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CONCEPT

Updating to Remain the Same

Chun's paradoxical diagnosis: the compulsion to stay current—to adopt the latest model, learn the latest feature—produces not change but perpetual provisionality, a chronic state of adaptation that never arrives at durable competence.
The updating paradox is that the imperative to update does not produce progress toward a stable state; it produces a perpetual present in which the user is always adapting, always learning, and never arriving. Each new model, feature, or capability threshold requires re-learning—not from scratch, but enough to destabilize the workflow finally optimized for the previous version. The investment in expertise does not compound; it depreciates as the tool changes. The result is a condition of permanent precarity disguised as permanent possibility: the builder has access to more powerful tools than ever and a chronically unstable relationship with their own capability, because the capability is borrowed from a system that will be different tomorrow. The updating produces not mastery but provisional competence, not arrival but perpetual transition. And the transition itself becomes the stable state—crisis metabolized into ordinary, transformation habituated into background.
Updating to Remain the Same
Updating to Remain the Same

In The You On AI Field Guide

Chun's concept emerged as a diagnosis

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