博客來The Practical AI Engineer: A Hands-On Guide to Building Production-Ready LLM and RAG Applications
Moving from a simple prompt to a reliable production system is the hardest challenge in modern software. Stop fighting with ＂vibe-based＂ development and start building AI with the rigor of a systems architect.
This guide provides a technical roadmap for developers moving beyond basic API calls. It focuses on the transition from experimental chatbots to robust, autonomous agents capable of operating in high-stakes environments. You will find detailed strategies for optimizing Retrieval-Augmented Generation (RAG), managing the ＂Intelligence Tax＂ through FinOps, and securing applications against emerging threats like prompt injection.
The content prioritizes the engineering reality of 2026. Rather than focusing on fleeting prompt hacks, it emphasizes stable architectural patterns: semantic caching, multi-agent orchestration, and the deployment of Small Language Models (SLMs) to the edge. Every chapter balances theoretical foundations with functional code, ensuring you can implement observability and evaluation pipelines that actually catch hallucinations.
What’s Inside This Book?Production-Grade RAG: Advanced techniques for vector database optimization and context retrieval.
Agentic Orchestration: Frameworks for building multi-agent systems that solve complex, multi-step tasks.
AI FinOps: Strategies to monitor token burn and maintain unit economics at scale.
Zero-Trust Security: Hardened guardrails to protect your data and prevent unauthorized agent actions.
Small Language Models: Guidance on quantizing and deploying efficient models to local and edge hardware.
Master the tools and tactics required to deliver reliable AI. Get your copy of The Practical AI Engineer and transition from coder to architect.
