Vercel AI SDK is a TypeScript-first toolkit for building AI features. It streamlines text generation, embeddings, and structured outputs.
We just posted a course on the freeCodeCamp.org YouTube channel that will teach you to use the Vercel AI SDK to create and ship a customer support agent that makes autonomous decisions to either answer questions based on your support docs or search the web in real time.
In this course, you’ll ship a customer support agent that:
Embeds support docs into a Supabase vector store.
Uses retrieval and web search as tools, selected on-the-fly based on the user’s question.
Classifies intents with structured outputs (via generateObject + Zod).
Answers questions with grounded, trustworthy responses—pulling from your docs when relevant or searching the web in real time when needed
The course covers these topics.
Explain RAG & embeddings and decide when to use each of them.
Set up Supabase as a vector store: create tables, embed documents, and handle chunking/text splitting for large files.
Implement retrieval with Supabase RPC so your agent can fetch the right context for any question.
Use Vercel AI SDK basics: embeddings and generateText for fast, reliable model calls.
Produce structured outputs with generateObject and Zod to validate and route intents.
Call tools with the AI SDK—define schemas, wire execution, and keep everything type-safe.
Treat retrieval and web search as tools, and compose them into a single agent decision flow.
Use the OpenAI web search tool to pull fresh, real-time information when your docs aren’t enough.
Combine it all into a support agent that chooses the best strategy (retrieve, search, or answer directly) and explains its answers.
Watch the full course on the freeCodeCamp.org YouTube channel (2-hour watch).