Retrieval Augmented Generation
Why a trained model goes stale, how retrieval fixes it, and what teams actually build with RAG once they have it.
AILLMRAGWeb SearchRetrievalCritical Thinking
The curriculum
3 parts · read in order- 01
Published Why AI Models Fall Behind the Real World Fluency is not freshness. A chatbot can explain the Roman Empire and then fail badly on something that happened last week, and it will sound exactly as confident either way. Here is where the line falls, and why it is a slope rather than a line. - 02
Published Retrieval Augmented Generation: How RAG Helps AI Look Things Up Before It Answers A large language model only knows what was in its training data. RAG lets it look up fresh or private information before it answers. Here is how retrieval plus generation works, the parts of a RAG system, and why it became a default pattern for enterprise AI. - 03
Published What RAG Is Actually Used For: Code, Support, Compliance and Your Own Files RAG is easy to explain and hard to place. Here is what changes when a coding assistant reads your real send_email() helper, when a support bot answers from a manual nobody updated, when a legal answer has to trace to a paragraph, and when the retriever has to ask who is allowed to see the document before it ranks anything.