AI Prompts — define prompt templates as code alongside your tasks, version them on deploy, and override the text or model from the dashboard without redeploying. Prompts integrate with the Vercel AI SDK via toAISDKTelemetry() (links every generation span back to the prompt) and with chat.agent via chat.prompt.set() + chat.toStreamTextOptions().

import { prompts } from "@trigger.dev/sdk";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";

export const supportPrompt = prompts.define({
  id: "customer-support",
  model: "gpt-4o",
  config: { temperature: 0.7 },
  variables: z.object({
    customerName: z.string(),
    plan: z.string(),
    issue: z.string(),
  }),
  content: `You are a support agent for Acme.

Customer: {{customerName}} ({{plan}} plan)
Issue: {{issue}}`,
});

const resolved = await supportPrompt.resolve({
  customerName: "Alice",
  plan: "Pro",
  issue: "Can't access billing",
});

const result = await generateText({
  model: openai(resolved.model ?? "gpt-4o"),
  system: resolved.text,
  prompt: "Can't access billing",
  ...resolved.toAISDKTelemetry(),
});

What you get:

• Code-defined, deploy-versioned templates — define with prompts.define({ id, model, config, variables, content }). Every deploy creates a new version visible in the dashboard. Mustache-style placeholders ({{var}}, {{#cond}}...{{/cond}}) with Zod / ArkType / Valibot-typed variables.
• Dashboard overrides — change a prompt's text or model from the dashboard without redeploying. Overrides take priority over the deployed "current" version and are environment-scoped (dev / staging / production independent).
• Resolve API — prompt.resolve(vars, { version?, label? }) returns the compiled text, resolved model, version, and labels. Standalone prompts.resolve<typeof handle>(slug, vars) for cross-file resolution with full type inference on slug and variable shape.
• AI SDK integration — spread resolved.toAISDKTelemetry({ ...extra }) into any generateText / streamText call and every generation span links to the prompt in the dashboard alongside its input variables, model, tokens, and cost.
• chat.agent integration — chat.prompt.set(resolved) stores the resolved prompt run-scoped; chat.toStreamTextOptions({ registry }) pulls system, model (resolved via the AI SDK provider registry), temperature / maxTokens / etc., and telemetry into a single spread for streamText.
• Management SDK — prompts.list(), prompts.versions(slug), prompts.promote(slug, version), prompts.createOverride(slug, body), prompts.updateOverride(slug, body), prompts.removeOverride(slug), prompts.reactivateOverride(slug, version).
• Dashboard — prompts list with per-prompt usage sparklines; per-prompt detail with Template / Details / Versions / Generations / Metrics tabs. AI generation spans get a custom inspector showing the linked prompt's metadata, input variables, and template content alongside model, tokens, cost, and the message thread.

See /docs/ai/prompts for the full reference — template syntax, version resolution order, override workflow, and type utilities (PromptHandle, PromptIdentifier, PromptVariables).