ManningBooks
Building Specialized AI Systems (Manning)
General-purpose models are impressive, but they aren’t always the right fit for domain-specific or mission-critical applications. Prompt engineering and RAG can take you a long way, but there comes a point when a model needs deeper knowledge of your domain, tasks, and constraints.
Martin Logan, Eric Merritt, and Richard Carlsson
This book explores how to build AI systems for those situations. It covers the practical tradeoffs between prompting, RAG, and fine-tuning, along with techniques such as supervised fine-tuning, RLHF, LoRA, and QLoRA. The focus isn’t only on adapting models, but on building specialized agents and applications around them.
What I find especially useful is that the book starts with a decision many teams are facing right now: when is a general-purpose model good enough, and when is specialization actually worth the added work?
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