产品官方一手
AWS 提出 Trust in Depth：分层设计让 AI 智能体更自主且可控
Trust in Depth: Giving agents more autonomy without losing control
精选理由
AWS 把智能体自治拆成五层可控框架，做企业级 agent 落地的可以照着设计权限和验证机制。
AWS 发布 Trust in Depth 方法论，针对企业想让 AI 智能体承担更多工作但担心其行为不可靠的问题。该方法包含 scope、know、bound、observe、prove 五个层次，核心思路是智能体行为可验证时允许自主执行。需要人工判断的决策则保留人类介入，避免完全放手带来的失控风险。
原文 · AWS Machine Learning Blog
Trust in Depth: Giving agents more autonomy without losing control
Enterprise leaders want AI agents to take on more work but don't fully trust them to act correctly every time. Trust in Depth is AWS's layered approach-scope, know, bound, observe, and prove-that lets agents act on their own when their actions can be verified, reserving human judgment for the decisions that need it.
