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The article argues that AI agents fail in production primarily due to poor distribution, lack of proactivity, and lack of persistent memory, not because of model capability limitations.
A reflection on why AI agents often fail to gain adoption: they force users to switch contexts, creating friction that outweighs perceived value. The author suggests designing agents to integrate directly into existing workflows.