Software testing is moving inside AI coding agents. These agents can generate code, tests, environments, data, reviews, and fixes in the same continuous loop, but that creates a dangerous question: should the system that wrote the bug also decide whether the software is ready to ship? Jason Arbon explores how testing changes when software is generated dynamically, requirements evolve through prompts, and agents work autonomously for hours or days. You will learn how to separate generation from independent validation, capture evidence from agent trajectories, test changing prompts and...
Jason Arbon
Principal
IcebergQA
Jason Arbon has spent his career ensuring the quality of large, complex, and non-deterministic systems. He has built and led quality efforts across Microsoft, Bing, Google Search, Chrome, ChromeOS, Applause, and AI-first testing products. He is the author of Testing AI: Engineering Confidence in Non-Deterministic Systems and co-author of How Google Tests Software. He is a principal at IcebergQA, where he helps teams transform toward AI-first quality engineering and test AI-powered products.