AI Prompt Engineering

One-Month Study Plan to Master LLM Prompting, RAG, Evaluation, Safety, and a Job-Ready Portfolio and Land High-Paying AI Jobs with 30-Day Self-Learning System

By: Jonathan Whitestone

Narrated by: Virtual Voice

AI is changing how work is done, and the people who know how to direct AI reliably are becoming some of the most valuable professionals in the market. But prompt engineering is not “prompt tricks.” Real prompt engineering is a system: clear output contracts, multi-step pipelines, evaluation tests, grounded retrieval (RAG), and safety controls that prevent hallucinations and prompt injection.

AI Prompt Engineering is a practical, self-learning textbook designed to take you from beginner to job-ready in 30 days. You will learn how to write professional prompts that produce consistent results, build multi-stage workflows (plan → draft → edit → QA → final), and measure quality using evaluation sets, scoring rubrics, and regression testing. You will also learn modern grounding methods—document-grounded prompting and retrieval-augmented generation (RAG)—using the evidence-quote discipline, so your outputs are auditable and trustworthy.

This book is built around a graduation capstone: a complete Prompt Engineer Portfolio Launch. By the end, you will produce five portfolio artifacts that employers and clients can review immediately: a pipeline prompt pack, evaluation proof system, grounded RAG template with test cases, safety audit report with red-team prompts, and a polished portfolio pack suitable for PDF/Notion publishing.

Whether you’re a student, career switcher, educator, business operator, or creator, this book gives you a structured path to one of the most important skills of the AI age: turning AI from a toy into a reliable production tool.

Inside you’ll learn:

• Professional prompt structure: role, task, context, constraints, output format

• Multi-step workflow prompting and modular prompt design

• Validation, repair, retry loops, and safe fallback logic

• Evaluation sets, scoring rubrics, A/B testing, and regression tests

• RAG and document-grounded prompting with citations discipline

• Prompt injection defenses, output sanitization, monitoring, and governance

• Portfolio packaging, case studies, offers, proposals, and first client plan

If you want a real skill, a real portfolio, and a real path into high-paying AI work, this is your one-month roadmap.