Expired50% confidenceBenchmarkExact time
Research by Anthropic indicates that in production environments, more than 30% of Agent task failures originate from improper loop design.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/7/2026
First Seen
Valid until: 10/5/2026(expired)
Sources
Related Claims
Unverified常见的Agent失败模式包括无限循环、目标漂移、过度自信以及工具误用73% similarUnverifiedAccording to Gartner's prediction, by 2025, more than 30% of enterprise AI projects will fail due to a lack of proper operational infrastructure rather than insufficient model capabilities.70% similarUnverified工具设计应遵循动作幂等、错误明确的原则,否则模型调用失败无法恢复,工具描述质量直接决定Agent成败69% similarUnverifiedA 2023 DeepMind study showed that approximately 30% of robot training failures could be traced back to poorly designed reward functions68% similarUnverifiedA single context window exhibits three typical failure modes when handling complex tasks: agent laziness, self-preference bias, and goal drift.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/147826API
curl https://kongchang.com/api/v1/knowledge/claims/147826MCP
get_claim(id=147826)