Retrieval-augmented generation is how you get AI answers grounded in your own documents instead of guesses. This hands-on guide walks practitioners through building RAG systems that hold up in practice, covering chunking, embedding, retrieval, and evaluation, with hard-won advice on the failure modes nobody warns you about. For developers and technical builders shipping real AI features.
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