Rag
7 practitioners working with Rag:
Agent Memory Systems
How AI agents implement memory: short-term context, long-term storage, vector retrieval, and the architecture that ties it together.

Dylan Freedman's Local Semantic Search
How the NYT AI Projects Editor built Semantra, an open-source privacy-first tool for searching PDFs and documents by meaning instead of exact keywords

Eugene Yan's Personal AI Workflow
How an Amazon Principal Scientist builds personal AI tools for writing, reflecting, and staying informed

Jason Liu's Structured Output Methodology
How the Instructor creator built tools that force LLMs to return validated, type-safe data
Jerry Liu's Files-First Agent Architecture
The LlamaIndex founder on why filesystems are becoming the universal interface for AI agents—and why RAG is evolving beyond vector search

Stan Girard's Open Source RAG Framework
How the Quivr creator went from weekend prototype to 38K GitHub stars and Y Combinator backing
Vector Databases for Personal RAG
Compare Chroma, Qdrant, pgvector, and Pinecone for your personal knowledge system. Local-first options, setup guides, and honest costs.