Testing RAG pipelines requires both synthetic queries for controlled evaluation and real traffic monitoring to catch production failures. Learn how to combine both approaches to build reliable, secure, and cost-effective AI systems.
Retrieval-Augmented Generation (RAG) lets AI answer questions using live data instead of outdated training. It cuts hallucinations, updates instantly, and powers enterprise AI today. Learn how it works, where it shines, and what to avoid.
Large language models often answer confidently even when they're wrong. Learn how AI systems are learning to recognize their own knowledge limits and communicate uncertainty to reduce hallucinations and build trust.