AI/MLJuly 202610 min read
Hybrid Search and Reranking: Better RAG Retrieval
Boost RAG accuracy with hybrid search and reranking, fusing BM25 keyword search with vector search, then reranking with cross-encoders before generation.
Read MoreBlog
AI / Machine Learning
Deeper machine learning articles — model selection, embeddings, and the core ML concepts behind applied AI systems.
5 articles
AI/MLJuly 20269 min read
Choosing an Embedding Model: A Practical Benchmark
A practical framework for picking an embedding model for RAG: dimension versus cost versus recall, why MTEB scores can mislead you, and a script to benchmark candidates on your own data.
Read More
AI/MLMay 202610 min read
Semantic Search with pgvector: Skip the Dedicated Vector Database
You probably do not need Pinecone. How to build production semantic search with pgvector inside the PostgreSQL you already run, indexes and hybrid search included.
Read More
AI/MLApril 20269 min read
RAG vs Fine-Tuning: An Honest Decision Framework
RAG and fine-tuning solve different problems, and most teams pick wrong. A practical framework for deciding which one your LLM feature actually needs.
Read More
AI/MLMarch 202612 min read
Building Production RAG LLM Applications: Architecture, Chunking, and Evaluation
A practical guide to architecting production-grade Retrieval-Augmented Generation systems using LangChain, pgvector, and RAGAS evaluation metrics. Covers chunking strategies, vector store setup, retrieval optimization, and how to measure answer quality in real deployments.
Read More