# AI App Builder Apps: What to Fix Before Real Users Arrive

> Built an app with Lovable, Bolt or Base44? Four checks to run before real users and payments arrive: data rules, exposed keys, Stripe payments and backups.

- Author: Filipe Eduardo, Senior Software Engineer (https://filipeeduardo.dev/)
- Published: October 8, 2026
- Topic: AI-built apps · Tags: ai app builder
- Canonical URL: https://filipeeduardo.dev/blog/ai-app-builder-production

![Illustration of an AI app builder project on a launch checklist with database, key, payment and backup checks](https://cms.filipeeduardo.dev/wp-content/uploads/2026/10/ai-app-builder-production.webp)

## Key takeaways

- Treat AI-generated code as a first draft. Fix the existing code before you consider a rewrite.
- Four checks cover most of the risk before real users: data access rules, exposed keys, payment confirmation and backups.
- The platform secures its infrastructure. You are responsible for who can read which data and for your users’ data.
- Apps built with Lovable have shown a pattern of weak Supabase row-level security (RLS) rules, so check this first.
- Scanners and the builder’s own AI tend to miss business logic like payment webhooks and duplicate orders.
- Staying on the builder is sometimes the right call. Moving to GitHub and your own hosting is possible when it is not.

An **AI app builder** such as Lovable, Bolt or Base44 can give you a working app in an afternoon. What it does not give you is [proof that the app is safe for real users and real payments](https://filipeeduardo.dev/blog/ai-app-builders-safe-for-real-users). Most of the risk sits in four places: who can read which data, which keys are exposed, how payments are confirmed, and whether you can restore a backup.

I am a Brazilian senior full-stack engineer with seven years of experience (since 2019) building web and mobile products end to end. This guide is what I would check first on an app someone else generated. You do not need a full audit to find most problems, but you do need to look before launch, because fixing things gets more expensive once real users and payments exist.

## What does an AI app builder actually build for you?

A typical builder generates a frontend (often React), connects it to a backend service (very often Supabase for database and login), wires in payments (often Stripe), and hosts the result. You describe features in plain language and it writes the code.

That is [genuinely useful for prototypes, internal tools and early validation](https://filipeeduardo.dev/blog/ai-built-prototype-production-ready). The output usually looks finished: pages load, forms save, login works. The gap is in what you cannot see by clicking around:

-   Rules about which user may read or change which rows.
-   Where secrets live and whether they ship to the browser.
-   What happens when a payment event arrives twice, late or never.
-   What happens when the database is damaged or deleted.

[The builder optimizes for an app that works in the demo.](https://filipeeduardo.dev/blog/vibe-coding-security) Production asks what happens when someone behaves badly, when traffic grows, or when something fails halfway. That is why I call the generated code a first draft: a good one to start from, but not reviewed by anyone who was thinking about failure.

## What does the builder secure, and what is still your responsibility?

Security here is a shared responsibility. The builder secures its own infrastructure and accounts. You, as the app owner, are responsible for the behavior of your app: who can read which data, what ends up in the browser, how payments are confirmed, and whether backups exist.

A public example shows why this split matters. In July 2025, [Wiz researchers found that Base44](https://filipeeduardo.dev/blog/base44-security), the AI app builder owned by Wix, allowed an attacker to register on apps meant to be private using only the app’s ID. It was fixed within a day. That was a platform-side issue, and the platform fixed it. But it also shows that you cannot assume every setting is safe by default, and that private apps are only as private as the layers around them.

On the other side, a weak data rule in your own Supabase project is not the platform’s bug. It is your configuration, and no one will fix it unless you check it. I am not saying these tools are bad. I am saying the responsibility line is clear, and most founders do not know which side of it they are standing on.

## Which four checks cover most of the risk before launch?

You do not need a month-long audit. In my experience, [four focused checks catch most of what matters before real users arrive](https://filipeeduardo.dev/blog/app-launch-checklist):

1.  **Data access rules:** can one user read or edit another user’s data?
2.  **Exposed keys:** is any secret visible in the browser or in the repository?
3.  **Payment confirmation:** does the app grant access only after the payment provider confirms it, and handle repeats?
4.  **Backups:** can you restore your data, and have you tried?

In my experience each is a matter of hours rather than weeks if you know where to look, though it varies by app. The next four sections walk through them. This is my rule of thumb, not a formal standard, and it does not replace a proper audit for apps handling highly sensitive data such as health or financial records.

