Unverified50% confidenceFactExact time
In traditional software, action sequences are hard-coded by developers with predictable paths that allow for static authorization reasoning, whereas in agent systems the model decides actions at runtime.
1
Sources
50%
Confidence
Long-term
Relevance
9/17/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedReasoning configuration allows developers to control the model's reasoning effort, determining how much reasoning computation the model invests before answering.72% similarUnverifiedTool calling allows models to dynamically invoke external functions during inference and incorporate execution results into the context of subsequent reasoning, forming a closed loop of perception, decision-making, and execution.71% similarUnverifiedReasoning configuration allows developers to adjust the trade-off between accuracy and latency, balancing reasoning depth against response speed.70% similarUnverified执行轨迹记录模型或人类解决问题的完整中间步骤，使训练系统能识别推理链条中具体哪一步出错，从而提供更精细的学习信号70% similarUnverified模型直觉包括判断任务是否需要 RAG、Agent 多步推理或微调等技术路径的选择能力70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/930510API
curl https://kongchang.com/api/v1/knowledge/claims/930510MCP
get_claim(id=930510)