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RAG Systems for 2026

Generative AI · Machine Learning · Python

RAG Systems for 2026

By Maya Ellison

4.8 ★ editorial rating

$38.00

  • Format EPUB, PDF
  • Pages 268
  • Published 2026-04-02
  • Language English
  • Skill Intermediate
  • Technology Python / vector search
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Description

Chunking, hybrid retrieval, reranking, citations, and the failure modes that made 2024 RAG demos fall over. Updated for today’s embedding models and eval harnesses.

What you’ll learn

  • Choose retrieval that matches your corpus
  • Ground answers with citations
  • Catch hallucinations with evals

Table of contents

  1. When RAG is the right tool
  2. Chunking that matches the job
  3. Hybrid search
  4. Rerank and compress
  5. Citations users can trust
  6. Evals and drift

Author

Maya Ellison

Builds production LLM systems and writes about practical architecture.