else. Agents Are Going Async (LangChain) Key points ・🧠 Agents need to be responsive (react immediately) and productive (advance many long tasks at once) ・🚧 In a ReAct loop, one long tool call makes every other task wait ・🔀 The design is one orchestrator that stays with the user, plus background workers ・🛠️ Five management tools: start, check, update, cancel, and list async_task ・♻️ Follow-ups use interrupt (default, for corrections) or enqueue (for additions) ・🔔 Results are picked up before the next model call if busy, or wake the orchestrator if idle ・🧪 Available in Deep Agents and Managed Deep Agents, in beta The post has no benchmarks and is a LangChain product write-up, but the design ideas are useful. #AIAgents# #LangChain#