Snap Cut 1,000 Jobs As AI Generated 65% Of Its New Code

The Common Question

Are companies using AI as a reason to cut jobs and headcount?

The Lesson in This Case

Snap cut roughly 1,000 employees – 16% of its workforce – while AI was already generating more than 65% of its new code and absorbing a large share of customer support volume, meaning smaller teams held output steady rather than losing ground. The real driver was not automation in the traditional sense but a deliberate shift in cost structure: variable labor expense converted into scalable AI infrastructure with front-loaded capital spend and declining marginal costs per unit of output. Senior leaders reviewing their own AI budgets should stop framing these investments as productivity tools and start treating them as capital allocation decisions – because that is exactly how the companies acting on this data are already treating them.

Originally reported by Meer | English edition. Read the full story here.