Why LLM-Decoupled Research Architecture Matters The target keyword is LLM decoupled search architecture . In AutoSearch terms, this means the research tool is separate from the model that plans, reasons, or writes the final answer. AutoSearch retrieves source material through MCP across 40 channels, including 10+ Chinese sources. The agent host chooses the LLM and decides how to synthesize the evidence. This architecture is practical because model choice changes often. Source needs change differently. A team should not rebuild channel access every time it changes a model, editor, or agent framework. Architecture issue When retrieval and reasoning are fused together, debugging becomes hard. If the answer is wrong, did the tool miss sources, did the model misunderstand them, or did the product hide the evidence trail? LLM-decoupled architecture separates those concerns. AutoSearch focuses on open-source deep research: source routing, channel access, and evidence return.…