Build a Support Agent with Vercel AI SDK

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).