5 Things That Break After You Ship Your AI-Built App (And How to Fix Each)

Shipping an AI-built app is the easy part. Keeping it running for the first month after launch is where most vibe-coded projects quietly die - not from one catastrophic failure, but from five predictable ones that show up in roughly the same order, on roughly the same timeline, in nearly every project. Knowing which they are in advance turns a frantic week of firefighting into a calm afternoon of small fixes.

The short version: expect auth sessions to expire on returning users, expect Row Level Security to lock out real users the first time they hit a new feature, expect to hit a free-tier limit during your first traffic spike, expect verification emails to land in spam, and expect mobile layouts to break in ways your desktop preview never showed. The rest of this article is what each one looks like, why it happens, and the exact fix.

1. Auth sessions expire and users see a blank page

What it looks like

A user signs up on launch day, comes back three days later, opens the app, and sees an empty dashboard, a spinning loader that never resolves, or a console full of 401 errors. They assume the app is broken and don't come back. You discover it a week later when you check analytics and notice the bounce rate on returning sessions is 100%.

Why it happens

JWT access tokens typically expire after an hour. Refresh tokens last longer - days or weeks - but they have to be exchanged for a fresh access token, and most AI-generated auth code doesn't handle that exchange gracefully. When the access token expires, the next API call returns 401, and the frontend has no idea what to do with it.

The fix

Two lines, conceptually:

1. Set up an HTTP interceptor (or your Supabase/Butterbase client's built-in onAuthStateChange listener) that catches 401 responses, attempts a single silent token refresh, and retries the failed request.
2. If the refresh itself fails, redirect to the sign-in page - don't leave the user on a broken screen.

Most modern auth SDKs do this automatically if you let them. The bug usually appears because someone (often the AI) wrapped the SDK in a custom fetch helper that swallows the SDK's own refresh logic. Strip the wrapper, use the SDK directly, and the problem disappears.

Test it

In your auth dashboard, manually shorten the access-token lifetime to one minute. Load your app, wait two minutes, then click something. If the click works without a refresh, you're protected.

2. Row Level Security locks out real users on a new feature

What it looks like

You ship a new feature on Saturday. You test it as the user account you've been using since the start of the project. It works. Sunday morning, a real user tries the same feature and sees "could not load" or "no data." You can't reproduce it. You blame the user.

Why it happens

Every time you add a new table, your AI tool may or may not remember to add Row Level Security policies for it. Even when it does, the policies are usually written for the read case (SELECT) and forget the write case (INSERT, UPDATE, DELETE). Your developer account often has elevated permissions or seeded data that masks the problem; a new user account has nothing.

The fix

Make this a habit, not a checklist item you remember sometimes:

• Every new table gets RLS enabled the moment it's created - never later.
• Every new table gets four policies, not one: SELECT, INSERT, UPDATE, DELETE. The most common pattern is USING (auth.uid() = user_id) on all four, plus a WITH CHECK on insert/update so users can't reassign rows to other users.
• Keep a second test account around - one with no admin rights, no seeded data, no special permissions. Test every new feature with it before you call the feature shipped.

Test it

Open two browser windows. Sign in as your dev account in one, your test account in the other. Walk through the new feature in both. If the test account can't see what it just created, your INSERT or SELECT policy is wrong.

3. The free tier hits its cap mid-launch

What it looks like

You post on Product Hunt or X, traffic spikes, and within an hour your database starts returning errors, your AI feature stops responding, or your file uploads fail. The error message says something like "rate limit exceeded," "monthly active users exceeded," or "function invocation limit reached."

Why it happens

Every free tier on every platform has limits - monthly active users, database egress, function invocations, AI token usage, storage bandwidth. You don't notice them during development because your traffic is one person. On launch day, a few hundred curious visitors will hit every one of those limits in an afternoon.

The fix

Twenty-four hours before any kind of launch:

• Add a payment method to your backend, hosting platform, and any AI gateway you're using. You don't have to leave the free tier - you just have to be allowed to burst past it without being cut off.
• Set a spending cap (most platforms support one). $20–$50 is a fine safety net for a launch-day spike; you can raise it if you actually see real revenue.
• Check your analytics provider - Plausible, PostHog, Vercel Analytics - for its own page-view limits. They're the cap most people forget.

