RAG-Based Testing Series — Part 1: What Is RAG & Why Your Old Testing Playbook Won't Work Here

Short summary

RAG (Retrieval Augmented Generation) gives AI systems access to real, current data before answering—preventing hallucinations from training data alone. Unlike traditional software where same input produces same output, RAG generates different but equally valid answers. Traditional testing fails here; this series teaches how to build automated testing frameworks for RAG systems.

• •RAG grounds AI answers in real, current data to prevent hallucinations
• •RAG outputs are non-deterministic—same question yields different but valid answers
• •Traditional testing assertions fail for RAG; new frameworks needed

Generated with AI, which can make mistakes.