#rag

Wiki 7

• Agent Memory Components (Extractor / Store / Retriever) The three-part decomposition of an agent memory system and the one hard decision at each layer
• Agentic Search Search an agent decides when and how to run, across many context sources each with its own native search tool
• Agentic Search for Context Engineering Leonie Monigatti's case that context engineering is ~80% agentic search, with three demos on what each search tool can and can't do
• Leonie Monigatti AI engineering writer at leoniemonigatti.com on RAG, context engineering, embeddings; workshop speaker
• Limitations of Naive RAG Failure modes of naive top-K retrieval that motivate richer agent access patterns
• Memoryfields — agent memory as a file format Cal Paterson's portable agent-memory format — markdown pages plus an optional SQLite vector index in a zip — a data structure, not a pipeline
• Mintlify's ChromaFs: A Virtual Filesystem for AI Assistants How Mintlify built a virtual filesystem to replace sandboxes and RAG for their docs assistant