Structured Output With Zod

Stop Parsing Prose

Asking an LLM for JSON and parsing the string is a trap. Use the AI SDK's generateObject with a Zod schema — you get validated, typed data every time.

import { generateObject } from "ai"; import { anthropic } from "@ai-sdk/anthropic"; import { z } from "zod"; const ExtractSchema = z.object({ people: z.array( z.object({ name: z.string(), role: z.string().optional(), email: z.string().email().optional(), }) ), summary: z.string().max(240), }); export async function extract(text: string) { const { object } = await generateObject({ model: anthropic("claude-opus-4-7"), schema: ExtractSchema, prompt: `Extract people mentioned and a short summary from:\n\n${text}`, }); // object is fully typed from the schema console.log(`${object.people.length} people found`); return object; }generateObject validates the response against the schema and retries on failure. You get a typed object, not a string.

With raw OpenAI instead

import OpenAI from "openai"; import { zodResponseFormat } from "openai/helpers/zod"; const client = new OpenAI(); const r = await client.responses.parse({ model: "gpt-5", input: [{ role: "user", content: "Extract a person from: Ada Lovelace, mathematician" }], text: { format: zodResponseFormat(z.object({ name: z.string(), role: z.string() }), "person") }, }); console.log(r.output_parsed); // { name: "Ada Lovelace", role: "mathematician" }OpenAI's helpers.zod converts Zod to the JSON schema the API wants. parse() returns typed data.

Understanding "Structured Output With Zod" in practice: AI-assisted coding shifts work from syntax recall to design thinking — models handle boilerplate so you focus on architecture. Force an LLM to return JSON that matches a schema. Zod + tool-use or JSON mode makes this reliable — and knowing how to apply this gives you a concrete advantage.

• Apply Zod in your ai-coding workflow to get better results
• Apply JSON schema in your ai-coding workflow to get better results
• Apply structured output in your ai-coding workflow to get better results
• Apply parse in your ai-coding workflow to get better results

1. Use AI to generate unit tests for an existing function
2. Ask AI to refactor a messy function and explain the changes
3. Have AI suggest a code review for a recent pull request

The big idea: never parse JSON by hand from an LLM. Zod + generateObject turns the model into a typed function.