A vague backlog item is poor input for AI and people. Now that AI assistants work directly with your backlog, requirement quality matters even more.

When backlog work remains manual, or teams use AI in disconnected chats, they miss the value of connected, AI-assisted workflows. We show how reusable Agent Skills for GitHub Copilot and the Azure DevOps MCP Server support governed backlog management: AI proposes and refines; people provide context, review, steer, and approve what reaches the backlog.

In a live demo, we turn a specification into a hierarchical backlog with refined descriptions, test-ready acceptance criteria, all without manual editing. You'll learn how agent skills differ from prompt templates, how MCP connects Copilot to Azure DevOps context, and how approval gates keep people in control.