Unverified60% confidenceFactExact time
Modern agents typically use large language models as the decision-making brain, combined with reasoning paradigms such as ReAct and Chain-of-Thought
2
Sources
60%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
AI Agent开发入门：从零构建智能应用的完整学习路径
bilibili小全栈7/10/2026
Related Claims
VerifiedIn the era of large models, within an Agent architecture, the LLM acts as the brain responsible for reasoning and decision-making, tools act as the limbs responsible for interacting with the external world, and the memory module stores conversation history and intermediate states.81% similarUnverifiedAgent能力的底层依赖于大语言模型的推理能力（Chain-of-Thought）以及ReAct（Reasoning + Acting）框架78% similarUnverifiedLarge language models such as Doubao and DeepSeek can serve as the brain of an Agent, responsible for understanding requirements, decomposing tasks, and making decisions.78% similarUnverifiedThe model is the brain of an Agent, taking on the decision-making role, responsible for reading user requests and deciding the next action, but not directly executing actions.77% similarUnverifiedThe name of the React Agent architecture originates from the paper "ReAct: Synergizing Reasoning and Acting in Language Models."77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/484914API
curl https://kongchang.com/api/v1/knowledge/claims/484914MCP
get_claim(id=484914)