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# Creating AI-Enhanced Workflow
Now you'll create a new workflow that includes agent analysis alongside your existing content processing steps.
## Creating the Enhanced Workflow
Add this new workflow to your file:
```typescript
export const aiContentWorkflow = createWorkflow({
id: "ai-content-workflow",
description: "AI-enhanced content processing with analysis",
inputSchema: z.object({
content: z.string(),
type: z.enum(["article", "blog", "social"]).default("article"),
}),
outputSchema: z.object({
content: z.string(),
type: z.string(),
wordCount: z.number(),
metadata: z.object({
readingTime: z.number(),
difficulty: z.enum(["easy", "medium", "hard"]),
processedAt: z.string(),
}),
summary: z.string(),
aiAnalysis: z.object({
score: z.number(),
feedback: z.string(),
}),
}),
})
.then(validateContentStep)
.then(enhanceContentStep)
.then(generateSummaryStep)
.then(aiAnalysisStep)
.commit();
```
## Registering the New Workflow
Update your Mastra configuration to include both workflows and ensure the contentAgent has been added.
```typescript
// In src/mastra/index.ts
import {
contentWorkflow,
aiContentWorkflow,
} from "./workflows/content-workflow";
import { contentAgent } from "./agents/content-agent";
export const mastra = new Mastra({
workflows: {
contentWorkflow,
aiContentWorkflow, // Add the AI-enhanced version
},
agents: { contentAgent },
// ... rest of configuration
});
```
## Testing the Agent-Enhanced Workflow
You can now access this new Workflow inside the Mastra playground. Select this new `ai-content-workflow` workflow from the Workflows tab and run a test to validate it works as expected.
## The Complete AI Pipeline
Your AI-enhanced workflow now:
1. **Validates** content and counts words
2. **Enhances** with metadata
3. **Summarizes** the content
4. **Analyzes** with AI for quality scoring and feedback
This creates a comprehensive, AI-powered content processing system! Next, you'll learn about parallel execution.