Before you begin
Make a copy or preserve a known working version before introducing production data or major changes.
Identify the person who will review uncertain, exceptional, or incorrect results.
Prepare the application
Once people use the application, you need to see more than page views.
Track the events that explain whether the workflow is working
A user begins the main task
The task completes
The AI returns a result
The result is accepted or corrected
The app asks for human review
A data connection fails
A deployment or background job fails
Credits or model costs increase unexpectedly
A user abandons the workflow
For your project, the most important success event is
[PRIMARY SUCCESS EVENT]
Add logs and alerts around the steps that can stop that event.
Do not collect data simply because it is available. Collect the minimum information needed to understand reliability, user behavior, quality, and cost while respecting your privacy obligations.
Common mistakes
Collecting logs without deciding which events need action.
Storing sensitive content in logs unnecessarily.
Monitoring usage but not quality, exceptions, or reviewer corrections.
Frequently asked questions
What is the difference between a preview and production?
A preview proves that the workflow can exist. Production adds realistic data, tests, permissions, monitoring, deployment, support, and a defined response when the system is wrong.
Do I need to complete every production step at once?
No. Identify the next material risk and address it. Typical next risks are data, evaluation, edge cases, deployment, or human review.