What's Missing in Standard OpenAI API Architecture
OpenAI API 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 OpenAI API Flow vs Optimized Skene Flow
User has access to OpenAI API features
Features available but usage not monitored
No activation prompts for unused features
Monitor OpenAI API 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:
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How Skene Fixes This
This Skene configuration tracks OpenAI API AI API calls and identifies users who haven't used AI features. It automatically triggers discovery emails with examples and use cases to drive adoption.
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 OpenAI API.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'
}
});