Unverified50% confidenceCautionExact time
In an automated chain, the erroneous output of one agent can become the input of the next, causing errors to amplify at each successive stage.
1
Sources
50%
Confidence
Long-term
Relevance
10/2/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen agents are in a shared environment of erroneous information, correlated behavior becomes a systemic liability, with errors amplified rather than self-corrected76% similarUnverifiedIn Agentic systems, errors can occur at multiple levels including planning, tool invocation, and context management, and upstream errors are amplified along the chain.74% similarUnverifiedIn multi-step agentic systems based on LangGraph, abnormal intermediate steps, tool call failures, or unexpected model outputs may cause incomplete or incorrect data to be written into the memory state, which is known as state contamination.74% similarUnverifiedDeploying AI data queries in an environment where underlying data definitions are disorganized and metric calibrations are inconsistent will produce erroneous conclusions at greater efficiency and mislead decision-making.73% similarUnverifiedAI在机器学习Data Loader场景中倾向于用try-except吞掉异常，可能掩盖数据损坏、标签错误等深层问题72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/967806API
curl https://kongchang.com/api/v1/knowledge/claims/967806MCP
get_claim(id=967806)