Mastering GenAI, LLMs & RAG
From prompt to production: the complete guide to building with large language models.
by Amol Katkade
A thorough, engineering-focused guide to generative AI: how LLMs work, prompt and context engineering, embeddings and vector search, retrieval-augmented generation, evaluation, and shipping reliable, cost-aware GenAI systems to production.
- How LLMs, embeddings & vector search work
- Production RAG: chunking, re-ranking, grounding
- Evaluation & cost control
- Prompt + context engineering patterns
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From the opening pages
What is Generative AI? Generative AI refers to a branch of artificial intelligence that focuses on creating new data — text, images, code — rather than merely analyzing or classifying existing data. Unlike traditional systems that draw a line between categories, generative models learn the underlying patterns of their training data and produce genuinely new outputs. This book takes you from that foundation all the way to shipping reliable, cost-aware GenAI systems in production.
Table of contents (excerpt)
- Foundations of Generative AI
- Prompt & Context Engineering
- Embeddings & Vector Search
- Retrieval-Augmented Generation (RAG)
- Building LLM Applications
- Fine-Tuning & Customization
- Evaluation & Guardrails
- Deployment, Scaling & Cost
81+ pages · instant PDF download
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