已过期60% 置信事实精确时间
The technical architecture of an Agentic Workflow typically includes a large language model as reasoning engine, function calling interfaces, memory modules, and a planning module
2
来源数
60%
置信度
中期 (~90 天)
时效性
2026/7/2
首次发现
此条事实已过期，仅作历史留存，不再代表当前状态
有效期至：2026/9/30(已过期)
来源
Andrew Ng on AI Agent Development: Evaluation and Error Analysis Are the Core Competitive Advantage
bilibili吴恩达Agentic2026/6/12
相关事实
待验证Mainstream Agent architectures typically use a large language model as the brain, combined with memory modules, planning modules, and tool interfaces to accomplish complex tasks85% 相似待验证Agent层本质是基于大语言模型的自动化任务执行单元，具备工具调用（Function Calling）能力82% 相似待验证Agentic Workflows的底层技术基础包括ReAct框架、Chain-of-Thought提示工程以及Tool Use/Function Calling接口79% 相似待验证Agentic Loop的技术基础是大语言模型的工具调用（Tool Use/Function Calling）能力79% 相似待验证The technical foundation for the shift to the Agent paradigm includes advances in large language models' reasoning capabilities, long-context processing, and Function Calling78% 相似
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