Fine-tuning changes what a model knows permanently. RAG changes what it sees at runtime. They're not interchangeable — and most agentic use cases don't need fine-tuning at all.
RAG extends an agent's knowledge base without loading it permanently into context. Here's how the pipeline works — from raw documents to retrieved chunks.