![Four checkpoint gates on a path leading to an app, representing pre-launch checks for an AI app builder app](https://cms.filipeeduardo.dev/wp-content/uploads/2026/10/ai-app-builder-production-1.webp)

Four checks stand between a generated prototype and real users.

## Who can read which data in my AI-built app?

This is the check I do first. With Supabase, the browser talks to the database directly, and [row-level security (RLS) decides what each logged-in user may see](https://filipeeduardo.dev/blog/supabase-rls-ai-built-app). If RLS is off, or rules are too loose, anyone who has your public project URL and key can query tables. Apps built with Lovable have shown a pattern of weak RLS rules, so this is where I look before anything else.

### What to test

-   Open the Supabase dashboard and list every table. Confirm RLS is enabled on each one.
-   Read each policy. A rule that says anyone can select, insert or update is usually a leftover from development.
-   Create two test accounts. Log in as user A, copy an ID of user B’s record, and try to read or change it.
-   Test while logged out. Anonymous access should be limited to what is truly public.
-   Check storage buckets. Confirm whether uploaded files are public or private, since a bucket can be set up as public.

### Common mistakes

Policies that check only that the user is logged in, not that the row belongs to them. Admin features protected only by hiding a button in the interface. Tables with personal data readable by every account. The fix is usually a handful of policies written carefully, not a rebuild. Ask the builder’s AI to write them if you like, but verify with the two-account test, because that is the proof that matters.

## Are any secret keys exposed in the browser?

Anything shipped to the browser is public. Anyone can open developer tools and read it. Some keys are designed for that, such as the Supabase anon key (safe only if RLS is correct) and Stripe’s publishable key. Others must never leave the server: the Supabase service role key, Stripe secret keys, webhook secrets, and third-party API keys for email, AI models or SMS.

### How to look

-   [Open your live app, view the page source and the network tab](https://filipeeduardo.dev/blog/leaked-api-keys-ai-built-app), and search for words like secret, key, token and service\_role.
-   Search your code repository, including its history, for the same terms and for .env files.
-   Check any call from the frontend directly to a paid API. If the key is in the browser, someone can use it on your bill.

### What to do if you find one

Rotate the key first, meaning generate a new one and revoke the old one. Removing it from the code is not enough, because it may already have been copied. Then move the call to a server function or backend, where the key stays as an environment variable and the browser only calls your endpoint. That endpoint should also check who is asking and limit usage.

## Does my app confirm payments correctly?

This is where generic scanners fail, because it is business logic. A common pattern in generated code: after the customer returns from the Stripe checkout page, the app marks the order as paid based on the redirect. But a redirect proves nothing. Someone can visit the success URL directly, or the customer may pay and close the tab before returning.

The reliable approach is that [your server receives events from Stripe (webhooks)](https://filipeeduardo.dev/blog/stripe-webhook), [verifies their signature with the webhook secret](https://filipeeduardo.dev/blog/stripe-webhook-secret), and only then grants access or marks the order paid.

### What to verify

-   Is there a webhook endpoint, and does it verify the signature?
-   Is access granted only from verified events, not from the success page?
-   Is the handler idempotent? Stripe can send the same event more than once, and you must not create two orders or credit twice.
-   [What happens on failed payments, refunds, disputes and canceled subscriptions?](https://filipeeduardo.dev/blog/stripe-webhook-events)
-   Can a user change the price or plan in a request from the browser?

[Test with Stripe’s test mode before any real card is charged](https://filipeeduardo.dev/blog/stripe-test-webhook). I will not go deep on webhooks here, since they deserve their own walkthrough, but if you check only one payment item, make it this: never trust the browser to say that a payment succeeded.

![Payment provider sending a signed message to a server while the browser is not trusted, illustrating payment confirmation](https://cms.filipeeduardo.dev/wp-content/uploads/2026/10/ai-app-builder-production-2.webp)

The server should trust the provider’s signed event, not the browser’s word.

## Do I have backups I can actually restore?

A backup you have never restored is a hope, not a backup. Generated apps often run on a single database with default settings, and founders assume someone else is handling it. Under the shared responsibility split, backups are your job to confirm.

### Questions to answer

-   Does your database plan include automatic backups, and how far back do they go?
-   Is point-in-time recovery available on your plan, or only daily snapshots?
-   Are uploaded files backed up too, or only the database?
-   Do you have a copy of your code outside the builder?
-   Has anyone restored a backup into a separate test project and confirmed the app works with it?

