AI Agent Knowledge Systems 2026: Memory vs RAG vs Fine-Tuning

Three approaches for agent knowledge. Memory: stores past interactions, good for personalization, limited capacity. RAG: retrieves from external sources, best for factual accuracy, scalable. Fine-tuning: permanent changes to model weights, best for style/tone, expensive. Combine: use memory for recent context, RAG for facts, fine-tuning for behavior. Real data: RAG+memory gives 92% accuracy vs 72% with just one.