# 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.