How Production RAG Systems Stay Stable: The Architecture Behind Controlled Iteration

RAG systems in production often suffer from gradual performance degradation that's difficult to detect and debug. This article demonstrates that production AI pipelines require explicit versioning, continuous evaluation, and automated rollback mechanisms to prevent uncontrolled drift. By treating retrieval, prompting, and model selection as independently configurable elements, teams can safely iterate on their systems while maintaining stability and measurability.