By now, most developers are familiar with GitHub Copilot helping write code faster. But what if Generative AI could support you across the entire software development lifecycle (SDLC)—from the very first business idea to production deployment? In this session we will follow the journey of a feature across Software Development Lifecycle and see how GenAI can impact the way we work covering::
• Perform business analysis and extract requirements from unstructured input
• Generate user stories and acceptance criteria
• Design architectures and UML diagrams
• Write clean, maintainable code
• Generate unit and integration tests
• Scaffold IaC templates
• Document your solution and generate changelogs

For this will create a full demo covering all aspects of the SDLC by using Azure Open AI, Azure AI Search, Prompt Engineering, GitHub Copilot (including workspaces and agents), Markdown, Mermaid.

We’ll also explore what’s next: the rise of autonomous agents that go beyond assistance, capable of coordinating tasks, managing iterations, and improving code quality over time, upgrade .NET framework versions —without constant human prompts.

Whether you’re a developer, DevOps engineer, or architect, you’ll leave this session with practical examples and ready-to-use techniques to bring GenAI into every phase of your SDLC. Let’s go beyond code completion and unlock full-lifecycle productivity.