The ROI-Driven AI Engineer: A Practical Framework for Building AI Systems That Create Measurable Business Value (The Practical AI Engineering Series: ... Monetizing Artificial Intelligence Systems.)
Language: English
Published by Independently published, 2026
- Softcover
- New
Seller: California Books, Miami, FL, U.S.A.California Books
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- Title
- The ROI-Driven AI Engineer: A Practical Framework for Building AI Systems That Create Measurable Business Value (The Practical AI Engineering Series: ... Monetizing Artificial Intelligence Systems.)
- Author
- Pendang, Jhon
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798167986152
- Series
- Book 1 of 1: The Practical AI Engineering Series: Building, Deploying, Managing, and Monetizing Artificial Intelligence Systems.
BUILD AI THAT DELIVERS BUSINESS VALUE—not just impressive technology.
Artificial intelligence is transforming the way businesses operate, but building an AI system is only part of the challenge. The real measure of success is whether that system solves meaningful problems, improves business performance, operates reliably, and delivers measurable financial value.
In The ROI-Driven AI Engineer, Jhon Pendang presents a practical framework for connecting AI engineering with business strategy, system architecture, financial discipline, and responsible implementation.
Designed for AI engineers, software developers, technology leaders, product managers, founders, and business decision-makers, this book explores how to move beyond experimental AI projects and build systems that create sustainable business value.
Inside this book, you will discover how to:
- Choose the Right AI Architecture: Evaluate deterministic systems, machine learning, foundation models, retrieval-augmented generation (RAG), fine-tuning, and hybrid architectures based on real business requirements.
- Understand RAG vs. Fine-Tuning: Identify the difference between knowledge retrieval and model behavior, and determine when each approach makes sense.
- Build Intelligent AI Agents: Design tool-using workflows with clear permissions, human oversight, controlled autonomy, and reliable execution.
- Control AI Infrastructure Costs: Understand cloud expenses, model usage, caching, model routing, and cost optimization while measuring cost per successful outcome.
- Make AI Safe for Enterprise: Apply practical principles for security, privacy, governance, access control, risk management, and responsible AI deployment.
- Move from Prototype to Production: Develop the evaluation, monitoring, testing, deployment, and operational practices needed to run AI systems reliably.
- Build a Profitable AI SaaS Product: Connect customer value, product strategy, pricing, unit economics, customer retention, and sustainable growth.
More than technical concepts, this book connects engineering decisions to measurable business outcomes.
Throughout the chapters, practical Python-oriented examples, business scenarios, financial models, evaluation frameworks, management questions, and implementation checklists help readers understand not only how AI systems are built, but also how their value can be assessed and sustained.
Whether you are developing your first AI-powered product, improving an existing enterprise system, or evaluating an organization's AI investment, this book provides a structured way to think about technology, cost, risk, and business performance.
Build with purpose. Engineer with discipline. Measure what matters.
The ROI-Driven AI Engineer is a practical guide for those who want to bridge the gap between artificial intelligence and real business value.
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