How to Vibe Check Your Code: Auditing AI Suggestions

AI generates code fast—sometimes too fast. Before you ship AI-generated code to production, you need to “vibe check” it: verify that it's correct, secure, and maintainable.

In this guide, we'll show you how to audit AI-generated code like a pro.

The Vibe Check Checklist

✅ 1. Does It Actually Work?

Test: Run the code. Click every button. Try to break it.

Common Issues:
* Functions that look correct but have off-by-one errors
* Edge cases that aren't handled
* Race conditions in async code

How to Check:
“`bash

Run the app

npm run dev

Run tests

npm test

Check for TypeScript errors

npm run type-check
“`

✅ 2. Is It Secure?

Look For:
* Hardcoded secrets or API keys
* SQL injection vulnerabilities
* XSS (Cross-Site Scripting) risks
* Missing input validation
* Insecure dependencies

Tools:
“`bash

Check for security vulnerabilities

npm audit

Scan for secrets

npx secretlint “/*”

Static security analysis

npx eslint-plugin-security
“`

✅ 3. Is It Performant?

Check:
* Are there unnecessary re-renders (React)?
* Are database queries optimized?
* Are images/assets optimized?
* Is there excessive nesting or complexity?

Tools:
“`bash

Analyze bundle size

npx webpack-bundle-analyzer

Check React performance

Use React DevTools Profiler

“`

✅ 4. Is It Maintainable?

Ask:
* Can I understand this code in 6 months?
* Are variable names descriptive?
* Is there proper error handling?
* Are there comments explaining complex logic?

Red Flags:
* Variable names like `x1`, `temp`, `data2`
* Functions longer than 50 lines
* Deeply nested conditionals (> 3 levels)
* No error handling

✅ 5. Does It Follow Best Practices?

Check:
* Consistent code style
* Proper use of async/await
* No console.logs in production code
* Proper TypeScript types (if using TS)

Tools:
“`bash

Run linter

npm run lint

Format code

npm run format
“`

✅ 6. Is It Accessible?

For UI Code, Check:
* Proper semantic HTML
* ARIA labels where needed
* Keyboard navigation works
* Color contrast meets WCAG standards

Tools:
“`bash

Accessibility linting

npx eslint-plugin-jsx-a11y

Automated accessibility testing

npx axe-core
“`

✅ 7. Is It Tested?

Verify:
* Unit tests exist for critical functions
* Integration tests cover main user flows
* Edge cases are tested

Check Coverage:
“`bash
npm run test — –coverage
“`

Aim for at least 70% coverage.

The Manual Review Process

Step 1: Read the Code Line by Line

Don't just skim. Actually read it. Ask:
* What does this line do?
* Why is it necessary?
* Could it be simpler?

Step 2: Check the Logic

Trace through the code mentally:
* What happens if the user does X?
* What if the API returns an error?
* What if the input is null/undefined?

Step 3: Look for Code Smells

Common AI-Generated Code Smells:
* Overly complex solutions to simple problems
* Unnecessary abstractions
* Repeated code (DRY violations)
* Magic numbers (use constants instead)

Step 4: Verify Dependencies

Check `package.json`:
* Are all dependencies necessary?
* Are versions pinned (not using `^` or `~`)?
* Are there known vulnerabilities?

“`bash
npm outdated
npm audit
“`

Red Flags to Watch For

🚩 Red Flag 1: “It Works on My Machine”

If the AI generated code that works locally but might fail in production:
* Environment-specific paths
* Missing environment variables
* Hardcoded localhost URLs

🚩 Red Flag 2: Over-Engineering

The AI might add unnecessary complexity:
* Using a state management library for simple state
* Creating abstractions for code used once
* Implementing features you didn't ask for

🚩 Red Flag 3: Under-Engineering

The AI might take shortcuts:
* No error handling
* No loading states
* No validation

🚩 Red Flag 4: Outdated Patterns

AI models are trained on old code. They might use:
* Deprecated APIs
* Old React patterns (class components)
* Outdated libraries

🚩 Red Flag 5: Copy-Paste Code

The AI might generate code that looks suspiciously similar to open-source projects. Check for licensing issues.

The “Explain It to Me” Test

If you can't explain what the code does to a colleague, you don't understand it well enough to ship it.

Prompt to AI:
> “Explain this code line by line in simple terms.”

If the explanation doesn't make sense, refactor.

When to Reject AI Code

Sometimes it's faster to rewrite than to fix. Reject and start over if:
* You've spent more than 30 minutes debugging
* The code is overly complex
* You don't understand the approach
* It violates your coding standards

Prompt:
> “This approach isn't working. Rewrite this using [different approach].”

Automating the Vibe Check

Create a Pre-Commit Hook

“`bash

.husky/pre-commit

npm run lint
npm run type-check
npm run test
“`

This ensures all code (AI-generated or not) passes checks before committing.

Use CI/CD

Set up GitHub Actions or similar to run:
* Linting
* Type checking
* Tests
* Security scans

On every pull request.

Conclusion

Vibe Checking is the difference between shipping fast and shipping broken code. Always review AI-generated code before it reaches production.

At BYS Marketing, we have a strict code review process. All AI-generated code is reviewed by a senior developer before deployment.

—

Need help ensuring code quality?
Contact BYS Marketing. We'll audit your codebase and implement quality controls.