Unverified50% confidenceOpinionExact time
智能体式工作流通过迭代打磨能够产出比one-shot生成质量高得多的成果
1
Sources
50%
Confidence
Long-term
Relevance
7/7/2026
First Seen
Sources
吴恩达联手LangChain：LangGraph智能体开发核心解析
bilibili吴恩达机器学习7/6/2026
Related Claims
Unverified迭代优化Skill时每次只提1到2个明确的修改点，准确率非常高，迭代三四轮就能得到满意的结果73% similarUnverified在人机协作光谱上，越靠近全自动一端效率越高但灵活性越低，越靠近全手动一端控制力越强但门槛越高，这是一键生成类工具的共同权衡70% similarUnverifiedDecomposing tasks into verifiable sub-steps can significantly improve execution reliability and reduce the probability of the model hallucinating69% similarUnverifiedAgents are not omnipotent; they require sound scenario design, continuous tuning, and human oversight, with their value lying in automating repetitive process-driven work.69% similarUnverifiedUltra mode can mobilize an entire team of agents working in parallel, with task quality and speed improving as the number of agents increases69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/133595API
curl https://kongchang.com/api/v1/knowledge/claims/133595MCP
get_claim(id=133595)