Engineers within Google are now expected to use AI for code generation, but frequently encounter capacity constraints due to internal competition for computing power. This internal bottleneck highlights a demand signal for more compute resources within the company.
Internal compute capacity within Google is a binding constraint for AI adoption, indicating that even hyperscalers face infrastructure limits for scaling AI workloads.