Expired50% confidenceFactTime unknown
Orchestration-Based Agents combine LLM reasoning capabilities with deterministic workflow logic, allowing developers to define when an Agent should make decisions versus follow a fixed process.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
Getting Started with Agent Development: 3 Agent Types × 8 Core Mechanisms Fully Explained
bilibili赋范大模型课堂
Related Claims
UnverifiedAgent的工具调用决策完全依赖大模型的语义理解和逻辑推理能力，不是程序员用if-else硬编码控制的80% similarUnverifiedTerminal Agents introduce an LLM reasoning layer that enables them to adjust subsequent strategies based on real-time command output, a capability known in engineering as 'Reactive Planning'76% similarUnverifiedThe technical essence of Agent-type tools is an LLM-based autonomous decision-making loop, i.e., the ReAct framework (Reasoning → Action → Observation → Re-reasoning).76% similarUnverified纯智能体（Autonomous Agent）将决策权交给大模型，工作流编排（Workflow）保留决策权在开发者手中75% similarUnverified现代LLM Agent的核心逻辑可归结为一个循环：接收目标、调用LLM、解析输出、执行工具、重复迭代75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/57777API
curl https://kongchang.com/api/v1/knowledge/claims/57777MCP
get_claim(id=57777)