Why your AI-built app breaks every time you add a feature (and how to stop it)

Your AI-built app breaks when you add a feature because the AI changes more code than you asked for, and nothing tells you when it does. There are no tests to catch the damage, the code is tangled, so one change ripples into others, and every fix is another AI change with the same risk. The way out is not a better prompt. It is a safety net: version control, a few automated tests and a cleaner structure, so a broken change is caught before your users find it.

What does the problem look like?

If you built your app with Lovable, Bolt, Cursor or a similar tool, this probably sounds familiar:

• You ask for a small change, such as a new field on a form, and the login stops working.
• You ask the AI to fix the login, and now the dashboard shows the wrong data.
• You fix the dashboard, and the bug from last week is back.
• After a few rounds you are spending more time fixing than building, and you are afraid to touch the app at all.

You are not doing anything wrong. This is how most AI-built apps behave once they grow past the demo stage.

Why does adding one feature break something else?

The AI only sees part of your app

AI coding tools work with a limited view of your code. When you ask for a change, the tool reads the files it thinks are relevant and rewrites what it believes needs rewriting. It cannot reliably know that another page depends on the function it just “improved”. So it changes shared code, renames things or rewrites a file in full, and something elsewhere quietly stops working.

Nothing checks the app after a change

In professional software, every change is checked by automated tests: small programs that log in, create an order, send an email, and shout when the result is wrong. AI-built apps usually have none. So the only test is you, clicking around after each change, or your users finding the problem for you.

The same logic lives in many places

When an AI tool builds features one prompt at a time, it often writes similar code again instead of reusing what exists. You end up with three slightly different versions of “check if the user is logged in” or “calculate the price”. Fix one, and the other two still have the old behaviour.

Big files where everything touches everything

AI-generated apps often grow into a few very large files where data loading, business rules and screen layout are mixed together. In code like that, every change touches more than it should.

The database changes without a plan

When the AI adds a feature that needs new data, it may change your database tables directly. Without proper migrations (step-by-step, reversible changes to the database), existing data and older parts of the app can break.

Fixes are patches, not solutions

When something breaks, the natural move is to ask the AI to fix it. The AI fixes the symptom, often with another quick patch, and the real cause stays. That is why the same bugs come back.

How do you stop the loop?

You do not need to throw the app away. These six steps make it safe to keep building.

1. Put the code under version control

Connect your project to Git and save a version before every AI change. Lovable and Bolt both have built-in GitHub sync, and Cursor works directly on a Git project on your computer. If a change breaks something, you can see exactly what changed and go back in seconds, instead of asking the AI to undo its own work.

2. Make one small change at a time

Ask for one feature per prompt, tell the tool which files it may change and which it must not touch, and read the summary of what it changed before you accept it. Small changes are easier to check and easier to undo.

3. Add automated tests for the flows that make you money

You do not need tests for everything. Start with the five to ten flows that must never break: sign-up, login, payment, the main thing your customers do in the app. Run them automatically on every change. From then on, a change that breaks checkout is caught in minutes, not by an angry customer.

4. Clean up the structure where it hurts

Split the biggest files, remove the duplicate versions of the same logic and keep each business rule in one place. You do not need a full rewrite. Clean up the parts you change most often, and the ripple effects drop sharply.

5. Separate testing from production

Try changes on a test version of the app with test data first, and only then release them to real users. Database changes should go through migrations that can be rolled back.

6. Know when to get help

If you have tried the steps above and still fix the same problems again and again, or if the app handles payments or personal data and you are not sure it is secure, it is time for a review by an experienced developer. The longer the loop runs, the more tangled the code gets.

Do you have to rebuild the app?

Rarely. Most AI-built apps have a reasonable foundation. What they miss is the production layer: tests, structure, security and a safe way to release changes. Adding that layer is usually much faster and cheaper than starting over, and you keep everything your users already know.

How we help

At InitHere we take over apps built with Lovable, Bolt, Cursor and similar tools and make them safe to grow. We fix what is broken, close security gaps, add tests for your critical flows and set up automatic, reversible releases, so new features stop breaking old ones. You can keep building with AI tools afterwards. The difference is that a broken change is now caught before it goes live.

• AI-built app rescue: from 35,000 DKK, typically 1–6 weeks.
• System Health Audit: not sure where to start? A Quick Scan from 4,995 DKK shows what is safe to keep and what must be fixed, with a fixed price for the next step.

Book a free 30-minute call and tell us what keeps breaking.

FAQ

Can I keep using Lovable, Bolt or Cursor after the app is fixed?

Yes. Once the app has version control, tests and a cleaner structure, AI tools become much safer to use, because a change that breaks something is caught before it reaches your users.

Why does the same bug keep coming back?

Usually because the AI fixed the symptom, not the cause, or because the same logic exists in several places and only one copy was fixed. Tests stop a fixed bug from coming back unnoticed.

How do I know if my app is secure?

You cannot tell from the outside. AI-built apps often have exposed secret keys, missing access checks or database rules that let users see each other’s data, and they all look fine in the demo. In one documented case, researchers found that 170 of 1,645 scanned Lovable apps had database tables without access rules, so their data could be read by anyone (Cloud Security Alliance). If your app uses Supabase, check that Row Level Security is turned on for every table; if it uses Firebase, check that your security rules do not allow anyone to read or write everything. A short code review will show the rest.

How long does it take to stabilise an AI-built app?

Most projects take between one and six weeks, depending on the size of the app and how much is broken. We fix the critical security and data problems first, so the riskiest issues are gone early.