In this session we'll delve into the powerful capabilities of Microsoft Copilot Studio, starting with an introduction to the service and exploring your options. Learn how to configure Copilot from scratch, including adding knowledge, customizing topics, and selecting channels for a tailored experience. In the second half of the session, we’ll demonstrate how to publish and seamlessly integrate Copilot into a Static Web Page on Azure. Finally, we'll conduct thorough testing to ensure our Copilot is ready to go!

In this session we'll delve into the powerful capabilities of Microsoft Copilot Studio, starting with an introduction to the service and exploring your options. Learn how to configure Copilot from scratch, including adding knowledge, customizing topics, and selecting channels for a tailored experience. In the second half of the session, we’ll demonstrate how to publish and seamlessly integrate Copilot into a Static Web Page on Azure. Finally, we'll conduct thorough testing to ensure our Copilot is ready to go!

Discover how Microsoft Power Platform empowers you to build impactful business solutions – from simple no-code apps to advanced, extensible systems with pro-code capabilities. This session will introduce the core components of the platform – including Power Apps, Power Automate, and Copilot Studio, and demonstrate how they work together to streamline processes, enhance user experience, and integrate AI capabilities. Whether you're a beginner or a developer looking to accelerate solution delivery, you'll gain practical insights into how to start creating your own apps using Power Platform tools.

AI coding agents can generate features in minutes, write tests, refactor modules and suggest architectural changes — and they will do all of it with the same confidence regardless of whether your project has any structure or none at all. That is the actual problem. In this session, we will explore what happens when the same AI agent works inside a disciplined engineering workflow versus without one, using a live Next.js application built entirely with GitHub Copilot inside Visual Studio Code. We will compare two versions of the same feature: one built without guardrails, one built with them. The difference is not subtle. The structured version introduced 60% fewer issues overall, 86% fewer critical bugs, and prevented 12 specific defects before a single line of review was written - not because the AI suddenly became smarter, but because the context it worked with was better. The session is not about AI replacing developers. It is about a concrete, observable truth: the quality of AI-generated code is a direct reflection of your architecture guidance, conventions, and repository context. Engineering discipline is no longer just good practice. It is the interface between your team and your AI tooling. You will leave with a practical understanding of how to structure a codebase so that AI agents become a reliable part of your workflow rather than an unpredictable accelerant.