22-25 April 2026 
Video unavailable
SQLBits 2026
Build AI-Ready Applications with SQL Server and GitHub Copilot in VS Code
Learn how the MSSQL extension and GitHub Copilot in VS Code help you build AI-ready apps with SQL Server by guiding schema changes, adding vector support, and enabling semantic search and RAG scenarios in a simple, end to end workflow.
AI-ready applications do not have to be complex, you can build them directly on top of SQL Server using tools you already know. In this session, you will see how the MSSQL extension integrated with GitHub Copilot in Visual Studio Code streamlines database design, helps generate schema changes, and guides you through adding SQL Server native vector data types to enable semantic search and Retrieval Augmented Generation (RAG) scenarios.
We will start with a traditional SQL-backed application and enhance it with vector columns, indexes, and embeddings, all created and managed inside VS Code. You will learn how Copilot assists with writing SQL, validating schema updates, and producing the queries needed for similarity search using SQL Server vector functions. The session then shows how these updates flow into the application layer so your backend can return meaningful, AI supported results with minimal changes.
The session also highlights how the MSSQL extension supports this workflow with a modern user interface, integrated query and editing tools, and local SQL container support for fast development and testing. Together these capabilities create a practical path for evolving existing applications or starting new projects that combine SQL development, vector search, and Copilot assisted productivity inside a single unified environment in VS Code.
We will start with a traditional SQL-backed application and enhance it with vector columns, indexes, and embeddings, all created and managed inside VS Code. You will learn how Copilot assists with writing SQL, validating schema updates, and producing the queries needed for similarity search using SQL Server vector functions. The session then shows how these updates flow into the application layer so your backend can return meaningful, AI supported results with minimal changes.
The session also highlights how the MSSQL extension supports this workflow with a modern user interface, integrated query and editing tools, and local SQL container support for fast development and testing. Together these capabilities create a practical path for evolving existing applications or starting new projects that combine SQL development, vector search, and Copilot assisted productivity inside a single unified environment in VS Code.