AI Working Knowledge

The Essential Guide to Machine Learning, Generative AI, Agents, Business Value, and Responsible Use

By: Finn S. Moriarty

Narrated by: Virtual Voice

AI is everywhere at work. Judgment is still scarce.

Artificial intelligence is moving from a specialist technology into the everyday operating environment of business. The professionals who benefit most will not necessarily be the people who know the most model names or collect the most prompts. They will be the people who understand where AI belongs, how it works, how much to trust it, and when human judgment must remain in control.

AI Working Knowledge is a practical, vendor-neutral guide for managers, founders, analysts, operators, project leaders, consultants, and professionals who need to work intelligently with AI—without becoming machine-learning engineers.

Starting with clear explanations of machine learning, neural networks, deep learning, generative AI, multimodal systems, retrieval, tools, and agents, the book builds a durable framework for turning AI capability into dependable business outcomes.

Inside, you'll learn how to:

• understand what modern AI systems are actually doing—and what they are not;
• distinguish prediction, classification, recommendation, generation, extraction, retrieval, optimization, and action;
• decide when to use prompting, retrieval-augmented generation, tools, fine-tuning, traditional automation, or agents;
• identify high-value AI opportunities by examining real workflows rather than chasing technology;
• design human + AI systems that preserve accountability and make verification practical;
• evaluate AI with representative test cases, evidence, acceptance criteria, and failure libraries;
• manage hallucinations, privacy, cybersecurity, intellectual property, bias, provenance, and model risk;
• understand the economics of AI through cost per accepted outcome, not merely token cost;
• make better build-versus-buy decisions and reduce vendor lock-in;
• design governance that enables responsible experimentation instead of blocking it;
• prepare organizations for AI agents, delegated authority, and increasingly automated workflows; and
• apply the same operating framework across marketing, sales, customer service, finance, operations, HR, research, product development, and software.

The book also includes learning goals, decision drills, reasoning checks, diagnostic questions, Part Mastery Checks, an Answer Guide, a 30-day AI Working Knowledge plan, glossary, and source notes—making it suitable for structured professional self-learning.

This is not a collection of temporary prompt tricks or a catalog of tools that may be obsolete next quarter.

It is a framework for thinking.

See the system. Find the value. Judge the output. Lead responsibly. Put AI to work.

You do not need to know everything about AI.

You need working knowledge.