Unverified75% confidenceTradeoffExact time
Excessive model caution creates misalignment between internal safety logic and users' expectations for productivity, which is especially costly in paid API scenarios where users pay for waiting time
1
Sources
75%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
The 'Laziness' Controversy Around GPT-5.6 Sol: 70% of Runtime Spent Executing Sleep Commands
Related Entities
Related Claims
UnverifiedThe cost and latency of applying large language models to real-time security moderation remain major obstacles, resulting in a capability gap between the security layer and the generation layer.71% similarUnverifiedPoorly designed system prompts (such as those that overemphasize completing user tasks at all costs) may undermine the model's safety guardrails; the agent framework design, permission controls, and the security of the operated system collectively determine whether such incidents occur.71% similarUnverifiedThe opacity of Auto mode means users cannot clearly perceive which model they are using or how much cost is being consumed, making billing difficult to predict.68% similarUnverifiedLoop Engineering在无人监管下存在成本失控和质量失控两大风险，其中质量失控更隐蔽且不可见68% similarUnverified护栏设计的核心权衡是延迟成本——越复杂的检查逻辑，响应时间增加越多68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/680070API
curl https://kongchang.com/api/v1/knowledge/claims/680070MCP
get_claim(id=680070)