Systems | Development | Analytics | API | Testing

Most QA teams are still switching between requirement docs, their local codebase, and CI/CD dashboards to get automation done. This session is about closing that gap -using AI not as a code generator you prompt occasionally, but as something closer to an actual QA teammate working inside your IDE. ​Key Takeways:​A working understanding of MCP architecture - how to configure and run local or cloud-based MCP servers to connect your IDE with enterprise tools.

In this interactive AMA session, Brenn Hill, AI executive and author of The Delivery Gap, explores why many AI adoption initiatives fail to create lasting impact despite growing investment and enthusiasm. Drawing from his experience helping engineering organizations adopt AI at scale, Brenn unpacks the common pitfalls that hold teams back and shares practical strategies for engineering leaders to drive meaningful adoption. The session will cover how to align AI with business goals, measure success beyond hype, and build a culture that enables sustainable AI-driven transformation.

When a performance test run goes wrong, the real work begins, which means hours of manual analysis, digging through metrics, and trying to prioritize what to fix first. Agentic Performance Testing (APT) in NeoLoad changes that. In this demo, see how APT's specialized AI agents automatically analyze a failed test complete with a full, stakeholder-ready report, surfacing an executive summary, SLA compliance breakdown, trend analysis. critical findings, a prioritized action plan, and more, all without leaving NeoLoad.

AI writes code faster than any team can check it. Diego Molina thought he had a tooling problem. He didn't. In 37 minutes he shows the workflow mistake most engineering teams are making right now, the one bottleneck that decides whether AI speeds you up or buries you, and the principles that drive his own workflow scale without the noise. Chapters Learn more at saucelabs.com.