Launching Your Product with Vibe Coding: How Far It Holds, Where It Breaks

Vibe coding lets you launch a prototype without knowing how to code: you describe what you want to an AI, it writes the application, you test it and start again. That holds up for a landing page, a test with customers, or an internal tool used by five people. It breaks as soon as your product stores customer data, takes payments, or has to run for months without you touching it.

What vibe coding does well

Vibe coding is effective for one simple question: does anyone want this product? In a few days you have a working mockup, you show it to ten prospects, and you see what interests them. For that purpose, code quality matters little, because you will probably throw the version away once the question is settled.

It also suits an internal tool used by a few trusted people, such as a tracking board or a quote generator. The scope is small, the users are known, and a mistake is quick to fix.

Where it breaks: security

This is the most sensitive point. AI-generated code can look functional while leaving doors open.

The Veracode 2025 report on the security of AI-generated code tested 80 coding tasks given to more than 100 models. In 45% of cases, the code produced contained a security flaw. That doesn't mean 45% of all generated code is dangerous, but it shows that an AI regularly picks the least secure option, without flagging it (Veracode press release).

The case most often cited involves applications built with a vibe coding platform connected to a Supabase database. According to an analysis published in March 2026 by Superblocks, a low-code platform vendor, a vulnerability (CVE-2025-48757) exposed more than 170 applications built with Lovable. The cause: access rules, the "Row Level Security", missing on 303 endpoints.

These figures come from an interested source: keep the mechanism, not the detail (Superblocks analysis).

The mechanism is simple. The application works: the screens display, the forms save. But the rule that says "only the logged-in user sees their data" was never tested. Nobody notices until a stranger tries the access.

Where it breaks: maintenance

The second breaking point comes after launch. When you ask for a change, the AI sometimes rewrites parts that were working. When a bug appears, you don't know where it lives, so you ask the AI to "fix it", and the bug changes shape.

The METR study from summer 2025 illustrates another risk. Sixteen experienced developers worked on 246 real tasks in open source repositories. With AI tools, they took 19% longer. Before the study, they expected a 24% speedup, and afterwards they still estimated they had gained about 20%.

This result concerns early 2025 tools. It still raises a useful question: if developers get their own time savings wrong, how would a non-developer know whether their code holds up? (METR study)

Where it breaks: production bugs

A production bug is a bug nobody has seen. Without automated tests, error logs and backups, you discover the outage when a customer complains. And since you don't read the code, you spend more time diagnosing than fixing.

Vibe coding doesn't add these safeguards on its own. You have to ask for them, check them, and know what they cover.

What serious recommendations say

In 2024, ANSSI, the French cybersecurity agency, and its German counterpart, the BSI, published a joint document on AI coding assistants. It does not cover vibe coding specifically, but it details the risks of these tools and gives security recommendations to managers and developers (ANSSI-BSI document).

For a personal project, this is not always feasible. The principle stays the same: a competent person should look at anything that touches data and access before you hand it to a real audience.

The checklist before putting real data online

These questions take an hour to go through, without being a developer:

• Is your data protected on the server side? Create two accounts, log in with the second and try to display the first account's data, including by changing the address or identifier in the URL.
• Are your keys and passwords absent from the visible code? An API key placed in the browser code is a public key.
• Do you have a backup you can use? A backup you have never restored doesn't really count.
• Who answers if it breaks on a Saturday? If the answer is "nobody", the product is not ready for real customers.

You can also ask the AI for a security review, with a precise prompt:

Review this project like an attacker. List every place where one user's data
could be read or modified by another user, or without logging in. For each
point, give the file, the line and the proposed fix. Explain every fix.

Be careful: an AI review does not replace a real test. It finds leads, not proof that the problem is solved. The two-account test remains the most reliable check.

When to bring in a developer

The warning signs are clear: your users enter personal data, you take payments, or you need to connect your product to other software. At that point, a developer should review the architecture, and ideally the code that controls data access. The prototype then becomes a product, and it deserves a professional's eye.

Frequently asked questions

Is vibe coding dangerous in itself? No. The risk comes from going live without checks, especially with real data. A prototype tested on fictional data carries little risk.

Does a vibe coding platform protect my data by default? Don't assume it does. Protections depend on how the database and access rules are configured. Check them yourself with the checklist above, and read the platform's documentation on what is public.

Can you trust an AI code review? For finding leads, yes. For guaranteeing security, no. A flaw is proven by a test, not by a reading.

Should you avoid vibe coding for a serious product? No. It is very useful for exploring and validating an idea. But for a product that receives real data, plan a human review and tests before launch.

For more on the real cost of an AI tool, read the real cost of AI and its three hidden costs.