Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG by Louis-François Bouchard, Louie Peters

Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG by Louis-François Bouchard, Louie Peters

The core thesis of Building LLMs for Production is that getting a language model to work in a local chat demo is incredibly easy, but getting it to perform reliably, accurately, and securely at an enterprise scale is arguably one of the hardest problems in modern software engineering. Bouchard and Peters challenge the industry tendency to view large language models as general-purpose, hands-off black boxes. Instead, they position foundational LLMs as non-deterministic reasoning engines that must be tightly bounded by deterministic software pipelines to eliminate hallucinations, minimize API latencies, and optimize cloud infrastructure costs.

The textbook stands out by balancing heavy technical theory with hands-on, runnable Google Colab code notebooks. The authors meticulously guide developers past simple prompt wrapper templates into the deep structural layers of the modern AI stack. From the baseline mechanics of Transformer attention heads to advanced context injection via vector indexing frameworks, the text equips programmers with a diverse toolkit. Rather than advocating for a single solution, the book treats prompting, Fine-Tuning, and Retrieval-Augmented Generation (RAG) as a unified spectrum of optimization, detailing precisely when to apply each strategy depending on data privacy constraints and target accuracy metrics.

As our regional tech startups, offshore development centers, and corporate software houses experience a massive surge in AI application building, development teams are running into an expensive scaling wall. While any developer can quickly hook up a basic chat API, companies are finding that their applications routinely fail in real-world environments due to unexpected hallucinations, runaway cloud computing costs, and massive data latencies.

Language: English.

Genre: AI Engineering.

Binding: সেলাই করা বাইন্ডিং

Quality: Premium Quality Books.

Printing: High Quality Printing.

Paper: Eye Friendly paper (Cream White)

Cover: Matt cover (Paperback).