Expired50% confidenceFactExact time
In the Orchestrator-Worker architecture, the coordinator Agent is responsible for task planning and distribution while the executor Agent focuses on specific subtasks; both AutoGen's GroupChat and LangGraph's StateGraph support this pattern.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/9/2026
First Seen
Valid until: 10/7/2026(expired)
Sources
Related Claims
UnverifiedIn a multi-agent architecture, the Orchestrator is responsible for task decomposition and scheduling, delegating specific subtasks to specialized Sub-Agents for parallel or sequential execution; this is the design pattern of mainstream AI Agent frameworks such as AutoGPT, LangGraph, and OpenAI Swarm.81% similarUnverifiedIn the Agent architecture, the LLM is responsible for intent understanding and step planning, while actual execution is delegated to external tools such as calculators, search engines, and API endpoints.77% similarVerifiedIn LangChain's Agent architecture, the Agent itself is only responsible for reasoning and generating tool-call instructions, while the Agent Executor is responsible for executing tools, handling responses, and managing the iteration loop.75% similarVerifiedAn Agent is an application-layer architecture built on top of an LLM that enables the model to decompose complex tasks, invoke external tools, maintain context state, and iteratively optimize results by introducing mechanisms such as Planning, Memory, Tool Use, and Reflection.74% similarVerifiedThe core architecture of multi-agent systems typically involves an Orchestrator agent responsible for task decomposition and scheduling, along with multiple Worker agents responsible for specific implementation.74% similar
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