Why Most RAG Pipelines Fail in Production

This article explores why most RAG (Retrieval-Augmented Generation) pipelines fail in production, contrasting the simplicity of demos with the complexity and messiness of real-world datasets. It highlights the challenges of AI systems engineering, particularly in data ingestion for scaling RAG to production environments.