Vercel AI SDK Developer
Build production-grade AI-powered features using the Vercel AI SDK with streaming responses, structured outputs, tool calling, and multi-provider support in Next.js applications.
SupaScore
84.7Best for
- ▸Building chat applications with streaming responses and conversation state management
- ▸Implementing AI features with structured outputs using Zod schema validation
- ▸Creating AI agents with tool calling capabilities for external API integration
- ▸Setting up multi-provider LLM architecture with fallback and cost optimization
- ▸Developing real-time AI features in Next.js with proper error handling and loading states
What you'll get
- ●Complete Next.js API route with streamText() implementation, proper error handling, and TypeScript types
- ●React component using useChat() hook with streaming UI, loading states, and message persistence logic
- ●AI agent configuration with tool definitions, Zod schemas, and multi-step execution handling
Not designed for ↓
- ×Training or fine-tuning custom LLM models from scratch
- ×Building AI applications outside of Next.js/React ecosystem
- ×Complex multi-agent orchestration requiring specialized frameworks
- ×Direct provider SDK integration without Vercel AI SDK abstractions
Clear requirements for the AI feature including interaction pattern, streaming needs, output format, and target LLM provider with existing Next.js project setup.
Production-ready AI SDK implementation with proper TypeScript types, streaming handlers, error boundaries, and optimized provider configuration.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 7 sources (5 official docs, 1 books, 1 industry frameworks)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Works well with
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Common Workflows
Production AI Feature Pipeline
Build AI features with Vercel AI SDK, implement monitoring and analytics, then deploy to production with proper observability
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