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:

Validates content and counts words
Enhances with metadata
Summarizes the content
Analyzes with AI for quality scoring and feedback

This creates a comprehensive, AI-powered content processing system! Next, you'll learn about parallel execution.