Rag on Tyler Wells

Rag on Tyler Wellshttps://blog-theta-seven-23.vercel.app/tags/rag/Recent content in Rag on Tyler WellsHugoen-usThu, 16 Apr 2026 00:00:00 +0000Building Ozark Ridge: Lessons Learned and What I'd Do Differentlyhttps://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-5-lessons-learned/Thu, 16 Apr 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-5-lessons-learned/[Retail AI Series 5/5] What worked, what didn't, what I'd do differently in v2, and why this project matters for e-commerce AI.Building the AI Product Assistant: Context Injection, Multi-Turn Chat, and Cross-Product Retrievalhttps://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-4-ai-assistant/Wed, 15 Apr 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-4-ai-assistant/[Retail AI Series 4/5] How to build a Rufus-style AI assistant that answers product questions, suggests complementary gear, and builds camping loadouts — with conversation history, context injection, and dynamic retrieval.Keyword Search vs Semantic Search: Why Natural Language Queries Need Vector Embeddingshttps://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-3-keyword-vs-semantic/Tue, 14 Apr 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-3-keyword-vs-semantic/[Retail AI Series 3/5] Side-by-side comparison of keyword and semantic search, why keyword search fails on natural language queries, and what the retrieval scores actually tell you.Building the Catalog and Ingestion Pipeline: Archetypes, Embeddings, and ChromaDBhttps://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-2-catalog/Mon, 13 Apr 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-2-catalog/[Retail AI Series 2/5] How to generate 1180 realistic products from 20 archetypes, why product descriptions matter for RAG, and how the ingestion pipeline works.Building AI Search for a Retail Website: The Stack and Whyhttps://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-1-stack/Sun, 12 Apr 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/ozark-ridge-post-1-stack/[Retail AI Series 1/5] Building a mock outdoor retail site with AI-powered product search and a Rufus-style assistant. This post covers the architecture, stack decisions, and why RAG matters for e-commerce.Scoring RAG Answer Quality with an LLM Judgehttps://blog-theta-seven-23.vercel.app/posts/rag-answer-judging/Mon, 26 Jan 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/rag-answer-judging/[RAG Series 3/3] Source URL retrieval tells you whether the right content was retrieved. It doesn't tell you whether the answer was any good. Adding an LLM judge to the eval harness reveals two failure modes that retrieval scoring alone can't see.How to Design RAG Eval Test Caseshttps://blog-theta-seven-23.vercel.app/posts/design-rag-eval-test-cases/Sat, 24 Jan 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/design-rag-eval-test-cases/[RAG Series 2/3] How to write test cases that catch real retrieval problems, why source URL retrieval is a useful proxy metric, and when it isn't enough.RAG Retrieval: Chunking, Embeddings, Reranking, and an Evalhttps://blog-theta-seven-23.vercel.app/posts/rag-retrieval-quality/Thu, 22 Jan 2026 00:00:00 +0000https://blog-theta-seven-23.vercel.app/posts/rag-retrieval-quality/[RAG Series 1/3] Covers chunking strategy, embedding model consistency, reranking, and building an eval harness — including what happened when Voyage AI's free-tier rate limits forced a more resilient architecture.