Users attest to higher productivity and point to material but intermediate factors like token use, generated lines of code, pr counts, etc, but there doesn't seem to be a convincing revolution in the quantity or quality of mature software being delivered.
Combine that puzzling impressions of outcomes with a sense, for many, that they don't feel like they have a personal problem that warrants a new tool, and you end up with a pretty earnest and defensible indifference.
To get hold out engineers using AI, the industry needs to be focused on demonstrating relatable workflow improvements and demonstrating practical improvements to finished work product. Instead, policies like token use incentives just rely on luring them into pulling the slot machine handle with the expectation that once they do, they'll join the cadre of other converts who justify their transition with subjective improvements and intermediate metrics.
