"Am I Crazy?" [Wading Through AI - Episode 3]

AI adoption creates deeply uneven experiences, leaving users questioning whether they or the technology are at fault. This divergence stems from the technology’s inconsistent utility, where high-value productivity "pockets"—such as generating code bindings or customizing marketing collateral—are separated by voids of low reliability or negative utility. Corporate mandates to force AI usage often ignore these nuances, leading to "work intensification" rather than genuine efficiency gains. Furthermore, psychological reinforcement, akin to a slot machine, causes users to overvalue occasional successes while ignoring frequent failures. Reliable assessment requires moving beyond self-reported metrics and hype-driven expectations toward identifying specific, automatable tasks. Utilizing top-tier models is essential for gauging true potential, as lower-end tools often provide misleading representations of AI’s current capabilities.