Unverified50% confidenceOpinionExact time
In the face of capability proliferation, relying solely on model-level alignment and refusal is insufficient; it is also necessary to build defense-in-depth across multiple layers including deployment environments, software supply chains, and defensive AI.
1
Sources
50%
Confidence
Long-term
Relevance
9/29/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedModel-level safety alignment is fragile, because open-source model weights are accessible and behaviors are modifiable, meaning the alignment efforts invested by vendors can be erased by simple downstream operations.79% similarUnverified跑分优秀不等于实战能力强,模型可能存在基准过拟合导致分布外任务泛化能力不足77% similarUnverifiedOverly strict permission restrictions reduce AI utility, while overly loose restrictions defeat the purpose of security; the usability-security balance of permission granularity is the key trade-off determining the success or failure of local agent products.76% similarUnverified在模型推理之外构建行为拦截层是当前阶段不可回避的工程选择,这是许多团队迟迟不敢在生产环境中开放AI Agent自主权的根本原因74% similarUnverifiedThe three major engineering barriers of AI Agent performance instability, unpredictable costs, and difficulty closing the quality loop cannot be solved by switching to a stronger model and must rely on systematic engineering approaches74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/960347API
curl https://kongchang.com/api/v1/knowledge/claims/960347MCP
get_claim(id=960347)