15-Minute Quickstart
Welcome to the future of AI automation! You're about to discover AgenticFlow's most powerful feature - the Workforce - a visual multi-agent system that lets multiple AI agents work together seamlessly.
Think of it like having a team of AI specialists, each with their own expertise, collaborating on complex tasks while you watch everything unfold in real-time through a beautiful visual interface.
🎯 What You'll Build in 15 Minutes
By the end of this guide, you'll have created your first AI workforce that can:
Research a topic using multiple specialized agents
Analyze findings from different perspectives
Generate a comprehensive report automatically
Delegate tasks between agents intelligently
Monitor the entire process visually
Perfect for: Content creation, research projects, business analysis, complex automation, and any task requiring multiple AI perspectives.
🚀 Step 1: Access the Workforce Builder
Log into AgenticFlow and navigate to your dashboard
Click "Create New" → "Workforce" (you'll see the star ⭐ indicating it's our flagship feature)
Select "Start from Scratch" for this tutorial (templates available for advanced users)
📸 Screenshot needed: Dashboard with Workforce creation button highlighted
What you'll see: A beautiful React Flow visual canvas where you'll drag, drop, and connect your AI agents.
🧠 Step 2: Understanding the Workforce Interface
The Workforce builder has several key areas:
📊 Visual Canvas (Center)
Drag & drop interface for building your AI team
Real-time connections between agents
Live execution monitoring with progress indicators
🔧 Smart Node Palette (Left)
Agent Nodes: Your AI team members
Tool Nodes: Actions agents can take
Trigger Nodes: How workflows start
State Nodes: Data flow and conditions
⚙️ Configuration Panel (Right)
Node settings when you select any component
Agent configuration with our 11-tab system
Connection properties and conditional logic
📸 Screenshot needed: Full Workforce interface with labeled areas
🤖 Step 3: Create Your First AI Agent
Let's start by creating a research specialist:
Drag an "Agent Node" from the palette to the canvas
Double-click to open the agent configuration
Configure the Basic Tab:
Name: "Research Specialist"
Role: "Expert researcher and fact-finder"
Description: "Specializes in gathering and verifying information"
Configure the AI Model (Model Tab):
Provider: OpenAI (or your preferred model)
Model: GPT-4 (recommended for research tasks)
Temperature: 0.2 (lower for more focused research)
Set the System Prompt (System Prompt Tab):
You are a professional research specialist. When given a topic: 1. Break down the research into key areas 2. Find reliable sources and current information 3. Summarize findings clearly and concisely 4. Always cite your sources 5. Flag any uncertainties or conflicting informationAdd Research Tools (MCP Tab):
Enable "Google Search" for web research
Enable "Website Content Extractor" for detailed analysis
Enable "PDF Analysis" if researching documents
📸 Screenshot needed: Agent configuration dialog showing the 11 tabs
📊 Step 4: Add an Analysis Agent
Now let's create an analyst to work with the research findings:
Drag another Agent Node to the canvas
Configure it as "Data Analyst":
Role: "Analytical thinker and pattern recognizer"
System Prompt: Focus on finding insights, trends, and actionable conclusions
Temperature: 0.3 (slightly higher for creative analysis)
Connect the agents:
Click and drag from the Research Specialist's output to the Data Analyst's input
You'll see a connecting line appear
📸 Screenshot needed: Two connected agent nodes on the canvas
⚡ Step 5: Add Intelligence and Conditions
This is where Workforce shines - intelligent routing and decision-making:
Add a Conditional Node between your agents:
Drag a "Conditional Logic" node from the palette
Position it between your two agents
Reconnect the flow through the conditional node
Configure Smart Routing:
Condition: "If research findings > 500 words, route to analyst. Otherwise, request more research."
True Path: Continue to Data Analyst
False Path: Loop back to Research Specialist with feedback
📸 Screenshot needed: Conditional logic node configuration
📝 Step 6: Add Output Generation
Finally, let's create an agent to compile the final report:
Add a "Report Generator" agent at the end of your flow
Configure it for content creation:
System Prompt: Focus on creating well-structured, professional reports
Enable tools: Document generation, formatting tools
Add a "File Output" node:
Connect from Report Generator
Configure to save as PDF or Markdown
Set naming: Use timestamp and topic variables
🚀 Step 7: Test Your Workforce
Time to see your AI team in action!
Click "Run Workforce" at the top of the interface
Enter a test topic: "Latest trends in renewable energy technology"
Watch the magic happen:
Research Specialist gathers information
Conditional logic evaluates the findings
Data Analyst processes the research
Report Generator creates the final document
What You'll See:
Real-time progress on each node
Live data flow between agents
Decision points as conditions are evaluated
Final output generated and saved
📸 Screenshot needed: Workforce in execution mode with active nodes highlighted
🎉 Congratulations! You've Built Your First Workforce
Your AI team just collaborated to:
✅ Research a complex topic automatically
✅ Analyze findings intelligently
✅ Generate a professional report
✅ Make decisions based on data quality
✅ Handle exceptions gracefully
🔥 What Makes This Powerful
🧠 Multi-Agent Intelligence
Unlike simple workflows, your Workforce agents can:
Think independently with their own specialized prompts
Communicate and share context dynamically
Make decisions based on real-time analysis
Adapt to different inputs and scenarios
👁️ Visual Orchestration
See exactly how your AI team works together
Debug problems by watching the flow
Optimize performance by analyzing bottlenecks
Scale complexity without losing clarity
🔧 Enterprise-Grade Features
Version control for your workforce configurations
Team collaboration on complex automations
Performance monitoring and analytics
Error handling and recovery
🎯 Next Steps: Level Up Your Workforce
📚 Immediate Next Actions:
Try the templates: Explore pre-built Workforce examples
Add more agents: Create 3-5 agent teams for complex tasks
Experiment with loops: Create feedback cycles for quality control
Add triggers: Set up automatic workflow triggers
🔗 Recommended Reading:
Multi-Agent Orchestration - Advanced collaboration patterns
Visual Builder Guide - Master the interface
Node Types Reference - Complete node documentation
Workforce Templates - Ready-to-use examples
💡 Popular Use Cases to Try:
Content Marketing: Research → Write → Edit → Publish pipeline
Business Analysis: Data gathering → Analysis → Recommendations → Reports
Customer Support: Ticket analysis → Research → Response → Follow-up
Product Development: Market research → Feature analysis → Documentation
🆘 Having Issues?
Common Questions:
Q: My agent isn't producing good results A: Check your system prompt - be specific about the agent's role and expected output format.
Q: Agents aren't passing data properly A: Verify your connections and check that output formats match input expectations.
Q: Workflow is running slowly A: Consider parallel execution - agents that don't depend on each other can run simultaneously.
Q: I want to reuse this Workforce A: Save it as a template! Click "Save as Template" and share with your team.
🆘 Need Help?
Troubleshooting Guide - Common solutions
Discord Community - Get help from other users
Support Email - Direct technical support
🚀 Ready to Build More?
You've just experienced the power of visual multi-agent orchestration. Your AI workforce can handle increasingly complex tasks as you add more agents, smarter routing, and sophisticated logic.
What will you build next?
👉 Explore Workforce Templates →
👉 Master Multi-Agent Patterns →
🌟 The Workforce is AgenticFlow's flagship feature - you're now part of the future of AI automation. Welcome to the team!
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