The original title is about ReAct architecture for AI agents, explaining the separation of message layer from internal decision state.

Short summary

ReAct separates the agent's communication protocol (Message layer) from its internal decision state (Thought/Action/Observation). Critically, Thought and Action form a single Assistant message, while Observation must come from external tools—preventing models from fabricating results. This ensures agents ground decisions in reality rather than self-generated hallucinations.

• •ReAct is a state machine pattern enabling agents to reason and act iteratively, not just a prompt format with three fields
• •Messages (User/Assistant/Tool) implement the communication protocol; Thought/Action/Observation describe internal decision stages
• •Tools generate Observations to prevent agents from hallucinating results

Generated with AI, which can make mistakes.