Unverified60% confidenceFactExact time
The hallucination problem in Agents is more severe than in ordinary dialogue scenarios, because erroneous reasoning is amplified through the action chain.
2
Sources
60%
Confidence
Long-term
Relevance
8/16/2026
First Seen
Sources
四周入门AI Agent开发:零基础学习路线图
bilibili杨淑娟Python8/14/2026
Related Claims
UnverifiedAgent behavior is non-deterministic—the same input may produce different tool-calling sequences—making observability particularly complex.78% similarUnverifiedModel hallucinations, omission of edge cases, and overconfidence in ambiguous instructions tend to erupt concentrated at the seams of human-AI collaboration.77% similarUnverified由于大语言模型存在提示词注入攻击风险和幻觉问题,权限过大的Agent可能在被恶意输入诱导或判断失误时对业务数据、外部系统造成不可逆破坏77% similarUnverifiedIn a LangGraph multi-agent system, passing complete conversation transcripts during agent handoffs wastes tokens and inference compute, and introduces misreading risks, because downstream agents need to rediscover which decisions have been confirmed, which tool results are authoritative, and which issues remain unresolved.76% similarUnverifiedIn multi-agent systems where multiple agents share the same memory space, erroneous information written by one agent can affect the judgment of other agents, leading to behavioral drift or even cascading errors.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/755675API
curl https://kongchang.com/api/v1/knowledge/claims/755675MCP
get_claim(id=755675)