Unverified50% confidenceFactExact time
大语言模型的自然倾向是生成流畅文本,而Agent工作流需要严格、可预测、机器可读的结构化输出,两者存在冲突
1
Sources
50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
VerifiedThe root cause of Prompt Injection is that large models cannot structurally distinguish between "system instructions" and "user data," as both are presented as natural language text at input time.73% similarUnverifiedThe capability boundaries of intent recognition systems are determined by manually written rules and have limited scalability, whereas large language models, through pretraining on massive text, can handle new tasks that were not explicitly programmed, achieving a paradigm shift from rule-driven to data-driven approaches.73% similarUnverified大语言模型在符号操作、模式识别、定义比对等任务上表现较强,但在需要深层数学直觉和构造性证明的创造性工作上仍相当薄弱73% similarUnverifiedLarge language models naturally tend to generate code that looks complete, including various defensive programming patterns, abstraction layers, and extension points, which are often unnecessary for current requirements.73% similarUnverifiedThere are currently three mainstream approaches for large language models to process spreadsheets—text-based, code generation, and RPA-style—and their common drawback is that the data seen by AI and the data seen by humans come from different processing logic, making consistency difficult to guarantee.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/572587API
curl https://kongchang.com/api/v1/knowledge/claims/572587MCP
get_claim(id=572587)