"Autonomy is an output of a technical system. Trustworthiness is an output of a design process. Here are concrete design patterns, operational frameworks, and organizational practices for building agentic systems that are not only powerful but also transparent, controllable, and trustworthy. In the first part of this series, we established the fundamental shift from generative to agentic artificial intelligence. We explored why this leap from suggesting to acting demands a new psychological and methodological toolkit for UX researchers, product managers, and leaders."
"Now, we move from the foundational to the functional. This article provides the how: the concrete design patterns, operational frameworks, and organizational practices essential for building agentic systems that are not only powerful but also transparent, controllable, and worthy of user trust. If our research is the diagnostic tool, these patterns are the treatment plan. They are the practical mechanisms through which we can give users a palpable sense of control, even as we grant AI unprecedented autonomy."
Autonomy emerges from technical systems while trustworthiness arises from deliberate design processes. The shift from generative to agentic AI requires new psychological and methodological toolkits for UX researchers, product managers, and leaders. A clear taxonomy of agentic behaviors, from suggestion to autonomous action, supports appropriate research methods and accountability metrics. Attention to risks like agentic sludge is necessary to prevent harm. Concrete design patterns, operational frameworks, and organizational practices translate research diagnostics into actionable treatments. The objective is to provide users palpable control so autonomy feels granted by the user rather than seized by the system, guided by six lifecycle patterns and success metrics.
Read at Smashing Magazine
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