Core Concepts Video Series

Essential AgenticFlow concepts explained in under 5 minutes total. Perfect for understanding the fundamentals before diving deeper.

📺 Foundation Concepts (Quick Bites)

graph LR
    A[👤 User Inputs<br/>21s] --> B[⚙️ Actions<br/>1:25]
    B --> C[🧠 Knowledge<br/>1:44]
    C --> D[✨ Intelligent Output]
    
    style A fill:#e8f5e8
    style B fill:#e3f2fd  
    style C fill:#f3e5f5
    style D fill:#fff3e0

User Inputs (21s)

What are User Inputs? (21s) - Learn the bridge between users and AI: different input types for collecting text, files, images, and structured data with dynamic validation.

Perfect for: Understanding how users interact with your AI solutions

What you'll learn:

• Different types of user input fields available

• How to collect text, files, images, and structured data

• Best practices for user experience design

• Dynamic input validation and processing

Key insight: User inputs are the bridge between your users and your AI - design them thoughtfully.

Actions (1:25)

What are Actions? (1:25) - Discover where the magic happens: Core action types, chaining workflows, configuring parameters, and error handling strategies.

Perfect for: Understanding how AI actually processes and responds

What you'll learn:

• Core action types (LLM calls, API integrations, data processing)

• How actions chain together in workflows

• Configuring action parameters and outputs

• Error handling and fallback strategies

Key insight: Actions are where the magic happens - they transform inputs into intelligent outputs.

Knowledge (1:44)

What is Knowledge? (1:44) - Knowledge is power: Learn about knowledge base types, RAG fundamentals, AgenticFlow's 10-file limit optimization, and curating knowledge for better AI responses.

**Perfect for:** Understanding how to give your AI context and expertise

What you'll learn:

• Knowledge base types (documents, websites, structured data)

• RAG (Retrieval-Augmented Generation) fundamentals

• How AgenticFlow's 10-file limit per agent works

• Optimizing knowledge for better AI responses

Key insight: Knowledge is power - well-curated knowledge makes your AI exponentially more useful.

🧭 Learning Path Integration

These concepts form the foundation of every AgenticFlow solution:

User Inputs → Actions → Knowledge → Intelligent Output
    ↑                                        ↓
    └──────── User Experience Loop ──────────┘

Recommended Order:

1. Actions first (1:25) - Understand what AI can do

2. User Inputs (21s) - Learn how to collect what AI needs

3. Knowledge (1:44) - See how to make AI responses intelligent

Total learning time: Under 4 minutes for complete conceptual foundation!

🎯 How These Apply to Each Platform Feature

For AI Agents:

• User Inputs = Chat interface design

• Actions = Agent capabilities and tool access

• Knowledge = Agent's expertise and context

For Workflows:

• User Inputs = Workflow parameters and data collection

• Actions = Workflow nodes and processing steps

• Knowledge = Reference data and context for decisions

For Multi-Agent Teams:

• User Inputs = Team task assignments and goals

• Actions = Individual agent capabilities

• Knowledge = Shared team knowledge and coordination

🔗 Next Steps After Watching

Choose your path based on what interests you most:

• Agent Builder → Visual Agent Builder Guide

• Workflow Creator → Visual Workflow Builder Guide

• Team Orchestrator → Multi-Agent Workforce Guide

💡 Pro Tips from the Videos

• Start with actions - Know what your AI can do before designing inputs

• Design inputs for users, not developers - Think about the end-user experience

• Knowledge quality > quantity - Better to have focused, relevant knowledge

• Test the full loop - Always verify inputs → actions → knowledge → output flow

🎬 Related Video Content

• Understanding Multi Agent Systems (2:01)

• What is AgenticFlow AI? (2:52)

• Office Hour deep dives for advanced concepts

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📺 Part of our comprehensive 96-video learning library. These foundational concepts appear in every AgenticFlow solution.