{ "item_title" : "Context Engineering for LLMs Applications", "item_author" : [" Carter Zhang "], "item_description" : "Context Engineering for LLMs is the operational handbook for anyone who wants LLMs to behave predictably, efficiently, and responsibly in production. The book reframes prompt engineering as a systems discipline context pipelines that include chunking, compression, vectorization, retrieval orchestration, and memory layers. You'll learn token-economics for large context windows, practical prompt architectures, system and user message patterns, and templates for common tasks.The middle sections cover embedding strategies, vector-store patterns, and RAG designs that ensure relevance, freshness, and cost control. Memory system chapters describe how to design short-term and long-term memory, when to use episodic memory, and how to index and expire context. Security and reliability are core themes: learn prompt injection defenses, context validation, and audit trails. The book closes with evaluation, A/B testing, CI pipelines for prompt changes, and operational patterns for continuous improvement.What's inside: Practical prompt templates and system-message strategies for structured outputs.Token cost modeling and context-window optimization techniques.Chunking, semantic compression, and fragment re-assembly recipes.Embedding strategies, batching, and hybrid index maintenance.Memory architectures: ephemeral, episodic, and persistent memory designs.RAG workflows and retrieval orchestration best practices.Prompt-injection defenses, content filtering, and context validation checks.Evaluation frameworks, metrics, and test suites for context quality.CI/CD for prompts and context pipelines, plus A/B testing patterns.Operational playbooks for latency, scaling, and cost tradeoffs.Who this book is for: Prompt engineers, ML engineers, SREs, and product teams shipping LLM features.Teams that require predictable, auditable, and cost-effective LLM behavior.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/826/587/9798265876911_b.jpg", "price_data" : { "retail_price" : "19.50", "online_price" : "19.50", "our_price" : "19.50", "club_price" : "19.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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