LLMs in Production: From language models to successful products by Christopher Brousseau, Matt Sharp
LLMs in Production: From language models to successful products by Christopher Brousseau, Matt Sharp
🚚 ক্যাশ অন ডেলিভারি সারা বাংলাদেশ 🕒 ৭২ ঘন্টার মধ্যে সারা দেশ এ ডেলিভারি
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LLMs in Production: From language models to successful products by Christopher Brousseau, Matt Sharp
The core thesis of LLMs in Production is that a fine-tuned neural network or a clever prompt template is not an actual software product. Moving a Large Language Model (LLM) into production creates a mountain of operational complexity: text models are naturally prone to hallucinations, data leakage risks, unpredictable computing costs, and high inference latency. Brousseau and Sharp introduce an end-to-end framework that treats an LLM as just one component within a larger, data-intensive corporate architecture.
The authors guide readers through the practical realities of building Retrieval-Augmented Generation (RAG) systems, creating automated semantic parsing layers, and managing state across long-running autonomous agent networks. Rather than focusing purely on abstract math or simple tool wrappers, the text details the concrete engineering trade-offs between hosting open-source models (like Llama or Mistral) locally versus consuming closed cloud models. From implementing robust guardrails to protect user privacy to scaling semantic cache systems to optimize infrastructure budgets, the book provides clear, step-by-step corporate case studies showing how high-performance AI software is built.
As our regional software market undergoes rapid digital modernization—with local software houses, banking institutions, and e-commerce platforms rushing to integrate generative AI—engineering teams are hitting a painful production wall. While many local developers can easily build a simple chatbot using a basic API call, very few know how to design an enterprise-grade RAG pipeline that stays accurate, respects data privacy laws, and operates without causing massive cloud cost overruns.
LLMs in Production delivers the exact, battle-tested engineering blueprint needed to break through this operational bottleneck. Christopher Brousseau and Matthew Sharp combine their immense prestige as senior enterprise data consultants to provide an exceptionally practical, code-rich masterclass. They strip away industry hype and abstract math, giving local tech leads, data platform architects, and software engineers the concrete infrastructure patterns required to build secure, low-latency, and highly profitable AI applications. It is an absolute must-read manual for any technical professional serious about mastering the business-critical world of MLOps.
Language: English.
Genre: Enterprise Software Architecture.
Binding: সেলাই করা বাইন্ডিং
Quality: Premium Quality Books.
Printing: High Quality Printing.
Paper: Eye Friendly paper (Cream White)
Cover: Matt cover (Paperback).
