Why Your AI-Built App Is Slow (And How to Fix It)

Quick answer: AI-built apps are typically 500ms to 1500ms slower than necessary due to redundant auth calls, heavy JS bundles, and render-blocking spinners. SimplyScan's analysis shows many apps suffer from these speed issues. Fixing them via code splitting and CSS animations can reduce bundle sizes and significantly boost user conversions.

By Daniel A · Kraftwire Software

AI-built apps are typically slow because they suffer from redundant network requests, unoptimized JavaScript bundles, and render-blocking loading gates. You can fix this by removing duplicate auth calls, implementing route-based code splitting, and replacing heavy animation libraries with native CSS.

What Does a Slow App Actually Cost You?

Speed is no longer a luxury; it is a fundamental requirement for both user retention and AI visibility (AEO). When you build with tools like Lovable or Bolt, the "vibe" might be fast, but the actual performance often lags.

• Conversion Loss · Every additional second of load time costs conversions. According to research on Core Web Vitals, the Economic Times saw a 43% reduction in bounce rate simply by optimizing these metrics.
• Mobile Abandonment · Mobile visitors abandon slow pages in large numbers, often within the first three seconds of a blank screen.
• Engagement Drop · Page views per visit fall as pages get slower, directly impacting your ad revenue or funnel depth.
• The 1-Second Rule · Sites loading in 1 second convert significantly better than sites loading in 5 seconds.

Speed is not a technical detail. It's a revenue lever.

Why Is Your AI-Built App Slow?

AI coding tools like Lovable, Cursor, Bolt.new, and Replit can build a full-stack app in minutes. However, there is a recurring pattern in almost every AI-generated codebase: the app works, but it is unoptimized.

The AI's primary goal is to provide a working solution to your prompt. It often achieves this by using "safe" but heavy patterns · like importing entire libraries for a single function or wrapping the whole app in a global loading state to avoid race conditions. In fact, developers have noted that as AI models update, the complexity of the generated code can lead to slower generation and execution times if not properly managed.

SimplyScan includes Speed Optimization as a core category in our site health scanner. Here are the 10 most common speed bottlenecks we find in "vibe-coded" applications.

1. Duplicate Network Requests on Load

The problem: AI-generated authentication providers commonly call both onAuthStateChange and getSession() on mount. In Supabase, for example, the onAuthStateChange listener fires with the INITIAL_SESSION event synchronously. This means the manual getSession() call is entirely redundant, doubling your initial auth-related requests and delaying the app's interactive state.

The fix: Remove the manual getSession() call. Let the listener handle the initial state.

Impact: Reduces network overhead by 2 to 4 requests per page load.

2. Full-Page Spinners Blocking First Paint

The problem: AI tools love "loading gates." If your app uses a CMS or a database for configuration, the AI often wraps the entire App component in a if (loading) return <Spinner /> block. This means every page · including static pages like Terms or Login · shows a blank screen until the database responds.

The fix: Use a library like React Query with staleTime: Infinity for configuration data. Render the UI immediately with hardcoded defaults or "skeleton" states. Swap in the real data seamlessly when it arrives.

Impact: Approximately 500ms faster First Contentful Paint (FCP).

3. Missing Route-Based Code Splitting

The problem: In many AI-built apps, all page components are eagerly imported at the top of the router file. When a visitor hits your landing page, their browser downloads the JavaScript for the Dashboard, the Admin Panel, the Settings page, and every other route in your app.

The fix: Use React.lazy to ensure users only download the code for the page they are actually viewing.

4. Heavy Dependencies for Simple Tasks

The problem: AI tools frequently import full libraries for tasks that require only a few lines of code. The most common offender is framer-motion (~45KB gzipped). We often see it imported in 10+ components just to handle a "fade-in" effect that CSS can do natively.

The fix: Replace simple animations with native CSS keyframes. Reserve heavy libraries like framer-motion for complex, layout-shifting animations or stagger sequences.

Impact: Saves ~45KB of JavaScript parsing and execution time.

5. React Query Re-Fetching Static Data

The problem: React Query (or TanStack Query) defaults to a staleTime of 0. This means the library considers data "stale" immediately and re-fetches it every time the window is refocused or a component remounts. For a blog post or a pricing table that changes once a month, this is a massive waste of resources.

The fix: Define an appropriate staleTime based on the data's volatility.

Impact: Eliminates redundant API calls and makes navigation feel "instant."

6. The "Dark Mode" Theme Flash

The problem: If your theme logic (dark vs. light mode) is handled entirely inside React, the browser will render the default theme (usually white) for a split second before React hydrates and switches to dark mode. This "flash" is a hallmark of unoptimized AI apps.

The fix: Place a tiny, synchronous blocking script in your index.html head. This script should check localStorage and apply the correct CSS class to the <html> element before the first pixel is painted.

Impact: Professional, flash-free loading experience.

7. Unoptimized Hero Images (LCP)

The problem: The Largest Contentful Paint (LCP) is usually your hero image. AI tools often treat these images like any other asset, sometimes even applying loading="lazy" to them. Lazy-loading your hero image is a performance anti-pattern because it tells the browser not to prioritize the most important visual element.

