RAG

SNEWPAPERS is a useful Show HN signal: the strongest agentic search products do not replace search results with prose. They teach the agent to operate a real search system.

OpenAI shipped an open-weight PII redactor. Here is how to wire it into a real ingestion pipeline locally, fast, with zero leaks, and how it benchmarks against Presidio and a regex baseline.

A production-grade RAG pipeline with Claude. Chunking that survives real documents, retrieval tuning that actually moves the needle, citation tracking, and the prompt caching trick that makes RAG cheap enough to ship.

Google's AI notebook that lets you ground a Gemini chat in your own uploaded sources. Generates summaries, mind maps, and podcast-style audio overviews.

Open-source AI orchestration framework by deepset. Modular pipelines for RAG, agents, semantic search, and multimodal apps. Pipeline-as-graph architecture with explicit control.

Agents forget everything between sessions. Here are the patterns that fix that: CLAUDE.md persistence, RAG retrieval, context compression, and conversation summarization.

How RAG works, why it matters, and how to implement it in TypeScript. The technique that lets AI models use your data without fine-tuning.

Most popular LLM framework. 100K+ GitHub stars. Chains, RAG, vector stores, tool use. LangGraph adds stateful multi-agent workflows with cycles and persistence.

TypeScript-first AI agent framework. Workflows, RAG, tool use, evals, and integrations. Built for production Node.js apps. Open-source.

LLM data framework for connecting custom data sources to language models. Best-in-class RAG, data connectors, and query engines. Python and TypeScript.