AWS Machine Learning Blog· Shawn Bice·· 17 h ago
Trust in Depth: Giving agents more autonomy without losing control
Trust in Depth: Giving agents more autonomy without losing control
AI summary
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.
Selection record
Threshold 60Official, first-handFirst 62Second 62
AdmittedSum of both 124 ≥ twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：AWS博客详述AI Agent信任与自主控制技术
- Why it was chosen
- AWS's executive turns two decades of defence-in-depth experience into an agent trust framework, with four concrete layers of control and a product entry point.
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com