Unverified50% confidenceOpinionExact time
The root causes of problems in LLM applications are often not code logic errors, but soft factors such as prompt wording, context management, and retrieval strategies, which are difficult to automatically fix with deterministic rules.
1
Sources
50%
Confidence
Long-term
Relevance
8/31/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLLM architectures cannot strictly distinguish between 'instructions' and 'data' at the semantic level, which is the root cause of why prompt injection is difficult to fundamentally eliminate.76% similarUnverified格式问题往往可以通过后处理、约束解码或重试机制来缓解，而语义错误才是难以修复的根本缺陷72% similarUnverifiedIn multi-agent systems, error propagation manifests as fault cascading; because LLMs tend to over-trust inputs (sycophancy), errors that enter the information flow are difficult for subsequent steps to correct on their own.68% similarUnverifiedHaving LLMs directly generate SQL is high-risk, because the model does not understand table structures, field meanings, or business definitions, and easily generates queries that are syntactically correct but produce wrong results.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/828541API
curl https://kongchang.com/api/v1/knowledge/claims/828541MCP
get_claim(id=828541)