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Engineering LLM Systems: From prototype to production at planet scale
Paperback
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ISBN13: 9798257510281
Publisher: Independently Published
Published: Apr 15 2026
Pages: 656
Weight: 1.90
Height: 1.32 Width: 6.00 Depth: 9.00
Language: English
Publisher: Independently Published
Published: Apr 15 2026
Pages: 656
Weight: 1.90
Height: 1.32 Width: 6.00 Depth: 9.00
Language: English
The book the AI industry didn't know it was waiting for.
Every week, another company burns through six figures moving an LLMprototype to production - and discovers too late that calling an API
is not engineering. That a clever prompt is not architecture. That a
working demo is not a system. This book is the discipline they were missing. Engineering LLM Systems is the first comprehensive field manual
for LLM Engineering - at the intersection of software architecture,
probabilistic systems design, cost engineering, safety governance,
and ethical responsibility. Not a tutorial. Not a tips collection.
A complete operating system for the engineer who builds production AI. 650+ pages. 25 chapters. 7 original production-tested frameworks:
the price. Every framework in this book is implemented in production-grade
Python. Not pseudocode. Not fragments. A complete, modular reference
codebase you can clone today and ship tomorrow.
days of architecture work. At $29.99, that is the highest ROI
technical book purchase you will make this year. This book is for you if:
every other AI book avoids: a modern Hippocratic Oath for LLM
engineers, frameworks for regulatory future-proofing, and a
philosophy of stewardship. This is not a book about language models.
This is a book about the engineers who build systems around them -
and the discipline those engineers need to do it responsibly.
probabilistic systems design, cost engineering, safety governance,
and ethical responsibility. Not a tutorial. Not a tips collection.
A complete operating system for the engineer who builds production AI. 650+ pages. 25 chapters. 7 original production-tested frameworks:
- The Five Properties Model - negotiate trade-offs between
capability, latency, cost, reliability, and safety - Total Cost of Intelligence (TCI) - model the true cost
beyond token pricing: orchestration, human review, failure
remediation - LLM-FMEA - aerospace-grade pre-mortem methodology adapted
for probabilistic AI - Prompt Pattern Language (PPL) - elevate prompt design from
craft to governed engineering discipline - The Eight-Layer Stack - complete vertical blueprint from
GPU memory to compliance audit - The Autonomy Gradient - calibrate AI agent freedom with
clear engineering controls at every level
the price. Every framework in this book is implemented in production-grade
Python. Not pseudocode. Not fragments. A complete, modular reference
codebase you can clone today and ship tomorrow.
- Hybrid RAG Pipeline - dense + sparse retrieval,
Reciprocal Rank Fusion, cross-encoder reranking, source attribution - Multi-Model Router - cost-aware query routing with
automatic fallback chain across model tiers - Evaluation Harness - CI/CD deployment gate with
LLM-as-Judge, Five Properties measurement, pass/fail decision - Circuit Breaker + Cost Governor - four-dimensional budget
control (per-request, per-session, per-minute, daily) - the system
that prevents the $47,000 invoice - Input Guardrails - prompt injection detection, PII
redaction, toxicity filtering - Full Test Suite - 5 test classes against real LLM-FMEA
failure modes
days of architecture work. At $29.99, that is the highest ROI
technical book purchase you will make this year. This book is for you if:
- You have received the surprise invoice after a production
LLM deployment - You have debugged a hallucination at 2 AM
- You are scaling an AI team and need shared engineering language
- You are a technical founder who needs to ship AI that
actually works - You are ready for the most consequential engineering role
of the decade
every other AI book avoids: a modern Hippocratic Oath for LLM
engineers, frameworks for regulatory future-proofing, and a
philosophy of stewardship. This is not a book about language models.
This is a book about the engineers who build systems around them -
and the discipline those engineers need to do it responsibly.
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