Common Bugs in JetBrains AI-Generated Code

Java's type system doesn't prevent null at compile time, so AI-generated code can produce valid Java that throws NullPointerException at runtime. Spring Boot's complex configuration means AI-generated beans may depend on conditions that aren't met

JetBrains AI generates Java and Kotlin code that often compiles but has runtime issues — null pointer exceptions in code that should use Optional, unchecked exceptions from I/O that are swallowed without logging, and Spring dependency injection that looks correct but fails at startup due to missing beans. Kotlin nullable types are sometimes handled inconsistently with the rest of the codebase

Start by running your app through its complete user flow — sign up, use every feature, try edge cases like empty inputs and invalid data. Most JetBrains AI bugs surface when you go off the happy path. Use your browser's developer tools to watch for console errors, failed network requests, and unhandled promise rejections. TypeScript's strict mode will catch many issues at compile time if it's not already enabled.

For async errors, wrap every server-side operation in try/catch blocks and return meaningful error messages. For state bugs, consider whether the state belongs in the URL, in a server component, or in client state — JetBrains AI often defaults to client state when server state would be more appropriate. For data fetching issues, implement proper loading and error states for every data-dependent component.

The best way to prevent JetBrains AI bugs from reaching production: enable TypeScript strict mode, add ESLint rules for common mistakes (no-floating-promises, exhaustive-deps), and write tests for critical user flows. Even basic smoke tests catch the majority of issues.