9 Vibe Coding Risks and How to Test for Them

Vibe coding risks are defects in AI-generated applications that appear plausible and pass conventional checks but fail in real use, including incorrect outputs, unclear validation, lost state after reloads, misleading HTTP statuses, dead assets, and unnecessary authenticated calls. A small browser-based study of six publicly accessible apps built with Bolt, Lovable, and Base44 found console or network errors in five apps, silent reload-related state loss in two, a soft 404 response in one, and a financial calculator that produced an optimistic verdict from blank inputs. The analysis argues that compilers, linters, visual tests, and implementation-derived automated tests often miss such issues because they verify whether code runs as written rather than whether its behavior meets independent domain expectations. It also identifies broader risks not observable through browser testing, such as security vulnerabilities, hallucinated package dependencies, and maintainability debt, citing external research while distinguishing those findings from the six-app probe. The recommended initial verification steps are to fail builds on console and network errors, validate HTTP response statuses, test empty form submissions for meaningful feedback, and reload applications during active workflows, while supplementing functional tests with security scanning, dependency review, static analysis, and human review. The study emphasizes its limited sample size, demo-focused selection, single-browser environment, and inability to inspect source code or server-side behavior.

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