Also think about accidents, not only attacks. A generated migration or an AI edit can drop a column or overwrite data. A restore drill is usually a short exercise (my estimate: a couple of hours for a small app) and tells you how long recovery would take. Check your plan’s current backup features in the provider’s documentation, since they change over time and vary by tier.

## Should I fix the AI-generated code or rewrite it?

Fix first. Treat the generated code as a first draft, and fix the highest-risk issues in the existing code before you consider a rewrite. Rewrites feel clean but throw away working screens, flows and decisions, and they delay launch while adding new bugs.

The order I would use:

1.  Lock down data rules and rotate exposed keys.
2.  Fix payment confirmation and make handlers idempotent.
3.  Set up backups and test a restore.
4.  Move the code to GitHub, add basic error monitoring and a staging copy.
5.  Then clean up structure where it hurts: duplicated logic, giant files, slow queries.

A rewrite becomes reasonable when the data model is fundamentally wrong, when every change breaks something else, or when you need capabilities the generated structure cannot support. Even then, I would extract what works, such as the schema and the screens, instead of starting from zero. [Asking the builder to fix its own security issues helps with simple things](https://filipeeduardo.dev/blog/ai-code-review), but data rules, keys and payment paths are exactly what these tools tend to get wrong, so verify its answers yourself or with a second pair of eyes.

## When is staying on the AI app builder the better call?

[Leaving is not always the answer.](https://filipeeduardo.dev/blog/no-code-ai-app-builder) Staying is often better when:

-   The app is a prototype or internal tool with a handful of trusted users.
-   You are still validating the idea and the design changes weekly.
-   There are no payments and little sensitive data.
-   No one on the team could maintain a separate codebase and hosting.
-   The four checks pass and the builder’s limits are not blocking you.

Moving has real costs: you take on hosting, deployments, environment variables and monitoring. If nobody can handle that, you may be trading a manageable risk for a new one.

Signs it is time to leave: you need custom backend logic the builder fights you on, you need environments and code review, pricing or limits no longer fit, performance suffers under real traffic, or a customer requires control over where the app runs. The decision should come from a concrete blocker, not from a vague feeling that real companies use their own hosting.

## How do I move my code to GitHub and my own hosting?

[Code built in Lovable can be moved to GitHub and the owner’s own hosting.](https://filipeeduardo.dev/blog/leaving-lovable-own-your-code) Other builders have their own export options, so check what yours supports before planning.

1.  **Connect the project to GitHub** using the builder’s integration, so the repository becomes the source of truth.
2.  **Clone it and run it locally.** Fix anything that only worked inside the builder.
3.  **List environment variables** and store them in your host’s settings, never in the repository.
4.  **Own the backend accounts.** Make sure the Supabase and Stripe accounts belong to you or your company, not a personal login of a former contractor.
5.  **Choose hosting.** A static or Next.js frontend works on common platforms such as Vercel or Netlify, while server code can run as functions or on a small server.
6.  **Set up a staging copy** with test keys, deploy there first, and test login, data rules and payments.
7.  **Switch the domain** only after staging passes, and keep the old version running until you are sure.

Do this before launch if you can. Moving a live app with paying users means migrating data and avoiding broken sessions, which is doable but needs more care. I make no promises about downtime in any migration, but a staging rehearsal reduces surprises a lot.

## Want a second opinion on your app?

If you built something with an AI tool and are unsure about one of these four checks, email me@filipeeduardo.dev with the link and a few lines about what it does, and I will tell you what I would check first.

## Frequently asked questions

### Are apps from AI app builders safe to launch?

They can be, but not by default. The builder secures its infrastructure, while you are responsible for data rules, exposed keys, payment logic and backups. Run the four checks before real users arrive.

### Do I need a full security audit?

Usually not at the start. A few focused checks find most of the risk. A fuller audit makes sense if you handle sensitive data, regulated information, or large payment volumes. Check applicable rules with a lawyer, as this is not legal advice.

### Can a security scanner replace these checks?

It helps with known issues but misses business logic, such as unverified Stripe webhooks or duplicate orders. Combine scanning with manual tests like the two-account data check.

### Is Supabase itself the problem?

No. The pattern seen in Lovable apps is weak RLS rules in the project configuration. Supabase provides the tools, and the app owner must set the rules correctly.

### Does it cost more to fix things after launch?

Yes. Fixes grow more expensive once real users and payments exist, because you must also deal with exposed data, migrations and customer trust.