What's Missing in Standard Pinecone Architecture
Pinecone provides AI capabilities, but usage tracking shows most users never try them. Without activation loops, 70% of users miss the core AI value proposition.
Standard Pinecone Flow vs Optimized Skene Flow
User has access to Pinecone features
Features available but usage not monitored
No activation prompts for unused features
Monitor Pinecone usage patterns and feature adoption
Identify users who haven't used key features
Trigger feature discovery emails with examples and use cases
Track feature adoption and send advanced usage guides
Visual comparison of the flows:
Loading diagram...
How Skene Fixes This
We created a Skene Prompt that installs AI activation for Pinecone. It monitors AI API usage and automatically sends feature discovery emails to users who haven't tried AI features after 7 days.
Implementation Comparison
Using Skene Infrastructure
Install via Prompt
@task: Initialize Skene.
@action: Analyze my local code, validating subscription via `npx skene login`, and generate `skene.config.ts` to implement the AI Activation pattern for Pinecone.Copy Skene Prompt for Cursor
Generated skene.config.ts
// skene.config.ts - The Automated Way
import { defineLoop } from '@skene/sdk';
export default defineLoop({
type: 'retention',
opinion: 'Detect dormant users and trigger personalized re-engagement campaigns',
steps: [
{
trigger: {
type: 'schedule',
cron: '0 9 * * *' // Daily at 9 AM
},
condition: {
type: 'query',
query: `SELECT * FROM users WHERE last_activity_at < NOW() - INTERVAL '7 days' AND re_engagement_sent = false`,
timeout: '10m'
},
action: {
type: 'email',
provider: 'resend',
template: 're_engagement',
personalization: {
name: '{{user.name}}',
lastActivity: '{{user.last_activity_at}}'
}
}
}
],
recovery: {
retries: 3,
backoff: 'exponential'
}
});