# Run.start()
[EN] Source: https://mastra.ai/reference/workflows/run-methods/start

The `.start()` method starts a workflow run with input data, allowing you to execute the workflow from the beginning.

## Usage example

```typescript showLineNumbers copy
const run = await workflow.createRunAsync();

const result = await run.start({
  inputData: {
    value: "initial data",
  },
});
```

## Parameters

<PropertiesTable
  content={[
    {
      name: "inputData",
      type: "z.infer<TInput>",
      description: "Input data that matches the workflow's input schema",
      isOptional: true,
    },
    {
      name: "runtimeContext",
      type: "RuntimeContext",
      description: "Runtime context data to use during workflow execution",
      isOptional: true,
    },
    {
      name: "writableStream",
      type: "WritableStream<ChunkType>",
      description: "Optional writable stream for streaming workflow output",
      isOptional: true,
    },
    {
      name: "tracingContext",
      type: "TracingContext",
      isOptional: true,
      description:
        "AI tracing context for creating child spans and adding metadata. Automatically injected when using Mastra's tracing system.",
      properties: [
        {
          parameters: [
            {
              name: "currentSpan",
              type: "AISpan",
              isOptional: true,
              description:
                "Current AI span for creating child spans and adding metadata. Use this to create custom child spans or update span attributes during execution.",
            },
          ],
        },
      ],
    },
    {
      name: "tracingOptions",
      type: "TracingOptions",
      isOptional: true,
      description: "Options for AI tracing configuration.",
      properties: [
        {
          parameters: [
            {
              name: "metadata",
              type: "Record<string, any>",
              isOptional: true,
              description:
                "Metadata to add to the root trace span. Useful for adding custom attributes like user IDs, session IDs, or feature flags.",
            },
          ],
        },
      ],
    },
    {
      name: "outputOptions",
      type: "OutputOptions",
      isOptional: true,
      description: "Options for AI tracing configuration.",
      properties: [
        {
          parameters: [
            {
              name: "includeState",
              type: "boolean",
              isOptional: true,
              description:
                "Whether to include the workflow run state in the result.",
            },
          ],
        },
      ],
    },
  ]}
/>

## Returns

<PropertiesTable
  content={[
    {
      name: "result",
      type: "Promise<WorkflowResult<TState, TOutput, TSteps>>",
      description:
        "A promise that resolves to the workflow execution result containing step outputs and status",
    },
    {
      name: "traceId",
      type: "string",
      isOptional: true,
      description:
        "The trace ID associated with this execution when AI tracing is enabled. Use this to correlate logs and debug execution flow.",
    },
  ]}
/>

## Extended usage example

```typescript showLineNumbers copy
import { RuntimeContext } from "@mastra/core/runtime-context";

const run = await workflow.createRunAsync();

const runtimeContext = new RuntimeContext();
runtimeContext.set("variable", false);

const result = await run.start({
  inputData: {
    value: "initial data",
  },
  runtimeContext,
});
```

## Related

- [Workflows overview](/docs/workflows/overview#running-workflows)
- [Workflow.createRunAsync()](../workflow-methods/create-run)


---
title: "Reference: Run.watch() | Workflows"
description: Documentation for the `Run.watch()` method in workflows, which allows you to monitor the execution of a workflow run.
---