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

Building AI Workflows with AgenticFlow (6:46) This comprehensive tutorial introduces you to AgenticFlow's visual workflow builder, showing you how to create your first automation from scratch.
Web Scraping Tutorial: Step by Step (7:59) Learn how to build a practical workflow that extracts data from websites, processes it with AI, and exports the results.

📖 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 steps

  • Variables 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

AI & Language Processing (12+ nodes):

  • openai_ask_assistant - GPT model interactions

  • claude_ask - Anthropic Claude integration

  • gemini_ask - Google's Gemini AI

  • perplexity_search - AI-powered search and research

Data Operations (20+ nodes):

  • web_scraping - Extract content from websites

  • api_call - Connect to external APIs

  • google_search - Search integration

  • dataset_import - Process CSV and data files

Communication (8+ nodes):

  • email_sender - Template-based email sending

  • telegram_send_message - Instant messaging

  • slack_post_message - Team communication

File & Media Processing (15+ nodes):

  • generate_image - AI image creation

  • enhance_image_v2 - Image improvement

  • text_to_speech - Voice generation

  • speech_to_text - Audio transcription

Business Integrations (25+ nodes):

  • google_sheet_export - Spreadsheet creation

  • mcp_run_action - Model Context Protocol tools

  • replicate_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

  1. Navigate to Workflows in your sidebar

  2. Click "+ Create Workflow"

  3. Choose "Build from Scratch"

  4. Configure basic settings:

    • Name: Email to Task Extractor

    • Description: Analyzes email content and extracts actionable tasks with priorities and deadlines

    • Visibility: 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

  1. Add Input Node: This defines what data comes into your workflow

  2. Configure the input:

    • Variable Name: email_content

    • Description: The email content to analyze for tasks

    • Input Type: Text (large text area)

Node 2: AI Analysis

  1. Add Node: Search for and select openai_ask_assistant

  2. Configure the AI processing:

    • Prompt:

    • Model: gpt-4o-mini (cost-effective for this task)

    • Max Tokens: 1000

Node 3: Task Formatting

  1. Add Node: Select openai_ask_assistant again

  2. Configure formatting:

    • Prompt:

Node 4: Output

  1. Add Output Node: This returns the final result

  2. 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:

  1. Click "Run Workflow"

  2. Paste the sample email in the input field

  3. Click "Start Execution"

  4. Watch real-time progress as each node processes

  5. 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-mini for most tasks (fast and cost-effective)

  • Only use gpt-4 for complex reasoning tasks

  • Set 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:

  1. What syntax is used to reference data from previous workflow steps?

    • A) [variable_name]

    • B) {{variable_name}}

    • C) $variable_name

    • D) @variable_name

  2. 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

  3. 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

  4. 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

  5. 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

Click to see answers
  1. B) {{variable_name}} - This is the AgenticFlow variable syntax

  2. C) Start simple, test each step, then add complexity - Best practice for reliable workflows

  3. B) They can chain multiple processing steps together - Sequential processing power

  4. C) When you need sequential data processing - Workflows excel at step-by-step automation

  5. C) Errors are harder to identify and fix - Testing each step ensures reliability

🚀 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_sender node

  • Add 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_export node

  • Export 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

Video Tutorials

Node Documentation

Advanced Topics

Community Resources


🎉 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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