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Trust in Depth: Giving agents more autonomy without losing control

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Imagem: AWS Machine Learning Blog

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.

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In every conversation I have with enterprise leaders, they say the same thing. They want agents to do more, but they don’t trust them to do it right all the time. That’s fair. The same creativity and autonomy that makes agents useful makes them hard to trust. Give an agent a task and it finds its own path to finish it, picking tools and sequencing steps no developer scripted. Run the same task twice and it might take a different route each time. A test that passes today tells you little about…

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