Unverified60% confidenceFactExact time
Combining LLMs with tool calling, memory mechanisms, and planning capabilities forms an Agent with autonomous action capabilities.
2
Sources
60%
Confidence
Long-term
Relevance
7/7/2026
First Seen
Sources
Vercel eve框架深度解析：AI Agent如何成为全新软件形态
rss7/3/2026
Related Claims
VerifiedAn Agent in the LLM context typically has four core components: perception, planning, action, and memory85% similarUnverifiedLLM兴起后，多智能体系统中的Agent从刚性规则执行器转变为具备自然语言理解与生成能力的柔性智能体，能够动态调用外部工具81% similarUnverified现代基于LLM的Agent通过自然语言角色描述和工具调用能力获得自主执行任务的能力，无需手工编程定义行为逻辑81% similarUnverified智能体的许多能力实际上是由Agent所运行的框架在LLM外部实现的，而非LLM本身80% similarUnverified自主型Agent的核心能力包括工具调用（Tool Use）、记忆管理（Memory）和自我反思（Reflection）79% similar
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