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HHussain C

Your app was built with AI. Here's how I make it safe to launch

Apps built with AI tools usually work in a demo and hide the same few problems. Here's what I look for, the order I fix it in, and when a rewrite makes sense.

Most apps built with AI tools work in a demo and hide the same five or six problems. The good news is that they're usually fixable without starting again.

I see a lot of these now. Founders build something real in Lovable, Bolt, Replit or Cursor, show it to customers, and then ask the right question before launch: is this actually safe? Often it isn't, yet. Here's how I get it there.

Why do AI-built apps look finished when they aren't?

Because AI tools are judged on what you can see. You ask for a dashboard, you get a dashboard. You click around, it works, you move on.

The parts that make an app safe don't show up on screen. Does the server check that this user is allowed to see this record? What happens when someone sends a form with a script in it? Where's the API key stored? You never asked for those, so you often didn't get them. One large Veracode study found 45% of AI-generated code samples failed security tests.

What do I usually find?

The same list, in roughly the same order of how much damage it can do.

QuestionWhat it looks likeWhat can go wrong
No server-side permission checksThe screen hides other people's data, but the API still returns itAny user can read or change any other user's records
Secrets in the codeAPI keys and passwords written straight into filesAnyone with the code, or the browser, can use your accounts
Wide-open database rulesRules set to allow everything while buildingYour whole database can be read from the outside
Outdated or made-up packagesLibraries that are old, or names the AI inventedKnown security holes, or an attacker publishing a package with that name
Inputs taken on trustForms and URLs passed straight to the database or pageData stolen or pages hijacked through a crafted input
No testsNothing checks that features still work after a changeEvery fix risks breaking sign-in or payments
The usual problems in an app built fast with AI, and what each one risks.

The first row is the one that worries me most, because it's invisible from the front end. The app looks fine. Then someone opens the browser's developer tools, changes a number in a request, and sees a stranger's invoices.

What order do I fix it in?

Whatever could hurt you most, first. Tidying the code comes last.

  1. 01ReviewRead the code, run it, write down what's there
  2. 02Close the holesPermissions, secrets, database rules
  3. 03Add testsSign-in, payments and the main flows
  4. 04Clean upPackages, structure, error handling
  5. 05LaunchWith monitoring, so you see problems first
How a rescue runs, from first look to a version you can launch.

The review is written in plain English and ranked by risk. You keep it whether or not I do the fixes. Most founders want to know what they're dealing with before they decide anything, and they should.

Should you fix it or start again?

Fix it, most of the time. An AI-built app usually has a sound shape and a handful of serious holes. Starting again throws away everything that works and takes months you probably don't have.

I'll suggest a rewrite only when the review shows something structural: a data model that can't support what the business needs, or an app so tangled that every fix breaks two other things. If that's the case, I'll show you why in the review, not just say it.

Can you keep using AI tools after the rescue?

Yes, and you probably should. They're fast. The trick is putting guard rails around them, so the next feature doesn't bring back the problems you just paid to fix.

  • Tests that must pass before any change goes live, whoever wrote it.
  • Instructions in the repo that tell the AI how your app handles permissions, secrets and data.
  • A person reviewing anything that touches sign-in, payments or the database rules.

Is your app ready to launch?

  1. Could a logged-in user see another user's data by changing a number in the URL or a request?Yes →Fix this first. Add permission checks on the server for every request.No ↓
  2. Are any API keys or passwords written in the code?Yes →Move them to environment settings and change the keys today.No ↓
  3. Are your database rules still set to allow everything?Yes →Lock them down before anyone else finds them.No ↓
  4. Would you have no way to know if a change broke sign-in or payments?Yes →Add tests for those two flows before you add anything else.No ↓
  5. Has nobody but the AI read the code?Yes →Get a review before launch. It's far cheaper than a breach.
  6. Still no →You've covered the basics. A second pair of eyes before launch is still worth it.
Five checks before real users arrive. Stop at the first yes.

If you've built something with AI and want to launch it without the worry, that's what my code rescue service is for. Or send me a short brief with what you built and what it's built on.

Quick answers

Is it safe to launch an app built with AI tools?

Not without a review. AI tools are good at getting features working, but they often skip permission checks, leave secrets in the code, pull in outdated or made-up packages and write no tests. One large Veracode study found 45% of AI-generated code failed security tests. A review before launch finds these problems while they're cheap to fix.

What are the most common problems in AI-written apps?

Missing permission checks on the server, so one user can see another's data. API keys and passwords committed to the code. Packages that are outdated or don't exist. No tests, so every change risks breaking something. And database rules left wide open.

Should I rewrite an app that AI built, or fix it?

Usually fix it. Most AI-built apps have a sound shape and a handful of serious holes. A rewrite throws away what works and takes months. It only makes sense when the review shows the data model or the core structure can't hold.

How long does it take to make an AI-built app ready to launch?

The review takes about a week. The security fixes for the riskiest problems usually come next, then tests around the main flows. Bigger cleanups and upgrades go out in small slices after that, so the app keeps running the whole time.

Contact

Want this in your product?

I read every message myself and usually reply the same day. A rough idea is enough to start.

Or send a short brief

Hours

Your hours work for me.

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    Me

I keep flexible hours and move my day to overlap with yours, whether that's a morning standup in New York or a late release in Sydney.