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Start Node

The Start Node is the entry point for every workflow in the AI Flow platform. It marks where flow execution begins and is the foundational node that all other nodes connect to, either directly or indirectly. Every flow must have exactly one Start node, making it the most fundamental component of workflow design.

Start Node

Basic Usage​

The Start Node is automatically added when you create a new flow. It serves as the initial trigger point from which all workflow execution originates.

Key Characteristics​

Single Instance Requirement​

Every flow must have exactly ONE Start node:

  • Only one Start node per flow is allowed
  • Cannot be deleted (it's a required node)
  • Cannot have duplicate Start nodes
  • All execution paths must originate from this node

Execution Entry Point​

The Start node:

  • Initiates workflow execution
  • Triggers when a user launches the flow
  • Begins the sequence of connected nodes
  • Sets the initial state for the workflow

Connection Point​

  • Has one output connection point (red circle on the right)
  • No input connections (as it's the starting point)
  • Must connect to at least one subsequent node for a functional flow
  • Can connect to any compatible node type

Visual Elements​

The Start node consists of:

  1. Node Body: Dark gray rectangular shape with rounded corners
  2. Label: "Start" text in white, centered on the node
  3. Output Port: Red circle on the right side for connecting to the next node
  4. Non-configurable: No settings or configuration panel - it works automatically

How It Works​

Flow Execution Sequence​

User launches flow → Start Node activates → Follows connection to next node → Continues through workflow

Execution Timing​

  • Manual Launch: When user clicks to run the flow
  • LTI Integration: When accessed from LMS (Canvas, Moodle, etc.)
  • API Trigger: When called via API endpoint
  • Assignment Launch: When student opens an assignment
  • Scheduled: If configured with scheduling (advanced setups)

Example Workflows​

Simple Linear Flow​

Scenario: Basic workflow starting with introduction and content.

[Start] → [Display Text: Welcome Message] 
       → [Display HTML: Content] 
       → [Progress Checkpoint]

Flow Structure:

  1. Start node triggers execution
  2. Welcome message displays first
  3. Main content shows next
  4. Progress is saved at checkpoint

Branching Flow​

Scenario: Assessment-based routing to different learning paths.

[Start] → [Display Text: Assessment Instructions]
       → [Form: Quiz Questions]
       → [Branching Node: Score Evaluation]
           ├─ Path A: Beginner Content
           ├─ Path B: Intermediate Content
           └─ Path C: Advanced Content

Flow Structure:

  1. Start initiates the flow
  2. Instructions display
  3. Assessment is administered
  4. Branching routes to appropriate difficulty level

Complex Interactive Flow​

Scenario: Multi-component learning experience with various node types.

[Start] → [Display Text: Introduction]
       → [Video Input: Upload Assignment]
       → [Describe Video: AI Analysis]
       → [AI General Prompt: Feedback Generation]
       → [Display Text: Show Feedback]
       → [Progress Checkpoint: Mark Complete]

Flow Structure:

  1. Start node begins execution
  2. Introduction explains task
  3. Student uploads video
  4. AI analyzes video content
  5. AI generates personalized feedback
  6. Feedback displayed to student
  7. Completion tracked

Parallel Processing Flow​

Scenario: Multiple simultaneous operations from start.

[Start] → [Parallel Processing Node]
           ├─ Branch 1: [AI Analysis Path]
           ├─ Branch 2: [Data Processing Path]
           └─ Branch 3: [Content Generation Path]
       → [Execution Merger: Combine Results]
       → [Display Results]

Flow Structure:

  1. Start initiates workflow
  2. Parallel processing splits execution
  3. Multiple operations run simultaneously
  4. Results merge back together
  5. Combined output displays

Integration with Other Nodes​

Display Nodes (Common):

  • Display Text: Show welcome message, instructions
  • Display HTML: Present formatted content, embedded media
  • Widgets: Interactive UI elements

Chatbot Nodes (Interactive):

  • Chatbot Flow Processor: Start conversational experience
  • Multi-Turn Conversation: Begin dialogue-based learning

Input Nodes (Data Collection):

  • Form: Collect user information upfront
  • File Uploader: Request document submission
  • Video Input: Accept video uploads

Processing Nodes (Advanced):

  • Parallel Processing: Split into multiple paths
  • Data Dump: Load saved state for returning users
  • Knowledge Bank: Access stored information

Flow Control (Routing):

  • Branching Node: Route based on conditions
  • Scenario Branch: Complex conditional routing
  • Flow Jump: Redirect to different flow
  • Progress Checkpoint: Often used as end point in flows starting from Start node
  • Display Text: Commonly the first node after Start for instructions
  • Branching Node: Routes flow based on conditions after initial Start
  • Parallel Processing: Splits execution into multiple paths from Start
  • Flow Call: Invokes sub-flows (which don't use Start node)
  • Flow Jump: Redirects to another flow's Start node
  • Chatbot Flow Processor: Can be immediate entry point after Start
  • Form: Collect data early in flow after Start

Summary​

The Start Node is the essential foundation of every AI Flow workflow:

✓ Required: Every flow must have exactly one
✓ Automatic: Created by default, no configuration needed
✓ Entry Point: Where all execution begins
✓ Simple: Just connect and go
✓ Reliable: System-managed, always works

Build your flows with Start as the foundation, connecting thoughtfully to create effective learning experiences and automated workflows.