What Are the Best AI Skills for “vector database”?
7 skills tagged “vector database”, each forged from a YouTube creator's methodology.
Production RAG Pipeline Engineering Framework
Transform a prototype RAG system that works on 10 documents into a production-grade, debuggable, and scalable system that works on 10,000+ documents without breaking.
12 Sept 2026Mohamed Naji AbooNaji RAG from Scratch Architecture
Build a fully functional Retrieval-Augmented Generation (RAG) system using LangChain that answers questions from private or recent documents an LLM was never trained on.
12 Sept 2026Sujan AnandSujan Anand RAG Application Build Framework
Build a fully working Retrieval Augmented Generation (RAG) system that answers questions from your own documents accurately, with zero hallucinations, by grounding every AI response in retrieved context.
28 Aug 2026Tejas AITejas AI Agentic AI Builder Framework
Design, build, and deploy production-grade AI agent systems by applying the complete Agentic AI methodology — from core loop architecture through RAG, vector memory, multi-agent topologies, and safety guardrails.
21 Aug 2026KodeKloudKodeKloud Complete RAG System Design Skill
Design, build, evaluate, and extend a production-ready Retrieval Augmented Generation (RAG) pipeline for any knowledge-base use case, using the right chunking strategy, vector database setup, retrieval metrics, and advanced RAG variant for the scenario.
31 July 2026T3chFestDenisov Agent Specialization RAG vs Fine-Tuning Framework
Given any AI agent use case, correctly decide whether to use RAG, fine-tuning, or a hybrid architecture — and implement the chosen approach without common data and retrieval mistakes.
18 July 2026Cole MedinCole Medin RAG 2.0 Agentic Knowledge System
Build a knowledge retrieval system where an AI agent reasons about whether to query a vector database, a knowledge graph, or both — delivering far more accurate and relational answers than naive RAG alone.
3 July 2026