The bill for the generative AI integration rush has arrived, and it is denominated in egress costs, token bloat, and idle container memory. For the past two years, engineering teams integrated LLMs via the path of least resistance: layering models on top of existing architectures. For human-facing use cases, this works. Humans provide implicit context, tolerate minor latency, and intuitively course-correct errors.