Day 4: Workflow Fundamentals
🎯 Learning Objectives
⏱️ Time Commitment
Video: 14 minutes
Reading: 13 minutes
Hands-on: 18 minutes
Total: ~45 minutes
📚 Lesson Content
📹 Video Tutorial: Building Your First Workflow
📖 Workflow Fundamentals Deep Dive
Workflows are the automation engine of AgenticFlow. While agents provide conversational intelligence, workflows handle the behind-the-scenes processing that makes everything work.
Understanding Workflow Types
AgenticFlow offers two distinct workflow systems:
1. Traditional Workflows (What we'll build today)
Sequential, step-by-step automation
Form-based node configuration
Perfect for data processing and system integration
80+ pre-built nodes for every task type
2. Workforce Workflows (Advanced)
Visual, node-based multi-agent orchestration
React Flow interface with drag-and-drop
AI agents working together as teams
Complex decision trees and parallel processing
Today we focus on Traditional Workflows - the foundation that powers most automation tasks.
Core Workflow Concepts
Nodes: Individual steps that perform specific actions
Input Nodes: Receive data into the workflow
Processing Nodes: Transform, analyze, or manipulate data
Action Nodes: Send emails, create files, call APIs
Output Nodes: Return results from the workflow
Variables: The data pipeline that connects nodes
Use
{{variable_name}}syntax to pass data between stepsVariables can contain text, numbers, objects, or files
Each node output becomes available as a variable
Execution Flow: How workflows run
Sequential processing (one step after another)
Real-time progress monitoring
Error handling and retry logic
Parallel execution for bulk operations
Popular Node Categories
AI & Language Processing (12+ nodes):
openai_ask_assistant- GPT model interactionsclaude_ask- Anthropic Claude integrationgemini_ask- Google's Gemini AIperplexity_search- AI-powered search and research
Data Operations (20+ nodes):
web_scraping- Extract content from websitesapi_call- Connect to external APIsgoogle_search- Search integrationdataset_import- Process CSV and data files
Communication (8+ nodes):
email_sender- Template-based email sendingtelegram_send_message- Instant messagingslack_post_message- Team communication
File & Media Processing (15+ nodes):
generate_image- AI image creationenhance_image_v2- Image improvementtext_to_speech- Voice generationspeech_to_text- Audio transcription
Business Integrations (25+ nodes):
google_sheet_export- Spreadsheet creationmcp_run_action- Model Context Protocol toolsreplicate_run_model- External AI models
💡 Key Insights
When to Use Workflows:
You need to process data in a specific sequence
You want to connect multiple systems or services
You have repetitive tasks that follow the same pattern
You need to handle bulk operations (CSV files, multiple records)
Workflow Design Principles:
Start Simple: Build with 2-3 nodes, then add complexity
Test Each Step: Verify output at each node before moving forward
Use Clear Variable Names:
{{user_input}}is better than{{step1_output}}Handle Errors: Plan for what happens when external services fail
🛠️ Hands-On Exercise
Build an Email-to-Task Workflow (18 minutes)
Let's create a practical workflow that takes an email, extracts action items using AI, and organizes them into a structured task list.
Phase 1: Workflow Setup (5 minutes)
Step 1: Create the Workflow
Navigate to Workflows in your sidebar
Click "+ Create Workflow"
Choose "Build from Scratch"
Configure basic settings:
Name:
Email to Task ExtractorDescription:
Analyzes email content and extracts actionable tasks with priorities and deadlinesVisibility: Keep as Private for now
Step 2: Understanding the Interface You'll see the form-based workflow builder with:
Steps section: Where you add and configure nodes
Variables panel: Shows available data from previous steps
Test section: For running and debugging your workflow
Phase 2: Building the Workflow (10 minutes)
Node 1: Input Setup
Add Input Node: This defines what data comes into your workflow
Configure the input:
Variable Name:
email_contentDescription:
The email content to analyze for tasksInput Type: Text (large text area)
Node 2: AI Analysis
Add Node: Search for and select
openai_ask_assistantConfigure the AI processing:
Prompt:
Model:
gpt-4o-mini(cost-effective for this task)Max Tokens:
1000
Node 3: Task Formatting
Add Node: Select
openai_ask_assistantagainConfigure formatting:
Prompt:
Node 4: Output
Add Output Node: This returns the final result
Configure output:
Variable:
{{openai_ask_assistant_1.result}}(the formatted task list)Output Name:
organized_tasks
Phase 3: Testing & Refinement (3 minutes)
Test with Sample Email Content:
Execution Process:
Click "Run Workflow"
Paste the sample email in the input field
Click "Start Execution"
Watch real-time progress as each node processes
Review the final output for quality
Expected Output: A well-organized task list with priorities, deadlines, and assignments clearly identified.
