Amazon will present its framework for engineering trustworthy AI agents at VB Transform 2026

AI agents are increasingly proficient at executing business tasks autonomously, but IT leaders are cautious about granting permissions to access enterprise systems. Part of the challenge lies in how AI reliability is measured. Industry standards often rely on EVAL scores, which… AI agents are increasingly proficient at executing business tasks autonomously, but IT leaders are cautious about granting permissions to access enterprise systems. Part of the challenge lies in how AI reliability is measured. Industry standards often rely on EVAL scores, which provide a static snapshot of performance rather than a measure of overall reliability. These metrics can fail to capture predictability across prompts, environments, and input types, said Bryan Silverthorn, director of the AGI Autonomy research lab at Amazon.Amazon’s AGI autonomy research lab is moving beyond raw performance benchmarks, focusing instead on a structured framework centered on consistency, robustness, predictability, and safety, Silverthorn told VentureBeat during an interview ahead of his session at VB Transform 2026.Rather than assuming that models can be harnessed into safety, Amazon’s approach emphasizes decoupled systems, such as sandboxed environments where agents propose changes that are reviewed by humans before implementation. This strategy aims to bridge the trust gap by prioritizing verifiable interactions, even in highly sensitive domains…