Systems | Development | Analytics | API | Testing

This demonstration shall suggest those baby steps that should encourage most of us (the testers) to inculcate the habit of exploring* GenAI and LLMs. The exploration shall help understand why, what, where, when and how we should use these rapidly moving technologies to bring efficiency and better thinking in our day-to-day testing work.

Let's talk about the real-world journey of operationalizing AI—what it looks like behind the scenes when you’re scaling solutions, building support systems, and doing it all with a lean team. There are plenty of brilliant AI experts—folks doing deep work, research, experimentation, and implementation. This session complements and focuses on how to operationalize, centralize and scale your team, organization and company!

Andy Steinmann of MarketAxess shares how access to Apache Kafka experts—not just software—became the turning point in MarketAxess’ shift to Confluent Cloud.

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.

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.

- 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.