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Framework Proposes Five Autonomy Levels to Govern AI Agents Safely in Production

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A developer has published an open-source framework for governing AI agent autonomy, inspired by Garry Kasparov's 2005 observation that process quality determines outcomes more than raw capability. The framework defines five autonomy levels with sixteen controls mapped to OWASP Agentic and ISO/IEC 42001 standards, along with a scoring worksheet and promotion rules requiring evidence before granting greater autonomy. The project was motivated by a Harvard and BCG study of 758 consultants showing the same AI tool produced 40% better results within its competency range but 19 points worse results just outside it. The author argues the key question for AI deployment is no longer human versus no human, but rather how much human involvement each specific use case requires and how safety can be verified. The draft framework is publicly available on GitHub under a CC BY 4.0 license, and the author is seeking feedback from teams running agents in production to help calibrate its thresholds.

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