💡 Workflow Optimization Tips
Performance Optimization:
Use
gpt-4o-minifor most tasks (fast and cost-effective)Only use
gpt-4for complex reasoning tasksSet appropriate token limits to control costs
Error Handling:
Test with various email formats and lengths
Consider what happens with unclear or incomplete information
Plan fallback responses for edge cases
Variable Management:
Use descriptive variable names:
{{extracted_tasks}}not{{step2_output}}Reference the specific output you need:
{{node_name.result}}
✅ Knowledge Check
Test your workflow understanding:
What syntax is used to reference data from previous workflow steps?
A) [variable_name]
B) {{variable_name}}
C) $variable_name
D) @variable_name
Which is the best approach for building workflows?
A) Add all nodes at once, then configure
B) Start complex, then simplify
C) Start simple, test each step, then add complexity
D) Copy existing workflows without modification
What's the main advantage of Traditional Workflows over single AI conversations?
A) They cost less to run
B) They can chain multiple processing steps together
C) They work faster
D) They don't require configuration
When should you use a workflow instead of an agent?
A) When you need conversational interaction
B) When you need 24/7 availability
C) When you need sequential data processing
D) When you need persistent memory
What happens if you don't test each workflow step individually?
A) The workflow runs faster
B) It costs less in credits
C) Errors are harder to identify and fix
D) Variables work better
🚀 Apply Your Knowledge
Workflow Enhancement Challenges
Now that you have a working Email-to-Task workflow, try these enhancements:
Challenge 1: Add Email Integration
Research the
email_sendernodeAdd a final step that emails the task list to the team
Configure with your email settings (if comfortable sharing)
Challenge 2: Export to Spreadsheet
Add a
google_sheet_exportnodeExport tasks to a Google Sheet for tracking
Include columns for Priority, Due Date, Assigned Person, Status
Challenge 3: Smart Prioritization
Enhance the AI prompt to better identify urgent tasks
Add logic to automatically flag overdue items
Include suggested completion dates based on task complexity
Real-World Workflow Ideas
Based on what you've learned, consider these workflow applications:
Business Process Automation:
Invoice processing: PDF → data extraction → approval workflow
Customer feedback: form responses → sentiment analysis → categorization
Content creation: brief → research → writing → review → publishing
Data Processing Workflows:
CSV analysis: upload → cleaning → analysis → reporting
Web monitoring: scraping → change detection → notifications
Research automation: query → multiple source search → synthesis
Communication Workflows:
Meeting follow-up: notes → action items → email distribution
Customer support: inquiry → classification → routing → response
Social media: content creation → scheduling → performance tracking
Choose one idea and outline the nodes you would use to build it.
📌 Summary
Excellent work! You've mastered the fundamentals of workflow automation:
Technical Skills Gained:
Built a complete workflow using the visual drag-and-drop interface
Configured multiple node types for different processing tasks
Used variables to pass data between workflow steps
Tested and debugged workflow execution in real-time
Conceptual Understanding:
When to use workflows vs agents vs workforce systems
How sequential processing can solve complex automation problems
The importance of testing and iteration in workflow development
Cost and performance considerations for AI-powered automation
Practical Experience:
Created a real, working automation that solves a business problem
Learned how AI nodes can be chained together for sophisticated processing
Understanding of how workflows integrate with broader business processes
What's Next: Tomorrow we'll explore how to choose your learning path and put everything together in a capstone project that demonstrates your new AgenticFlow skills.
🔗 Additional Resources
Workflow Building Deep Dive
Workflows Hub - Complete workflow building reference
Node Reference - Comprehensive node documentation
Workflow Templates - Pre-built automation examples
Video Tutorials
File System Feature (12:38) - Advanced file handling workflows
MCP Workflow Integration (12:11) - Using MCP tools in workflows
Office Hours #11 (41:48) - Watch Claude build workflows live
Node Documentation
AI & Language Nodes - GPT, Claude, Gemini integration
Data Processing Nodes - CSV, JSON, API handling
Communication Nodes - Email, Slack, SMS integration
All Node Types - Complete 80+ node reference
Advanced Topics
Bulk Processing - Handle large datasets efficiently
Error Handling - Build robust, reliable workflows
Performance Optimization - Speed and cost optimization
API Integration - Connect external services
Community Resources
Discord #workflows Channel - Workflow-specific help and examples
Template Gallery - Community workflow examples
Use Cases - Real-world workflow applications
🎉 Fantastic progress! You've built your first automation workflow and understand how to chain AI processing steps together. Your Email-to-Task workflow demonstrates the power of sequential processing for business automation.
Tomorrow: We'll bring everything together as you choose your specialized learning path and complete a capstone project that showcases your new AgenticFlow skills.
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