▸ Tag · #pgvector
pgvector.
Postgres as a vector database — pgvector indexing, recall tuning, and running retrieval next to your relational data instead of beside it.
-
ShopifyCommerce RAG is not document RAG
Shopify Plus catalog RAG needs hybrid lexical plus vector search, then commerce ranking on stock, velocity, and margin. Not LangChain on PDFs.
Read post →
-
AIAI coding is like an addiction (in the best way)
A level-by-level map of the AI coding workflow: gateway prompts, codebase RAG, then multi-agent orchestration over MCP, and why manual coding now drags.
Read post →
-
AIVector search vs graph search for RAG
Compare vector search and graph search for RAG. When to use embeddings via pgvector vs relationship-based knowledge graphs, and why GraphRAG often wins.
Read post →
-
AIContext window vs memory: building AI that remembers
Stop context-stuffing your LLM prompts. The difference between the context window and persistent memory, and how RAG + pgvector scale AI agents affordably.
Read post →
-
AI7 mistakes wrecking your production RAG stack
Naive chunking, no reranker, embedding drift, latency blowups: the structural mistakes that wreck a production RAG stack, and the fixes that ship.
Read post →
-
AIPicking the right RAG stack: vector databases for AI
pgvector, Pinecone, Weaviate, Qdrant: a 2026 field guide to picking the right vector store for your AI app, with hybrid search and scaling tips.
Read post →