AI is transforming the way we approach software testing, and knowing how to make Large Language Models (LLMs) more intelligent, responsive, and context-aware has become a must.  In my session, “From RAG to Riches: Building AI’s Second Brain,” we’ll explore how RAG bridges the gap between generic AI knowledge and your organization’s real-world data. Picture an AI that doesn’t just generate test cases, but understands your testing landscape and tailors every output to your exact needs—accurate, current, and relevant. 

This talk will give you a practical understanding of RAG’s architecture, show you how to set up your own localized RAG framework, and help you assess its performance using RAGAS metrics like context relevance and faithfulness. Whether you’re in QA, test automation, or simply curious about AI’s growing role in testing, you’ll walk away with hands-on insights to make your LLM-driven testing smarter and more reliable—your own “second brain” for quality assurance