Unverified50% confidenceFactExact time
The decision-making brain of an agent operates based on the reasoning capabilities of large language models (LLMs), with GPT, DeepSeek, and Tongyi belonging to this category.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/28/2026
First Seen
Valid until: 12/27/2026
Sources
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Related Claims
VerifiedThe Chain-of-Thought prompting technique was formally proposed by the Google Brain team in the 2022 paper "Chain-of-Thought Prompting Elicits Reasoning in Large Language Models".74% similarUnverifiedSemantic agents with LLMs at their core understand task intent rather than memorizing operation paths, theoretically enabling a significant improvement in cross-version robustness.73% similarUnverifiedGPT-5.6 的 High/Medium/XHigh 思考模式对应模型生成回答前进行内部推理步骤（思维链）的深度与广度，思考强度越高消耗的推理Token越多73% similarUnverifiedThe greatest advantage of the sandwich architecture is the freedom to choose the currently strongest reasoning model as the agent's brain, without being limited by whether the model itself supports voice.72% similarUnverifiedIn an agent, the large model is responsible for reasoning and planning decisions, while tools are responsible for executing tasks, with tool invocation uniformly controlled and decided by the large model.72% similar
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