Why Vibe-Coded Apps Break in Production

The hidden cost of speed

Vibe-coded apps are useful for discovery, but they often hide the absence of architecture. The code may work locally while production concerns remain undefined.

That gap appears later as runtime instability, prompt regressions, data leaks, or infrastructure costs that do not match the business model.

The common production failure points

In practice, teams run into the same issues repeatedly: no release discipline, weak secrets handling, no rollback path, and no visibility into AI workflow failures.

• Credentials and tokens are managed manually.
• There is no staging environment that matches production.
• Model or prompt changes ship without measurable acceptance criteria.
• Failures surface through customer complaints instead of telemetry.

What to do instead

Keep the speed of AI product development, but wrap it in basic DevOps consulting discipline. A secure AI system is usually the result of predictable process, not a larger stack.