Recursive Language Models (RLMs) represent a structural departure from flat-context transformer inference — applying language model reasoning hierarchically across document structure to achieve linear compute scaling, coherent multi-document synthesis, and operationally tractable long-context AI. This article presents the complete production architecture, from chunk graph construction and tiered inference to cost modeling, failure design, and observability, written for solution architects and staff engineers building production AI platforms.