Anthropic 用 Claude 为 123 个开源库的 239 个入口点生成证明。上线评审仍要核对证明命题、部署工件和残余风险，避免把有边界的证明误读为整库无漏洞。
Anthropic's 123-library experiment shows that LLMs can scale proof writing. A deployment assurance manifest shows what was proved, what ships, and wha
把 Meta Forum 案例转成一份可执行的 AI 工程评审方法：定位瓶颈、定义证据包、划定生产权限，并按真实失败逐步改造工具链。
A caller's knowledge is not identity proof. Use a five-step protocol to exit the call, reopen a trusted channel, contain losses, and preserve evidence
DeepInfer 已提供批次不变与确定性采样能力，但生产验收仍要写清比较对象、环境边界、证据强度和性能代价。
DeepInfer makes determinism a testable inference feature. Audit batch invariance, seed conditions, hardware scope, and serving gaps before deployment.
WhatsApp 隐藏指令事件说明，官方来源的事实可信度与指令权限必须分开，RAG 系统需要审计模型实际看到的内容。
WhatsApp's hidden chatbot instructions show why RAG systems must separate source trust from instruction authority and audit model-visible content.
OpenAI 的低资源编程语言评测把问题从代码翻译推进到行为保留。生产迁移还需覆盖依赖、故障、影子运行、切流和回滚。
