Workflows

AI Workflows allow you to chain multiple Agents together to complete complex operations that previously required entire teams. Define a workflow once, and run it on-demand or on a schedule.

What Are Workflows?

Workflows orchestrate multiple AI agents (Content, Code, and Computer Use) to execute complex, multi-step operations autonomously. Each step in a workflow passes context to the next—content feeds into code, code deploys, and Computer Use tests and records demos.

How Workflows Work

Define Your Workflow: Choose a template or build custom. Chain Content, Code, and Computer Use agents in any sequence. Set triggers—manual, scheduled, or event-driven.
Execute Automatically: Agents work sequentially or in parallel. Each step passes context to the next, maintaining continuity throughout the workflow.
Monitor in Real-Time: Watch progress live with step-by-step updates. See token usage, costs, and duration. Pause for approval gates when human review is needed.
Review & Iterate: Get complete execution summaries. View all created content, code changes, and recordings. Clone successful workflows for future projects.
Rerun Anytime: Run workflows on-demand or schedule them to run automatically. Your automation runs 24/7 without intervention.

Workflow Use Cases

Full-Stack Product Launch

Time: 20 minutes vs 2-3 weeks

Content Agent creates your product catalog, Code Agent builds the storefront, Computer Use Agent tests and records a demo video. Complete e-commerce site, deployed.

Workflow steps: Content Generation → Code Development → Deploy & Test

Automated Content Optimization

Schedule: Runs every Monday at 2 AM

Automatically analyze 500+ articles for outdated content, validate links, capture fresh screenshots, and update flagged articles. Always-fresh content, zero manual work.

Workflow steps: Analyze Content → Validate Links → Auto-Update

Multi-Market Launch

Time: 90 minutes vs 16 weeks

Launch in 12+ markets simultaneously. Localized content, market-specific websites, compliance validation, and demo videos—all running in parallel.

Workflow steps: Localize Content → Deploy Sites → Validate Compliance

Auto-Documentation

Trigger: On every deploy

Code deploys to production, agents analyze changes, test new features, capture demo videos, write documentation, and create sales materials. Docs ship with features.

Workflow steps: Analyze Code → Test Features → Generate Docs

Creating a Workflow

Open your project and click AI Studio in the project sidebar, then choose Workflows
Click "Create Workflow"
Add steps by selecting agent types (Content, Code, or Computer Use)
Configure each step with specific instructions
Set execution order (sequential or parallel)
(Optional) Add approval gates for human review
(Optional) Set a schedule or trigger for automatic execution

Workflow Features

Sequential or Parallel Execution: Run steps one after another or simultaneously
Context Passing: Each step receives output from previous steps
Approval Gates: Pause workflow for human review when needed
Scheduling: Run workflows on a schedule (hourly, daily, weekly, monthly)
Event Triggers: Automatically trigger workflows on specific events
Real-Time Monitoring: Watch progress with live updates
Execution History: Review past runs with complete logs and outputs
Templates: Start with pre-built workflow templates for common use cases

Event-Triggered Workflows

Workflows can be configured to run automatically when content events occur, enabling powerful automation scenarios.

Available Events:

Object Created: Run workflow when new content is added
Object Edited: Run workflow when content is modified
Object Deleted: Run workflow when content is removed
Object Published: Run workflow when content goes live
Object Unpublished: Run workflow when content is taken offline

Event Context Data:

When an event triggers your workflow, the following data is automatically included in the prompt context for all workflow steps:

Event Type: The action that triggered the workflow
Object Type: The content type that was affected
Object ID: The unique identifier of the object
Object Data: Title, slug, status, locale, and all metadata fields

Using Event Data for Conditional Logic:

Each step in your workflow can reference the event data to make decisions:

Step 1 (Content Agent):
"If the triggered object's status is 'draft', generate SEO metadata.
 If the object is 'published', create social media posts instead."

Step 2 (Code Agent):
"If the object type is 'products' and the price field changed,
 update the pricing display component."

Example Event-Triggered Workflows:

Auto-SEO on Publish:

Trigger: Object Published (blog-posts)
Step 1: Generate meta description and keywords from content
Step 2: Create Open Graph image using AI image generation
Step 3: Update object with SEO metadata

Content Localization Pipeline:

Trigger: Object Created (articles)
Step 1: If locale is 'en-US', translate to Spanish, French, German
Step 2: Create localized versions as new objects
Step 3: Send notification with translation summary

Product Update Automation:

Trigger: Object Edited (products)
Step 1: If price changed, update all related promotional content
Step 2: Regenerate product comparison charts
Step 3: Notify sales team via email

Workflow Examples

Research-to-Publication Pipeline:

Step 1 (Content Agent): Research topic from specified sources
Step 2 (Content Agent): Write article draft with citations
Step 3 (Code Agent): Create landing page for article
Step 4 (Computer Use Agent): Record demo video and screenshots
Step 5 (Content Agent): Publish with all media assets

Code Review and Documentation:

Step 1 (Code Agent): Implement feature from requirements
Step 2 (Code Agent): Write unit tests
Step 3 (Computer Use Agent): Test in browser and record demo
Step 4 (Content Agent): Generate documentation from code changes
Step 5 (Code Agent): Open PR with docs and demo video

Best Practices

Start Simple: Begin with 2-3 step workflows and add complexity as needed
Use Approval Gates: Add human review steps for critical operations
Test First: Run workflows manually before scheduling
Monitor Costs: Watch token usage across workflow steps
Clone Successful Workflows: Reuse working workflows as templates for new projects

Execution Retention

Agent and workflow executions are automatically cleaned up after a retention period to manage storage and keep your dashboard performant.

Retention Policy

Retention Period: 90 days
Affected Executions: Completed, failed, and cancelled executions
Protected Executions: Running and active executions are never automatically deleted

What Gets Deleted

When an execution exceeds the retention period, the following data is removed:

Execution logs and message history
Step-by-step results and outputs
Token usage records for that execution
Associated metadata (commits, file changes for code agents)

What's Preserved

Agent and Workflow configurations are never deleted by retention policies
Running executions remain until they complete
Content created by agents (CMS objects, media) persists independently
Code changes committed to your repository remain in Git history
Pull requests created by code agents remain in GitHub

Best Practices

Export important execution logs before the 90-day retention period if you need long-term records
Use the execution detail view to review results while they're available
Agent configurations store your prompts and settings permanently—only execution history expires