Teach your agent to search, read, and process external knowledge. Part of the free AI Agents Academy — every lesson below is open to everyone, no signup required.
Why RAG? Models are frozen in time when they finish training. Retrieval-Augmented Generation (RAG) gives them a search engine for your private data. T...
Beyond Basic Vector Search Simple vector search fails when concepts are spread out or use completely different vocabulary. Production systems use Hybr...
Agentic RAG Instead of a linear pipeline, we can use an Agent to handle retrieval dynamically. An Agentic RAG system can: Query Reformulation: The age...
The Art of Splitting Documents Chunking is the most underrated part of RAG. How you split your documents determines whether retrieval finds the right...
Beyond Vector Search: Structured Knowledge Standard RAG retrieves text chunks. GraphRAG converts documents into a Knowledge Graph of entities and rela...