AI quickstart

Turn a model call into a durable step, trigger it, and watch its spend, tokens, and latency roll up in the console’s AI view.

This picks up where the Quickstart leaves off - it assumes you already have a project, an API key, and a connected runner. If you don’t, start there first.

1. Add an AI step

ctx.step.ai.generate makes a model call a durable step: its result is recorded once under the step id, so a retry after a crash returns the saved result instead of calling - and paying for - the model again.

runner.ts

import { workflow } from "@duraton/sdk";

export const triageTicket = workflow<{ subject: string }>({
  name: "ticket.created",
  handler: async (ctx) => {
    const { text } = await ctx.step.ai.generate("classify", {
      model: "claude-opus-4-8",
      prompt: `Classify this ticket: ${ctx.event.data.subject}`,
    });
    return { text };
  },
});

2. Set your provider key

The built-in provider is Anthropic. Your runner makes the model call, so the key stays with your runner - Duraton meters tokens but never sees your key, your prompt, or the response. Set it in the runner’s environment:

export ANTHROPIC_API_KEY="sk-ant-..."

Duraton is bring-your-own-keys. Omit apiKey on the call and the provider SDK reads its conventional env var (ANTHROPIC_API_KEY); pass apiKey per call to override it. Either way the key is used for that one call and is never recorded in the run history.

This page is the SDK path - your own runner, your own key. A workflow built without code has no runner to hold an env var, so it resolves a key you add once under Credentials instead - same guarantee, same “used for one call, never recorded” rule, different placement.

3. Trigger it and watch spend land

Send the event your workflow listens for - with the SDK client, or over the REST API:

TypeScript
REST API

import { createClient } from "@duraton/sdk";

const duraton = createClient({
  url: process.env.DURATON_URL!,
  apiKey: process.env.DURATON_API_KEY,
});

await duraton.events.send({
  name: "ticket.created",
  data: { subject: "Refund not received" },
});

curl -X POST "$DURATON_URL/events" \
  -H "Authorization: Bearer $DURATON_API_KEY" \
  -d '{"name":"ticket.created","data":{"subject":"Refund not received"}}'

As the AI step runs, open the AI view in the console. Once the first call is recorded it fills in: total spend and tokens for the window, average latency, cache hit rate, and breakdowns of cost by hour, by model, and by workflow.

Read it over MCP

An AI agent reading your project sees the same rollup: Duraton exposes the AI spend summary as the ai_spend MCP tool, so an assistant can pull window totals and the by-model / by-workflow breakdowns without the console.

Next steps

AI steps

generate, wrap, embed, and loop - the full step.ai reference.

AI agents

Durable agent loops and the classic patterns, made crash-safe.

Cost controls

Cap and throttle model spend per run and per workflow.

AI observability

Token and cost rollups, sessions, and traces for every run.

Start with code

Agent kit

AI

Durable runs

Integrations

TypeScript SDK

REST API

Protocol

1. Add an AI step

2. Set your provider key

3. Trigger it and watch spend land

Read it over MCP

Next steps

AI steps

AI agents

Cost controls

AI observability

​1. Add an AI step

​2. Set your provider key

​3. Trigger it and watch spend land

​Read it over MCP

​Next steps

AI steps

AI agents

Cost controls

AI observability

1. Add an AI step

2. Set your provider key

3. Trigger it and watch spend land

Read it over MCP

Next steps