Building AI-Powered Message Routing
Watch: AI-Powered Message Routing Deep Dive (12:34)
Why Intelligent Message Routing Matters
In communities building toward a regenerative future, communication isn't just about moving information—it's about nurturing connections. Traditional notification systems blast messages indiscriminately, creating noise rather than signal. AI-powered routing transforms this by understanding context, urgency, and relationship dynamics.
Imagine a community member shares an insight about regenerative agriculture. Rather than notifying everyone, an intelligent system recognizes which members have expressed interest in this topic, who has expertise to add, and who might benefit from learning—then crafts the right message for each context.
The Technology Stack
We'll be orchestrating four powerful tools to create an intelligent communication hub:
AirtableData Layer
n8nOrchestration
ClaudeIntelligence
WebflowDelivery
Key Concepts
🎯 Intent Classification
Using Claude to understand the purpose behind each message—is it informational, requesting action, building relationship, or seeking support?
🔀 Dynamic Routing Rules
Creating flexible pathways that adapt based on member preferences, engagement history, and real-time context.
⏰ Temporal Awareness
Respecting time zones, preferred communication windows, and message urgency to deliver at the right moment.
🌊 Flow State Protection
Batching non-urgent communications and protecting deep work time for community members.
Building the Workflow
Let's create an n8n workflow that receives incoming messages, analyzes them with Claude, and routes them intelligently. Here's the core logic:
// n8n Function Node: Message Analysis Request
const message = $input.item.json;
const analysisPrompt = `
Analyze this community message and return JSON:
{
"intent": "inform|request|connect|support",
"urgency": "immediate|same-day|weekly-digest",
"topics": ["array", "of", "relevant", "topics"],
"sentiment": "positive|neutral|needs-attention",
"suggested_recipients": "criteria for who should receive"
}
Message: ${message.content}
Sender context: ${message.sender_profile}
`;
return {
prompt: analysisPrompt,
model: "claude-3-sonnet",
max_tokens: 500
};
When first implementing AI classification, use 4-5 broad intent categories. You can always refine into sub-categories as you learn from real community patterns. Premature specificity leads to brittle systems.
Interactive Exercise
Before moving forward, let's practice classifying some real community messages. Consider how you would route each of these:
Click each message to reveal the suggested routing:
"New governance proposal draft"
Click to see routing suggestion
"Feeling overwhelmed, need support"
Click to see routing suggestion
"Looking for collaborators on project"
Click to see routing suggestion
What You'll Build
By the end of this lesson, you'll have a working n8n workflow that:
- Receives messages from multiple channels (web forms, email, API)
- Analyzes content using Claude for intent and context
- Queries Airtable to find relevant recipients based on interests and preferences
- Routes to appropriate channels (email, in-app notification, digest, or escalation)
- Logs all routing decisions for continuous improvement
The goal isn't to automate human connection—it's to remove friction so authentic connection can flourish. Every automation decision should ask: "Does this create more space for genuine human interaction?"