Building RAG Systems: From Tutorial to Production (The Real Story)
Last Updated on February 3, 2026 by Editorial Team
Author(s): AbhinayaPinreddy
Originally published on Towards AI.
When Your AI Confidently Lies to Your Legal Team
Picture this: You’re in a boardroom. Your new AI system is answering questions about company policies. Everything’s going smoothly. Then the legal team asks about your data retention policy.

This article explores the inherent challenges of deploying Retrieval-Augmented Generation (RAG) systems beyond tutorial scenarios into practical applications in production, focusing on the five distinct levels of complexity that contribute to system failures, and emphasizing the need for better management, conceptual frameworks, and systematic evaluation processes to ensure AI accuracy and reliability in real-world environments.
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