<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>RAG on SiBlog</title><link>https://sinimite.work/en/tags/rag/</link><description>Recent content in RAG on SiBlog</description><image><title>SiBlog</title><url>https://sinimite.work/images/og-default.svg?v=20260525-210321</url><link>https://sinimite.work/images/og-default.svg?v=20260525-210321</link></image><generator>Hugo -- 0.156.0</generator><language>en-US</language><lastBuildDate>Fri, 17 Jul 2026 15:40:44 +0900</lastBuildDate><atom:link href="https://sinimite.work/en/tags/rag/rss.xml" rel="self" type="application/rss+xml"/><item><title>RAG Retrieval Engineering: From Hybrid Retrieval to Production Governance</title><link>https://sinimite.work/en/posts/rag-retrieval-engineering-guide/</link><pubDate>Fri, 17 Jul 2026 15:40:44 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-retrieval-engineering-guide/</guid><description>A technical report on designing and implementing the RAG retrieval layer, covering BM25, embeddings, ANN, RRF, reranking, query understanding, access control, evaluation, and deployment practices.</description></item><item><title>Designing Observability and Evaluation for RAG Systems</title><link>https://sinimite.work/en/posts/rag-observability-evaluation-design/</link><pubDate>Fri, 17 Jul 2026 15:06:18 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-observability-evaluation-design/</guid><description>A systematic guide to RAG observability and evaluation, including staged traces, runtime metrics, evaluation datasets, quality scoring, experiment comparison, privacy boundaries, and graceful degradation.</description></item><item><title>Best Practices for Chunking in RAG Systems</title><link>https://sinimite.work/en/posts/rag-chunking-strategies-evaluation/</link><pubDate>Wed, 15 Jul 2026 18:05:16 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-chunking-strategies-evaluation/</guid><description>A technical reference covering RAG chunking strategies, parameter selection, context preservation, and evaluation workflows.</description></item><item><title>The Role of RRF in RAG: A Simple but Not Universal Retrieval-Fusion Method</title><link>https://sinimite.work/en/posts/rag-rrf-retrieval-fusion/</link><pubDate>Wed, 15 Jul 2026 17:37:44 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-rrf-retrieval-fusion/</guid><description>A technical reference on the principles of Reciprocal Rank Fusion, its place in the retrieval pipeline, fusion choices, and production evaluation.</description></item><item><title>Dense + Sparse Hybrid Search in RAG</title><link>https://sinimite.work/en/posts/rag-dense-sparse-hybrid-search/</link><pubDate>Wed, 15 Jul 2026 17:25:30 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-dense-sparse-hybrid-search/</guid><description>A technical reference on Dense + Sparse Hybrid Search, including its principles, fusion methods, suitable use cases, and evaluation approach.</description></item><item><title>A Guide to Building Enterprise RAG Systems</title><link>https://sinimite.work/en/posts/enterprise-rag-system-building-guide/</link><pubDate>Wed, 15 Jul 2026 16:35:23 +0900</pubDate><guid>https://sinimite.work/en/posts/enterprise-rag-system-building-guide/</guid><description>An introduction to the architecture of enterprise RAG data ingestion, hybrid retrieval, access control, generation, evaluation, and observability.</description></item><item><title>What AI Engineers Should Learn in 2026</title><link>https://sinimite.work/en/posts/ai-engineer-skill-value-map-2026/</link><pubDate>Sun, 03 May 2026 20:09:15 +0900</pubDate><guid>https://sinimite.work/en/posts/ai-engineer-skill-value-map-2026/</guid><description>A skill value map for engineers moving into AI application engineering, explaining how the value of basic RAG, prompt engineering, and framework APIs is changing, and why evaluation, governance, and agentic workflows deserve greater investment.</description></item><item><title>The Complete RAG Systems Guide: From Zero to Production</title><link>https://sinimite.work/en/posts/rag-system-complete-guide/</link><pubDate>Fri, 27 Mar 2026 15:06:20 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-system-complete-guide/</guid><description>A panoramic RAG guide covering ingestion, chunking, retrieval, reranking, generation, evaluation, and production operations, with an implementation path from zero to launch.</description></item><item><title>RAG Chunking Best-Practices Guide</title><link>https://sinimite.work/en/posts/rag-chunking-best-practices/</link><pubDate>Wed, 18 Mar 2026 20:40:55 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-chunking-best-practices/</guid><description>A practical RAG chunking guide for AI application engineers, covering default parameters, mainstream splitting strategies, evaluation workflows, and production practices.</description></item><item><title>Notes on Anthropic's Contextual Retrieval</title><link>https://sinimite.work/en/posts/anthropic-contextual-retrieval-reading-notes/</link><pubDate>Wed, 11 Mar 2026 09:00:00 +0900</pubDate><guid>https://sinimite.work/en/posts/anthropic-contextual-retrieval-reading-notes/</guid><description>Reading notes on Anthropic&amp;#39;s Contextual Retrieval, covering semantic loss after chunking, experimental benchmarks, ground-truth evaluation, and production RAG practices.</description></item><item><title>Essential Reading for Contextual Retrieval and RAG</title><link>https://sinimite.work/en/posts/contextual-retrieval-rag-reading-list/</link><pubDate>Mon, 09 Mar 2026 08:30:00 +0900</pubDate><guid>https://sinimite.work/en/posts/contextual-retrieval-rag-reading-list/</guid><description>A Contextual Retrieval and RAG reading list for AI application engineers, covering official Anthropic resources, open-source implementations, evaluation methods, and industry trends.</description></item></channel></rss>