Start with three: Stripe for revenue, Slack for communication, and PostgreSQL as your source of truth. Most AI tools wire these in shallowly. This playbook shows how to integrate them properly so your app actually works under real conditions.
Why these three come first
Every SaaS app needs three things:
a way to make money
a way to communicate
a place to store truth
Stripe handles payments
Slack handles visibility and alerts
Postgres holds your data
Everything else is secondary
Stripe integration (where most systems break)
Stripe is not just checkout
It is an event system
When something happens:
payment succeeds
subscription updates
invoice fails
Stripe sends a webhook
The correct pattern
Receive webhook
Verify signature
Store event
Process idempotently
Idempotency is critical
If the same event is received twice
your system must not double charge or duplicate actions
Stripe is not your source of truth
Common mistake:
“Stripe knows everything”
Reality:
Stripe is a billing system
not your application database
Correct pattern:
Stripe → sends events
Postgres → stores state
You sync Stripe events into your database
Your app reads from Postgres
not directly from Stripe
This prevents inconsistencies
Stripe failure modes to handle
webhook delivery delays
duplicate events
partial failures
Runbook:
store all events
retry failed processing
reconcile periodically
Never assume real-time perfection
Slack integration (more than notifications)
Slack is your visibility layer
You have two main options:
Incoming webhooks
simple
send messages
Slack bot
interactive
richer workflows
Use webhooks for:
alerts
simple notifications
Use bots for:
workflows
user interactions
Slack patterns that actually work
Internal:
payment failures
system errors
incident alerts
Customer-facing:
support channels
status updates
Do not spam
Send only actionable information
Postgres setup (what AI tools skip)
PostgreSQL is your foundation
But production setup matters
Connection pooling
Use PgBouncer
Prevents connection exhaustion
Read replicas
Separate reads from writes
Improves performance
Backups
Automated, tested regularly
Most AI-generated setups ignore all of this
Integration test patterns
Each integration needs testing
Stripe:
simulate webhook events
test retries
Slack:
verify message delivery
test failure cases
Postgres:
test queries under load
validate constraints
Do not rely on happy paths
Test failures explicitly
Audit trail across all three
When something breaks, you need visibility
Stripe:
event logs
Slack:
alerts
Postgres:
stored state
Together, they form a trace
If a payment fails:
Stripe shows event
Postgres shows state
Slack shows alert
Without this, debugging is guesswork
Common failure modes
Stripe:
duplicate webhook processing
missed events
Slack:
silent failures
noisy alerts
Postgres:
connection limits
missing indexes
Runbook for failures
Stripe issue:
check webhook logs
replay events
Slack issue:
verify webhook or bot token
check delivery logs
Postgres issue:
inspect connections
check slow queries
Have this documented before issues happen
Where structured systems help
AI tools connect these services
but often miss depth
Structured systems like Avery.dev help:
enforce webhook handling patterns
define database setup properly
ensure integrations are production-ready
This is the difference between working code
and reliable systems
