Today we're previewing a new way to build cloud apps with GitHub Copilot in VS Code: a guided Copilot experience that takes you from idea to a deployed Azure app through a structured, predictable workflow instead of a free-form chat session that may or may not land where you need it to.

The problem: Copilot is powerful, but unpredictable

Ask Copilot to "build me a Node.js API on Azure Functions with a Postgres database" today, and you might get a working project, or you might not. Sometimes Copilot scaffolds the app but skips infrastructure. Sometimes it generates a deployment script that fails halfway through. Sometimes it forgets what you were building three prompts later.

The underlying model is capable. The problem is the shape of the experience: an open-ended chat with no checkpoints, no guardrails, and no consistent path from "I have an idea" to "it's running in Azure."

How it works

The guided Copilot experience adds to that open-ended flow with three clear, explicit stages:

1. Project scaffolding: Describe your app in plain language. Copilot proposes an architecture and asks for anything that is missing (e.g., language, app type, Azure services) through simple forms and pickers, not more back-and-forth chat. You review and approve the plan before any code is written.

2. Local development: Your project is scaffolded then Copilot checks for the runtimes, emulators, and tools you'll need and helps you install what's missing, so the project runs locally from the very first launch. Debug configurations are wired up automatically, so you can test and iterate on your app before it ever touches Azure.

3. Deployment: Copilot shows the tools that will be used for deployment along with a summary of all resources that will be created and a cost estimate so you can be confident in what you're getting. Infrastructure files are created for your app to ensure a consistent and reproducible deployment environment for testing and staging before going to production. Deployment runs through the same reliable tooling used across Azure (az and azd), so if something goes wrong, you get a clear explanation and a concrete next step instead of a wall of CLI output.

Once your app is live, the guided experience doesn't disappear, Copilot retains context about your project's architecture, so coming back later to add a service or make a change picks up right where you left off. 🎉

What this means for how you work

• Determinism over guesswork. The same input reliably produces the same kind of outcome, so no more wondering which "mode" Copilot is going to be in.
• First try success. Projects are built to run and deploy on the first attempt, not after several rounds of manual repair.
• Structure over chat walls. Decisions that matter such as architecture choices, missing configuration, and deployment targets are surfaced through real UI, so you're not parsing paragraphs of text to figure out what Copilot needs from you.
• Stay in VS Code. The entire journey, from planning through deployment, happens without leaving your editor.

What's in the initial preview

The first version focuses on JavaScript and TypeScript projects, including web apps, Azure Functions, Container Apps, and Static Web Apps, with support for PostgreSQL, Azure Storage, Azure Key Vault, and Azure OpenAI. .NET and Python support are on the roadmap for a future release.

Nothing about your existing Copilot workflows changes, the guided experience is an additional, opinionated path alongside the free form chat you already know, for when you want a reliable, structured way to go from zero to deployed.

What's next

This is an early look at a broader shift in how we think about AI-assisted development on Azure: less "ask and hope," more structured collaboration with clear checkpoints and real UI where it counts. We're continuing to expand language support, refine the deployment experience, and incorporate feedback from developers using it in the wild.

Install the Azure Tools extension pack and open an empty folder to try the guided Copilot experience and let us know what you think. File issues or share feedback on the GitHub repo.