AI-Driven Quality Engineering

Abstract - AI-Assurance is reimagining quality development, Quality Engineering (QE) faces unprecedented challenges and opportunities. While developers can now produce 10-100x more code using Vibe Coding techniques, QE processes haven't scaled accordingly, creating critical gaps in validation and verification. This talk explores how AI Augmented Testing can revolutionize Quality Engineering through intelligent test generation, time-aware knowledge graphs, and AI Agentic testing workflows that shift focus from reactive testing to proactive quality and test optimization.  

We'll examine the evolution from traditional coding-centric approaches to Vibe Testing techniques of neurosymbolic modelling,  system thinking, exploring how smaller, autonomous test teams can achieve faster iteration cycles while managing risks like hallucination-driven bugs and insufficient context for AI agents. The talk will cover practical implementation strategies, from well-defined bounded projects like photonic device modelling to enterprise-scalable meta-cognitive testing platforms.  

Focusing on key take away areas include building new AI literate teams, sharing enterprise knowledge context engineering that provide Agentic AI test agents with domain-specific context, orchestrating agentic workflows within existing DevOps/Post-Agile approaches, and transforming into AI-Driven Quality Engineering blueprints from reactive ticket-based systems to proactive, autonomous resolution mechanisms. Attendees will learn how to minimize mean time to repair, scale workflow reuse, and free human resources for strategic innovation while maintaining quality at scale.