Is "the more complex the agent memory, the better" actually true? Title: Is Complex Agentic Memory Always Needed? Naive RAG Is Stronger Than We Thought URL: ❓ What does the paper ask? Are agentic memory systems (extraction, summarization, graphs, mutation) really better than naive RAG, or are the reported gaps due to weak baselines? ❓ What is the "naive RAG" they compare? 💡 Raw-RAG splits conversations into 256-token windows, embeds them, retrieves the top 128, reranks to 15 with a cross-encoder, and hands them to the LLM. No LLM extraction, summarization, or graph building at all. ❓ What are the results? 💡 Raw-RAG ranks first among memory systems in 6 of 7 settings. On MemoryAgentBench it scores 48.32 vs. Memora's 43.84. Ingestion is far cheaper too: for ~1M tokens, 0.33 hours vs. 26.95 hours for Memora. ❓ Why doesn't the complexity win? 💡 Systems differ more in delivering evidence than in using it. Adding atomic-fact extraction cost 19.62 points, and summaries and graph expansion cost ~6 points each. Transformed stores fell short of raw evidence. #AIAgents# #rag#