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Creating an AI Summary App with Next.js

Build an AI-powered summary application using Next.js App Router and the Vercel AI SDK. You'll implement text summarization, structured output, caching, and production-ready patterns.

Eve Porcello

Eve Porcello

Have you ever bought something online and immediately regretted it? A sweater you loved but it's the right size for a doll? A vacation rental filled with clown art? A fishing trip where the guide doesn't know how to drive the boat? You could blame yourself for not reading the reviews closely, or you could build an AI-powered summary app to help you make better decisions.

Let's build a production-ready, AI-powered summary app using Next.js App Router and the Vercel AI SDK. You'll summarize product reviews using AI, with proper error handling, caching, and deployment to Vercel.

How this course teaches

This is a hands-on, incrementally built course:

  • Start with fundamentals - Build a solid Next.js foundation before adding AI
  • Layer in complexity - Add AI features progressively from basic to advanced
  • Use production patterns - Server Components, Zod validation, smart caching
  • Handle real scenarios - Error states, fallbacks, cost optimization
  • Deploy working code - Every section produces deployable, production-ready features

What you'll build and learn in this course

This course is split into three sections:

  1. Foundations: Build a modern Next.js application with type-safe data layers and dynamic routes
  2. AI SDK integration: Add AI-powered summarization with structured output and caching
  3. Production readiness: Handle AI failures gracefully, configure fallbacks, and understand costs

Each section builds on the previous one, creating a complete production application.

Prerequisites

Before diving in, make sure you have:

Overview of the course

Here are details about each course section:

Section 1: Foundations

Build your Next.js application foundation with:

  • Modern Next.js Setup: Configure Next.js 16 with App Router, TypeScript, and Tailwind CSS
  • Type-Safe Data Layer: Create a type-safe data layer for product reviews with proper TypeScript patterns
  • Review Display Components: Build reusable components to display reviews with ratings and content
  • Dynamic Routes & Static Generation: Implement dynamic routing with static generation for optimal performance

You'll create a solid foundation that's ready for AI integration, with production-ready patterns for data handling and rendering.

Section 2: AI SDK integration

Integrate the AI SDK to add intelligent summarization features:

  • AI Gateway Setup: Configure Vercel AI Gateway with API keys and environment variables
  • First AI Summary: Generate AI-powered review summaries using generateText and display them in a Server Component
  • Prompt Engineering: Improve output quality with few-shot examples, tone guidance, and response cleanup
  • Structured Output: Use generateObject with Zod schemas to extract pros, cons, and key themes
  • Smart Caching: Implement the "use cache" directive to reduce API costs by 97%

Each lesson builds incrementally, teaching production patterns for schema design, error handling, and cost optimization.

Section 3: Production readiness

Ship your AI features with confidence:

  • When AI goes wrong: Handle failures gracefully with fallback UI, leverage AI Gateway's automatic model fallbacks, and understand what breaks and why
  • Observability and monitoring: Set up structured logging, explore AI Gateway analytics, and configure alerts so you know when things break before users tell you

You'll finish with a fully deployed application that handles failures gracefully, costs what you expect, and keeps working even when AI providers have bad days.

Help your customers never buy the wrong thing again. Let's build it!