Unverified50% confidenceFactExact time
Error feedback refers to failure information flowing into the current task context so the Agent makes a different choice, but this does not mean the Agent learns permanently unless the system is deliberately designed to store and leverage this experience.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThere is a risk that a single Agent handling tasks may go off track (hallucinate), potentially misjudging an order and issuing an erroneous full refund.75% 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.74% similarUnverified错误自我修复能力是Agent感知-决策-执行闭环架构的直接体现，也是与传统软件最本质的区别之一74% similarUnverifiedThe 'repetition' phenomenon is a typical failure mode for large models in agent scenarios, usually stemming from reward design flaws during the reinforcement learning phase or a lack of effective termination judgment mechanisms.73% similarVerifiedIn real-world Agent development, evaluating agent performance, debugging erroneous behavior, and setting safety boundaries are often more challenging than building basic functionality.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1005697API
curl https://kongchang.com/api/v1/knowledge/claims/1005697MCP
get_claim(id=1005697)