Generative AI Testing Foundations: A Structured Method for Testing, Evaluating, and Governing Generative AI Systems

By Madhu Murty Ronanki

TRUST-FIRST AI ASSURANCE

Generative AI broke the contract classical testing was built on.

The same input can yield a different output, correctness becomes a matter of degree, and the worst failure is a fluent, confident, wrong answer no test case thought to ask about. This book supplies the method that closes the gap: seven trust attributes, a loop that runs from risk to metric to test to evidence, and gates that turn a quality judgment into a decision you can defend. Across four worked systems - a classifier, a retrieval-augmented advisor, a multi-agent orchestrator, and a workforce planner - it moves from failure modes and metrics through red-teaming and release governance to drift, observability, and incident response, then transfers the method into regulated sectors.

Every standard and regulation is verified to primary sources and dated.

Evidence over opinion - on every page.

• Format: Hardcover
• Language: English
• ISBN: B0HGGF1TSD
• ISBN13: 9798906439789
• Release Date: August 2026
• Publisher: Notion Press
• Length: 262 Pages
• Weight: 1.42 lbs.
• Dimensions: 0.9" x 6.0" x 9.0"