Test it

You can't easily simulate a launch spike, but you can read each platform's "what happens when I hit my limit" doc before you launch. If the answer is "your app goes offline," fix it before launch day.

4. Verification and reset emails land in spam

What it looks like

Users sign up and never confirm. You assume they lost interest. In fact, the verification email landed in Gmail's spam folder and was deleted three days later, unread. Same story for password reset. Your conversion rate looks 30% lower than it actually is.

Why it happens

Default email senders from backend platforms (the noreply@mail.supabase.io kind of address) are shared across thousands of projects with mixed reputations. Spam filters treat them with suspicion. Your beautifully designed signup flow ends in a folder no one opens.

The fix

• Connect a real sending domain through Resend, Postmark, or Loops. All three are free below ~3,000 emails per month and integrate with the major backend platforms in about ten minutes.
• Add SPF, DKIM, and DMARC DNS records for your sending domain. Your email provider gives you the exact records to copy. Without these, your emails fail authentication checks and get scored as spam regardless of content.
• Rewrite the default email templates. They read like robots wrote them, which scores poorly. Two sentences in your actual voice outperforms a generic "Welcome to YourApp! Click here to verify." every time.

Test it

Before launch, send test signup/reset emails to a Gmail, a Yahoo, an Outlook/Hotmail, and an iCloud address. All four should land in the inbox. If any land in spam, fix the DNS records or sending domain before going live.

5. Mobile layout breaks in ways your preview never showed

What it looks like

Desktop visitors love it. Mobile visitors bounce in five seconds. Looking at your actual phone, you see why: text overflows the screen, a button is half off the edge, a modal opens at 200% width, the iOS Safari address bar covers your hero CTA, or tapping anything inside a fixed-position element does nothing.

Why it happens

AI-generated layouts are tested almost exclusively at the preview's default desktop size. Mobile breakpoints get the least attention from the model, the least testing from you, and the most attention from real users - because around 60% of consumer web traffic is mobile.

The fix

• Before launch, open your app on a real phone - not just the browser's responsive-design mode. Browser emulators don't show iOS Safari's bottom bar, Android Chrome's URL bar collapse, or the way real touch targets feel.
• Walk through every primary flow on the phone: sign up, the main action, sign out. Note anything that requires zooming, sideways scrolling, or a second tap because the first one missed.
• Ask the AI to fix specific issues, not "make it responsive." A targeted prompt like "the sign-in button is being covered by the iOS Safari address bar - add bottom safe-area padding" produces a clean fix; "make it work on mobile" produces a rewrite.
• Add a viewport meta tag if it's missing: <meta name="viewport" content="width=device-width, initial-scale=1, viewport-fit=cover">. Without it, mobile browsers render at desktop width and zoom out.

Test it

Open your live site on your own phone and one borrowed phone of a different brand. iOS Safari and Android Chrome render differently enough to surface most layout bugs in two minutes of tapping.

A simple recovery plan when something does break

All five of these break quietly - you'll often hear about them from a user, not from an error log. The fastest way to catch them earlier:

• Install one error monitor (Sentry's free tier is plenty) so you see frontend exceptions in real time instead of in a support email.
• Add a one-line analytics event for "user signed in" and "user signed up." If one of those drops to zero unexpectedly, something is broken upstream of your funnel.
• Reply to every early user email personally for the first month. Most of these breaks are first reported as "hey, is your app working?" - and you find out within hours instead of weeks.

The bottom line

None of these five failures are bugs in your idea, your design, or your AI coding tool. They're the predictable seams between a working demo and a working product - the same seams every shipped app crosses in its first month, including the ones you admire. Knowing which to expect, in roughly which order, turns "my AI-built app keeps breaking" into "of course it did, here's the fix." That difference is the difference between projects that fade out after the launch tweet and projects that have real users a month later.

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