Systems | Development | Analytics | API | Testing

- Building a prototype is easy—but scaling reliable, secure AI is the real challenge. In this demo, we show you how to move past basic chat and into the era of Agentic AI with the ThoughtSpot MCP (Model Context Protocol) Server. The MCP Server acts as a bridge between your data and external LLMs like Claude, OpenAI, and Gemini. It doesn't just answer questions; it reasons through your data model to automatically generate governed, mission-critical Liveboards.

AI is not just changing how we test it's redefining how we lead. This high-impact AMA explores how testing leadership must evolve in an AI-first world. Whether you're managing a lean QA team or scaling quality across a large enterprise, the session offers frameworks and insight to help you lead, not just adapt, through transformation. What you'll take away: About Jaydeep Chakrabarty.

AI tools are getting smarter, and many of them now have access to more than you realize. From test scripts to config files to internal APIs, what starts as "just a helper" can become a hidden risk. In this AMA, Harinee will share where things go wrong when tools are trusted too quickly. We’ll look at real examples, permission pitfalls, and ways to keep your systems safer. If you’re using AI in testing or automation, this session will help you ask better questions. Bring your curiosity and your concerns. Let’s talk about what your tools can do, and what they shouldn't.

A quick overview of Xray Test Management - cutting-edge test management app for Jira. Xray is the leading Quality Assurance and Test Management app for Jira. More than 4.5 million testers, developers and QA managers trust Xray to manage 100+ million test cases each month. Xray is a mission-critical tool at over 5,000 companies in 70 countries, including 137 of the Global 500 like BMW, Samsung and Airbus.

Are your LLM coding agents (like Cursor or Claude Code) hallucinating fixes because they don't know what's actually happening in production? In this video, Matt from Speedscale shows you how to bridge the gap between your local IDE and live production traffic using the Model Context Protocol (MCP). Most observability tools just give you telemetry. Speedscale’s MCP server gives your agent the "inner workings" of actual API calls and payloads, so it can check its assumptions against reality. No more "vibe-coding" and hoping it works; let your agent find the 500 errors and rate limits for you.