23 stories
My research agent had read about 20,400 documents. It had concluded nothing. Not metaphorically. The knowledge store held roughly twenty thousand rows — papers, articles, PDFs, nightly log entries — and there was nowhere in the system that said what any of it meant.
RAG stands for retrieval augmented generation. Strip the jargon and it is one idea: the model does not know your documents, so before you ask it a question, you look up the relevant passage yourself and paste it into the prompt. Retrieve, augment, generate. That is the whole trick.
Built for the TigerGraph Agentic GraphRAG Hackathon. Repo and dashboard linked at the end. RAG retrieves text. GraphRAG adds structure. Agentic GraphRAG lets a model plan its own investigation. Everyone assumes the third one is better — but by how much, and on which questions?
Short answer: Model Context Protocol documentation is versioned by date, not by number. Each revision has its own specification pages, a schema published beside them, and a changelog recording what moved since the previous revision.
Why Autonomous SRE Needs Episodic Memory: How We Built Opsight with Hindsight Every on-call engineer knows the sinking feeling of getting paged at 3:14 AM for a SEV-1 outage that feels eerily familiar, yet nobody can remember which config flag or database lock script resolved it last time.
Showing 23 of 23 stories
You're all caught up.
Get the top AI news and tools straight to your inbox every week.
Weekly · AI news from Dev.to AI
Join 15,000+ AI enthusiasts