The fix: Use the fetchPriority="high" attribute on your hero image and add a preload link in your HTML head.

Impact: Improves LCP by ~200ms to 400ms.

8. Over-Fetching Data (The "Select *" Problem)

The problem: To keep things simple, AI prompts often result in queries that fetch every column and every row. For example, a "Recent Posts" widget might fetch the full body text of 50 articles just to display the titles of the last 3.

The fix: Use specific select statements in your database queries. If you only need the title and slug, only fetch the title and slug.

Impact: Reduced payload size and faster database response times.

9. Eager Loading of Third-Party Scripts

The problem: Analytics, chat widgets, and feedback tools often load immediately on the main thread. These scripts are heavy and block the browser from rendering your actual app.

The fix: Delay the loading of non-critical scripts until after the window load event, or use a "proxy" (like a simple button) that only loads the full chat widget when the user clicks it.

Impact: Significantly better "Time to Interactive" (TTI) scores.

10. Render-Blocking Fonts

The problem: Using standard Google Fonts <link> tags can block the page from rendering until the font CSS is downloaded. If the connection is slow, the user sees nothing.

The fix: Use font-display: swap in your CSS. This tells the browser to show a system font immediately and "swap" it for your custom font once it's ready.

Impact: Faster First Contentful Paint and better perceived speed.

The Cumulative Effect of Optimization

Individually, these fixes might save 100ms here or 200ms there. But in the world of vibe coding, these issues usually appear all at once.

• Fix duplicate auth requests · Saves 2 to 4 network calls on every refresh.
• Remove loading gates · Results in ~500ms faster First Contentful Paint.
• Remove heavy dependencies · Reduces JavaScript bundle size by ~45KB or more.
• Add query caching · Enables zero-latency navigation for static data.
• Preload hero image · Results in ~200ms faster Largest Contentful Paint.

When combined, these optimizations typically result in an app that is 500ms to 1500ms faster and significantly more responsive.

Performance as a Security and Reliability Signal

Interestingly, there is often a correlation between poor performance and poor security. An app that makes redundant, unoptimized network requests is often an app where the developer hasn't audited the architecture security risks.

As we look toward the future of AI development in 2026, experts suggest that unoptimized AI-built apps will be the most prone to breaking. Issues like race conditions, where two redundant requests finish in the wrong order, can lead to corrupted state or broken auth. A slow app is often the first symptom of these deeper architectural flaws.

How to Audit Your App's Speed

You don't need to be a performance engineer to fix these issues. SimplyScan provides a comprehensive site health scanner that grades your app across 8 dimensions, including speed, in about 30 seconds.

• Run a Free Scan · Enter your URL at simplyscan.io.
• Check the Speed Category · We detect performance bottlenecks like missing code splitting and unoptimized bundles.
• Review Security Signals · We also look for exposed API keys, missing/weak Supabase RLS, and broken auth.
• Implement Recommendations · Use the actionable advice to trim your bundle and secure your data.

Whether you are building with Bolt, Windsurf, or v0, speed is your competitive advantage. A fast app builds trust; a slow app builds doubt.

FAQ

Why is my Lovable or Bolt.new app so slow?

Most AI-generated apps prioritize functionality over performance. Common patterns include duplicate auth requests (calling onAuthStateChange and getSession simultaneously), full-page loading spinners that block the UI, and a lack of code splitting. This results in a heavy app that feels sluggish despite having simple features.

How much faster can I make my AI-built app?

By implementing basic optimizations like code splitting, query caching, and removing redundant auth calls, you can typically reduce perceived load times by 500ms to 1500ms. These fixes often reduce the initial JavaScript bundle size significantly, which is critical because fast load times correlate with much higher conversion rates.

Do I need to remove Framer Motion to improve speed?

Not necessarily, but you should use it sparingly. AI tools often import the entire 45KB library for simple fade-ins. Replacing these with native CSS animations reduces the JavaScript execution load. Keep Framer Motion only for complex interactions like layout transitions or drag-and-drop elements to keep your bundle lean.

What is the best staleTime for React Query in an AI app?

It depends on the data. For data that rarely changes (like user profiles or site settings), a staleTime of 5 to 10 minutes is ideal. For static CMS content, you can even use Infinity. This prevents the flicker caused by React Query re-fetching data every time a user switches tabs.

How do I stop the white flash on my dark mode app?

The flash occurs because React hasn't loaded yet to determine the theme. To fix it, add a small, blocking script in your index.html head that reads the theme from localStorage and applies a .dark class to the html tag immediately. This ensures the correct theme is rendered from the very first frame.

Can SimplyScan detect these performance issues automatically?

Yes. SimplyScan's free scan evaluates 8 dimensions, including speed and security. It detects issues like missing security headers, unoptimized bundles, and exposed API keys in about 30 seconds. The Pro report provides detailed code examples and AI prompts to help you fix every identified bottleneck.

Related Reading

• The Vibe-Coding Security Checklist · Ensure your fast app is also a secure app.
• AEO for Vibe-Coded Apps · Why speed is the #1 factor for ranking in AI search engines.
• Uptime Monitoring Guide · How to keep your app fast and available 24/7.
• SimplyScan vs. Platform Security · Why built-in platform checks aren't enough for production apps.