The Visibility Problem: Errors You Never See

When your app is running in production, you are not watching the browser console. Your users are. Every Uncaught TypeError, failed API call, and broken script silently degrades their experience - and unless you have real user monitoring in place, you will only hear about these failures when a user emails you or simply leaves.

According to a Google study on page experience, 53% of mobile users abandon sites that take longer than 3 seconds to load - and runtime JavaScript errors that block rendering contribute directly to that abandonment. W3C's Web Performance Working Group data shows that JavaScript errors are among the leading causes of perceived performance degradation on production websites.

For apps built with Bolt, Lovable, Cursor, or v0, the gap between the development preview and production reality is particularly wide. AI tools build against a controlled scaffold. They cannot anticipate the environment variables that are missing in your Vercel deployment, the Supabase tables that are structured slightly differently from what the code expects, or the API responses that contain null values instead of the assumed objects.

GitHub's analysis of AI-generated codebases found that error handling is present in fewer than 40% of async operations generated by popular vibe coding tools. That means the majority of API calls, database queries, and user interactions have no fallback if something goes wrong.

The Most Common Console Errors in AI-Built Apps

What AI-Generated Error Handling Actually Looks Like

Here is a representative data-fetching component from a Bolt or Lovable-generated Next.js app. It works in the preview environment but fails silently in production when the API returns an unexpected shape:

// ❌ BAD - No null checks, no error handling, assumes API shape
export default function UserDashboard() {
  const [data, setData] = useState(null);

  useEffect(() => {
    fetch('/api/user/profile')
      .then(res => res.json())
      .then(data => setData(data));
      // No .catch() - silent failure if fetch throws
  }, []);

  return (
    

      {/* ❌ Crashes if data is null or data.posts is undefined */}
      
{data.user.name}
      {data.posts.map(post => (
        
{post.title}
      ))}
    
  );
}

In a development environment with a seeded database, this works perfectly. In production, if the API returns { error: "unauthorized" } instead of the expected user object, data.user throws Cannot read properties of undefined and the entire component crashes - or worse, React throws an unhandled error that brings down the whole page.

How to Fix Runtime Errors Correctly

The same component written defensively handles all the failure modes that AI tools ignore:

// ✅ GOOD - Null checks, loading state, error boundary compatible
export default function UserDashboard() {
  const [data, setData] = useState(null);
  const [loading, setLoading] = useState(true);
  const [error, setError] = useState(null);

  useEffect(() => {
    fetch('/api/user/profile')
      .then(res => {
        if (!res.ok) throw new Error(`API error: ${res.status}`);
        return res.json();
      })
      .then(data => {
        setData(data);
        setLoading(false);
      })
      .catch(err => {
        console.error('Failed to load profile:', err);
        setError(err.message);
        setLoading(false);
      });
  }, []);

  if (loading) return 
Loading...
;
  if (error) return 
Failed to load profile. Please refresh.
;
  if (!data?.user) return 
Profile not found.
;

  return (
    

      
{data.user.name}
      {(data.posts ?? []).map(post => (
        
{post.title}
      ))}
    
  );
}

The key improvements are: checking res.ok before parsing JSON, catching errors and storing them in state rather than letting them propagate silently, using optional chaining (data?.user) before accessing nested properties, and providing a fallback array (data.posts ?? []) before calling .map().

How to Detect Console Errors on Your Live Site

There are two categories of detection: automated scanning and real user monitoring.

Automated scanning uses a headless browser to load your live URL, interact with key pages, and capture every console error thrown during the session. This catches the errors that are deterministic - ones that always fire on page load, broken script references, missing environment variables that cause immediate failures, and CORS errors on API calls.

Tools like VibeDoctor (vibedoctor.io) automatically scan your live website for JavaScript console errors and runtime exceptions, flagging specific URLs and error messages. Free to sign up.

Real user monitoring (RUM) captures errors that only occur in specific user flows or with specific data. Tools like Sentry, LogRocket, and Datadog RUM instrument your client-side JavaScript and send every unhandled exception - with stack trace, user context, and the sequence of actions that led to the error - to a dashboard. For any vibe-coded app that has real users, adding Sentry takes under 10 minutes and pays dividends immediately:

// ✅ Add Sentry to a Next.js app - catches all unhandled errors
// Install: npm install @sentry/nextjs
// Then run: npx @sentry/wizard@latest -i nextjs

// sentry.client.config.ts
import * as Sentry from "@sentry/nextjs";

Sentry.init({
  dsn: process.env.NEXT_PUBLIC_SENTRY_DSN,
  tracesSampleRate: 0.1,
  environment: process.env.NODE_ENV,
});

Broken Links and 404 Errors

Beyond JavaScript runtime errors, the WEB-002 check covers a related but distinct failure mode: broken internal links and missing resources that generate 404 responses. In AI-built apps, this commonly occurs when:

• Cursor or Bolt generates navigation links to routes that do not yet exist
• Images are referenced with hardcoded paths that differ between development and the Vercel deployment
• API routes are renamed during refactoring but the client-side fetch calls are not updated
• Dynamic import paths contain typos that only surface when a specific user interaction occurs

Broken links directly damage SEO. Google's crawlers penalize pages with high rates of 404 responses, and a Next.js app with broken <Link> components prevents Google from discovering and indexing your content. W3C's Link Checker and browser-based crawlers like Screaming Frog can map all internal links on a deployed site and flag 404s systematically.

How to Find and Fix These Issues Before Users Do

Build a three-layer approach: static analysis catches obvious patterns before deployment, automated scanning tests the live site after each deployment, and real user monitoring captures the long tail of edge-case failures.

For static analysis, add ESLint with the eslint-plugin-react-hooks and @typescript-eslint rules enabled. TypeScript strict mode catches a large percentage of the null-reference errors that create runtime crashes. Enable it in tsconfig.json with "strict": true - AI tools often disable this flag to avoid type errors in generated code.

For deployment validation, add a post-deploy smoke test to your CI pipeline. Even a simple Playwright or Puppeteer script that loads your homepage, navigates to two or three key pages, and asserts there are no console errors will catch the most common regressions before users see them.

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