6 Things Vibe-Coded Apps Get Wrong Before They Hit Production

The Gap Between Demo and Production

Vibe coding — using AI assistants to generate large chunks of working code quickly — has made it faster than ever to get a demo running. Founders can show a working prototype in days. Investors see something real. Momentum builds.

Then you try to scale it, and everything falls apart.

Here are the six most common things that break when a vibe-coded app goes to production.

1. No Error Handling

AI-generated code is optimistic. It assumes the happy path. There's no null check, no timeout handling, no retry logic. In a demo, that's fine — you control the conditions. In production, users do things you didn't anticipate and external services fail when you least expect it.

Every vibe-coded codebase we've inherited has had massive gaps in error handling. Fixing it isn't glamorous, but it's non-negotiable.

2. Security Vulnerabilities Nobody Thought About

When you're moving fast, security is an afterthought. API keys hardcoded in environment files that end up in git history. User inputs that flow directly into database queries. Admin routes with no authentication.

These aren't hypothetical risks. They're things we find in nearly every vibe-coded app that was built for speed without security review.

3. Data Model That Doesn't Scale

The data model you design for a demo is almost never right for production. Tables that should be normalised are flat. Relationships that will grow unbounded have no pagination. Indexes that matter for performance don't exist.

Refactoring a data model with live user data is painful. It's much harder than refactoring it before anyone depends on it.

4. No Observability

You can't fix what you can't see. Vibe-coded apps typically have no logging, no error tracking, no performance monitoring. When something breaks in production, you're debugging blind.

Setting up basic observability — application errors, slow queries, user-facing failures — should happen before launch, not after.

5. AI Calls With No Rate Limiting or Fallbacks

If your app makes LLM API calls, those calls will fail. Rate limits get hit. Timeouts happen. The model returns something unexpected. Without rate limiting, queuing, and fallback handling, your AI feature will fail loudly and visibly when it matters most.

6. No Tests for the Parts That Matter Most

Vibe-coded apps rarely have tests. That's fine for a demo. It's a serious problem for a production system where you need to ship new features without breaking existing ones.

You don't need 100% coverage. You need tests for the paths that, if broken, would cause real user harm or data loss. Those paths need to be protected before you have users on them.

The Fix

None of these are reasons to avoid vibe coding. It's a genuinely useful tool for moving fast in early stages. The key is knowing when to switch modes — from "get it working" to "make it production-ready" — and doing the unsexy hardening work that the vibe coding skipped.