AI-Enabled SDLC: Let the Robot Do the Work

Theory is great, but what about getting your hands dirty with some real problem-solving? This tutorial is about building your own AI Operating System that you'll take home and use immediately. Join Melissa Benua and Ryan Lee for a hands-on session where you'll construct a personalized AI toolkit that solves YOUR specific testing problems, regardless of your coding background. We'll start by deconstructing the modern SDLC, the same one you're already working in, and show you exactly where AI accelerates each phase. Then we'll prove a critical insight: code is now cheap. AI can generate functions, test cases, and automation scripts in seconds. What's expensive? Knowing what problem to solve and how to verify it's solved correctly. That's where testers become invaluable. During this tutorial, you'll build your AI-OS, a configured, customized environment with prompts, workflows, and integrations tailored to your testing challenges. Through live exercises, you'll use it to generate test automation from scratch (no prior coding required), refactor legacy test suites in minutes instead of days, create data generators and mock services on demand, debug failing tests by having AI explain root causes, and transform vague requirements into executable test strategies. This isn't about organizational transformation or governance frameworks. It's about YOU walking out with a working system ready for Monday morning. You'll see how the tester's role evolves when anyone can write code: from script-writer to problem-solver, from test executor to quality strategist. Bring your laptop and real problems from your day job. Leave with a functional AI-OS and skills that transform how you work.