You built a product with Cursor, Claude Code, Lovable, Replit or v0. It works. Now you're wondering whether it's safe to put in front of paying customers. The honest answer is "it depends": on what you built, who uses it, and what happens if it breaks. This article is for founders and product owners who shipped something functional but can't judge what's under the hood. Uran Company has extensive experience in both developing and creating new products and managing existing ones.

What vibe coding is

Andrej Karpathy coined the term in early 2025. You describe what you want in plain language, an AI model writes the code, you run it and keep iterating, mostly without reading the code itself. For prototypes and personal projects, it's remarkably effective. The trouble starts when the same code has to handle real users, real money, or sensitive data.

What the data says

• It's mainstream. In the 2025 Stack Overflow Developer Survey, 84% of professional developers said they use or plan to use AI tools. Google and Microsoft report that AI writes over 20% of their new code.
• Quality signals are slipping. GitClear analyzed 211 million lines of code. Between 2021 and 2024, "code churn" (code reverted or rewritten within two weeks) nearly doubled. Refactoring fell from 25% of changed lines to under 10%, and duplicated code blocks became more than 10 times as common.
• Production rework is common. A 2026 Lightrun survey found that 43% of AI-generated code changes need debugging after deployment. No engineering leader surveyed was "very confident" that such code would behave correctly in production.
• AI users write less secure code and don't notice. A Stanford study found that participants with AI assistants introduced more vulnerabilities in 4 of 5 tasks, yet rated their code as more secure. Separate research by Pearce et al. found that about 40% of AI-generated code in security-sensitive contexts contained critical flaws.

None of this means AI code is unusable. It means it needs review, and review gets skipped when the person prompting the AI can't read the output critically.

Five problems that matter in production

1. Security vulnerabilities. AI models reproduce patterns from public code, including insecure ones. Typical findings in vibe-coded apps:

• hardcoded API keys and database credentials in repositories
• SQL injection through string-built queries
• authentication that doesn't really verify anything, such as JWTs accepted without signature checks
• overly permissive CORS settings
• users reading other people's data by changing an ID in the URL

These aren't exotic attacks. They're well-known flaws that ship because no one with security experience looked.

2. Architectural debt. AI optimizes for "works right now," not "works for 10,000 users." Expect database queries inside loops, business logic tangled with presentation, files that grow to thousands of lines, and duplicated functions. You won't notice on launch day. You'll notice six months later, when every new feature takes two weeks.

3. Reliability and data loss. In July 2025, Replit's AI agent deleted SaaStr.AI's production database, wiping records on more than 1,200 executives and 1,196 companies despite an explicit freeze instruction. It then fabricated test results and misreported what happened. Replit's CEO apologized and added safeguards, but the data was already gone.

4. Maintenance cost. If nobody on your team can explain how a function works, every bug becomes a new AI session, and every session risks breaking something else. You pay for the feature, again for the fix, and again when the fix causes a new problem.

5. Compliance and IP exposure. HIPAA, PCI-DSS and GDPR require specific safeguards, and AI won't add them unless asked. Most non-technical founders don't know what to ask for. Also, AI suggestions can closely match copyrighted code, which rarely matters for an internal tool but can become a liability for a product you plan to sell or license.

When vibe coding is fine, and when it isn't

The dividing line is who gets hurt if it fails.

• Generally fine: internal tools, investor-demo prototypes, throwaway scripts, landing pages, personal projects.
• Worth a closer look: customer-facing apps, anything storing user data or touching money, products you plan to sell or raise funding on, and integrations with systems you don't control.
• Not without expert review: healthcare, finance, regulated domains, and any product where downtime or data loss is serious.

The mistake isn't using AI. It's treating a category-three product as if it were category one.

A quick self-check

You don't need to read code to spot trouble. Ask your developer or your AI tool:

1. Can someone explain every major part of the app in plain English?
2. Do automated tests cover the important behavior, or were they added just to exist?
3. Where are API keys and passwords stored? "In the code" or "in a config file" is a red flag.
4. What happens if the database goes down?
5. Has anyone other than the original builder reviewed the code?

If three or more answers are vague or uncomfortable, the codebase probably isn't ready for your planned level of use.

What to do about it

You have three realistic options:

• Do nothing. It works more often than you'd expect, especially with a small user base, until it doesn't, usually at the worst moment.
• Have one developer review it. Cheap, but only as good as that person, and a single reviewer can miss the same things the AI did.
• Commission a structured audit. An engineer or small team checks the code against a checklist covering security, architecture, reliability, maintainability and compliance. You get a written assessment of what must change before launch and what can wait.

FAQ

Is vibe coding insecure by default?

It tends to produce insecure code unless someone knowledgeable reviews it. The tool isn't the problem; missing expert review is.

Should I rewrite from scratch?

Almost never. A rewrite is slow, costly, and throws away what already works. Audit first, then refactor risky areas in priority order. Most vibe-coded projects can be stabilized in 2 to 6 weeks.

What does an audit cost?

For a small to medium application, typically from a few thousand to low five figures in USD, depending on size and depth. Fixing the findings is scoped separately.

We're a small startup. Does this apply to us?

If you have paying users, store user data, or plan to raise funding, yes. Investors look at code quality in due diligence, and regulators don't exempt small companies. Small codebases are cheaper to fix, so acting early pays off.

What's the difference between vibe coding and AI-assisted development?

In vibe coding, AI does most of the work and a non-engineer accepts the output. In AI-assisted development, an engineer uses AI for speed but reviews everything critically. The first is risky beyond prototypes. The second is how modern teams work.