How to Know What You Actually Built Before It Becomes a Problem

How to Know What You Actually Built Before It Becomes a Problem

Vibe coding has genuinely changed who can build software. A founder with a clear idea and no engineering background can now have a working product in days. The speed is real, the productivity gains are real, and for getting to an MVP it is often exactly the right call.

The problem is not the building. The problem is what happens next.

What AI tools are optimized for

When you describe what you want to an AI coding tool, it solves one problem: make something that works. What it is not optimized for is production. A demo has one user, controlled inputs, no real money moving through it. Production has none of those properties. The AI does not anticipate the problems you did not mention.

Three situations where this becomes expensive

The developer hire. You send a new engineer the repository. The onboarding estimate comes back at three months instead of three weeks. Not because they are slow, but because the codebase has no structure a human intentionally designed. The hire you planned to accelerate the business becomes a remediation project.

Fundraising. Technical due diligence means an investor's engineering team reviews the codebase. They are looking for risk. In a vibe-coded product that has never had a senior review, they will find it. The deal reprices, or it stalls while you fix things under time pressure.

The enterprise customer. The moment you enter a real procurement process, security questionnaires appear. If the honest answer to half of them is "we haven't set that up yet," the deal is at risk regardless of how good the product is.

What we actually find inside these codebases

We have reviewed several AI-assisted products in production. The findings are consistent enough to be predictable.

On a venue management platform built with Expo and Supabase, 5 out of 6 backend functions had no authentication, including the payment endpoints. There were 89 places in the code where errors were being silently caught and discarded, meaning the system appeared to work while quietly failing. Two critical security vulnerabilities, hardcoded API keys and an XSS exposure, had been live in production for months. Zero tests across 39,000 lines of code. Every push went directly to production with no pipeline in between.

On a SaaS marketplace built with Next.js and Stripe, the payment flow had never actually worked. Stripe webhook handlers existed as placeholder stubs. The founder was two weeks from a public launch and had no idea. The authentication flow had an open redirect vulnerability usable for phishing. Sixteen test files existed in the repository. The CI pipeline never ran any of them.

On an AI-native business platform handling CRM, finance, and payroll, the architecture was genuinely impressive. It scored well on every structural measure. But the financial logic was using float arithmetic for monetary calculations, meaning invoice totals were mathematically incorrect. There was a race condition in payment recording that would create duplicate transactions under load. The webhook signature verification, the mechanism that prevents forged payment events, was a comment placeholder.

None of these teams were careless. They built fast, which was the right call at the time. The AI produced functional software. It just did not produce production-ready software, and nobody had looked at the difference.

What the transition actually looks like

Moving to production-ready is rarely a rewrite. The underlying functionality is usually sound. What is missing is the engineering layer: authentication that covers every endpoint, credentials out of the codebase, error handling that surfaces problems instead of hiding them, a deployment pipeline with at least one checkpoint before code reaches users.

The founders who handle this well treat the review as part of the build process, not a reaction to a crisis. They know what they have before the investor asks. They know what the developer is walking into before the offer letter is signed.

Vibe coding is a powerful way to build. The question is not whether to use it. The question is whether you know what you built.