The RAG Implementation Handbook: An eBook for AI Engineering Teams

A hands-on eBook for AI engineering teams building retrieval-augmented generation systems, covering chunking strategy, embedding model selection, retrieval evaluation, and the production hardening steps most tutorials skip.

Beyond the tutorial-grade RAG pipeline

Most public RAG tutorials stop at “it returns a plausible answer” — this eBook continues past that point into evaluation methodology, access control, citation, and monitoring for retrieval drift over time.

What’s inside

Chapters on document processing and chunking strategy, embedding model tradeoffs, hybrid retrieval (vector plus keyword), evaluation with a golden test set, and production monitoring for answer quality regressions.