It's 5:47am and your phone buzzes. You want to keep sleeping, but you know that sound means only one thing: six inches of fresh powder at Grand Targhee overnight, temperature sitting at 18°F. Exactly the conditions you told the app to let you know about. You roll out of bed, pour coffee directly into your throat, and drive straight to the mountain.

That alert didn't come from a weather app. It's your app. A SvelteKit app that streams AI chat responses, parses natural language into structured alert rules, evaluates conditions against live weather data in a background workflow, and serves the whole thing from Vercel.

That's the project behind this course: Ski Alerts. A real app with real deployment problems to solve.

What you'll actually build

Throughout this course, you'll build Ski Alerts from first deploy to production-ready:

Progressive deployment pipeline:

Configure and deploy a SvelteKit app to Vercel
Set up environment variables across development, preview, and production
Implement preview deployments for team collaboration

AI-powered features:

Build streaming chat interfaces with AI SDK v6
Create tools and multi-step agents
Extract structured data with Valibot schemas

Background processing:

Build durable workflows with the Workflow DevKit
Run parallel steps and schedule re-checks with sleep
Handle errors with FatalError, RetryableError, and exponential backoff

Production hardening:

Configure ISR for optimal caching
Set up observability and logging
Optimize performance for real users

Prerequisites

Familiarity with SvelteKit basics and the official tutorial
Node.js 24+ and npm (or pnpm) installed
A Vercel account (free tier works)

Svelte on Vercel

What you'll actually build

Prerequisites

Course sections

Section 1: Deployment Foundations

Section 2: AI Gateway

Section 3: Workflows

Section 4: Production