Rag

10 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.

agent-first documentation: writing for machines that read like humans how to write documentation that both humans and AI agents can actually use

Rag

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

Rag

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

Rag

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

PageIndex document index for vectorless, reasoning-based RAG

Personal AI Operating Systems Comparison of 12 open-source personal AI systems: AutoGPT, Open Interpreter, CrewAI, Quivr, Khoj, Haystack, Letta, Leon, and more. Stars, features, setup complexity, and recommendations

Rag

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.