EU AI Act Article 50 needs a provider-to-deployer evidence contract for machine marks, human disclosures, exceptions, and audit-ready handoffs.
Chrome 的 AI 漏洞流水线说明，安全团队应衡量已验证、已发布和已应用的修复，而不是只统计发现数量。
Chrome's AI vulnerability pipeline shows why security teams should measure verified, shipped, and installed fixes instead of counting discovered bugs.
Agent 可观测性要记录结果、动作、成本、身份和审批。思维链可以提供安全信号，但无法充当生产运行账本。
Agent observability needs evidence about outcomes, actions, cost, identity, and approvals. Chain-of-thought is a signal, not the production record.
AI Agent 分数由模型、Harness、任务、测试和环境共同生成。本文给出五层评测框架，把公开榜单转成可复现的团队选型证据。
AI agent benchmark scores mix models, harnesses, tasks, tests, and environments. Use this framework to build a reproducible coding-agent eval.
AI Coding Agent 备份需要版本化副本、独立权限域和真实恢复演练。本文给出恢复合同、状态清单、权限矩阵与可执行验收方法。
AI coding agent backups need versioned, isolated copies and tested restores. Build a recovery contract that proves the workspace can work again.
Netflix 约 300 个片目使用过 GenAI 工作流。本文校准这一数字的证据边界，并把公开指南转成可执行、可审计的三段式生产门槛。
