@ai-sdk/workflow-harness

Run an AI SDK HarnessAgent (Claude Code, Codex, Pi) as a durable workflow using the Workflow DevKit. A turn can be divided into time slices or semantic agent steps.

Time slices let a long agent turn survive a Fluid Compute function recycle (~800s). Semantic steps let a workflow persist after each agent step, typically by configuring the agent with stopWhen: isStepCount(1). At either boundary the agent is frozen non-destructively and a serializable state object is persisted as the durable step return value.

This package ships plain helpers + a serializable state machine; you own the thin 'use workflow' / 'use step' wrappers (the Workflow DevKit compiles those directives in your app).

Keep the Workflow DevKit entrypoints separate from the agent definition. The workflow module should import only workflow-safe code plus step modules. The step module should dynamically import the agent inside the 'use step' body so the agent, sandbox provider, and other Node-heavy dependencies stay out of the compiled workflow bundle.

agent.ts:

import { HarnessAgent } from '@ai-sdk/harness/agent';
import { claudeCode } from '@ai-sdk/harness-claude-code';
import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';

export const agent = new HarnessAgent({
  harness: claudeCode,
  sandbox: createVercelSandbox({ runtime: 'node24', ports: [4000] }),
});

time-slice-step.ts:

import {
  runHarnessAgentTimeSlice,
  type HarnessWorkflowState,
} from '@ai-sdk/workflow-harness';

export async function timeSliceStep(
  state: HarnessWorkflowState,
): Promise<HarnessWorkflowState> {
  'use step';

  const { agent } = await import('./agent');
  return runHarnessAgentTimeSlice({ agent, state });
}

workflow.ts:

import {
  createHarnessWorkflowState,
  finalizeHarnessWorkflow,
  type HarnessWorkflowInput,
} from '@ai-sdk/workflow-harness';
import { timeSliceStep } from './time-slice-step';

export async function timeSliceWorkflow(input: {
  prompt: HarnessWorkflowInput['prompt'];
  sessionId: string;
}) {
  'use workflow';

  let state = createHarnessWorkflowState(input);
  do {
    state = await timeSliceStep(state);
  } while (state.status === 'ready_for_next_step');
  return finalizeHarnessWorkflow(state);
}

For a semantic stepped workflow, configure the agent with stopWhen: isStepCount(1), call runHarnessAgentStep() from the step module, and continue while the status is ready_for_next_step:

stepped-agent.ts:

import { HarnessAgent } from '@ai-sdk/harness/agent';
import { claudeCode } from '@ai-sdk/harness-claude-code';
import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';
import { isStepCount } from 'ai';

export const steppedAgent = new HarnessAgent({
  harness: claudeCode,
  sandbox: createVercelSandbox({ runtime: 'node24', ports: [4000] }),
  stopWhen: isStepCount(1),
});

stepped-agent-step.ts:

import {
  runHarnessAgentStep,
  type HarnessWorkflowState,
} from '@ai-sdk/workflow-harness';

export async function agentStep(
  state: HarnessWorkflowState,
): Promise<HarnessWorkflowState> {
  'use step';

  const { steppedAgent } = await import('./stepped-agent');
  return runHarnessAgentStep({ agent: steppedAgent, state });
}

stepped-workflow.ts:

import {
  createHarnessWorkflowState,
  finalizeHarnessWorkflow,
  type HarnessWorkflowInput,
} from '@ai-sdk/workflow-harness';
import { agentStep } from './stepped-agent-step';

export async function agentWorkflow(
  input: Pick<HarnessWorkflowInput, 'messages' | 'sessionId'>,
) {
  'use workflow';

  let state = createHarnessWorkflowState(input);
  do {
    state = await agentStep(state);
  } while (state.status === 'ready_for_next_step');
  return finalizeHarnessWorkflow(state);
}

route.ts (Next.js example):

import { start } from 'workflow/api';
import { timeSliceWorkflow } from './workflow';

export async function POST(request: Request) {
  const body = (await request.json()) as {
    prompt: string;
    sessionId: string;
  };
  const run = await start(timeSliceWorkflow, [body]);

  return new Response(run.readable);
}