What's Missing in Standard FastAPI + Redis + Stripe Architecture
FastAPI + Redis + Stripe manages data correctly, but lacks the infrastructure to track user activity and automatically segment users by engagement levels without custom implementation.
Standard FastAPI + Redis + Stripe Flow vs Optimized Skene Flow
User completes onboarding
User activity tracked manually (if at all)
No automated re-engagement when activity drops
Monitor Redis 'events' table for user activity patterns via standard features
Detect when user becomes dormant (stopped using feature X)
Trigger re-engagement email sequence with personalized content
Track re-engagement success and adjust campaigns
Visual comparison of the flows:
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How Skene Fixes This
This Skene Prompt sets up behavioral tracking for FastAPI + Redis + Stripe by watching Redis tables and detecting inactivity patterns. When users haven't engaged for 7 days, it triggers personalized re-engagement emails with context about their previous activity.
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 Retention Loop pattern for FastAPI + Redis + Stripe.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'
}
});