Your AI-built app worked or looked like it works. Then you tested it or changed one thing and everything broke.

You started with an idea.

You opened Lovable, Bolt, Replit, Cursor, Claude Code or another AI coding tool and started building.

A few prompts later, you had:

• A working interface
• Authentication
• A database
• APIs
• Payments
• An admin panel
• Something that actually looked like a product

That part was impressive.

Then you started making changes.

One prompt fixed the login screen and broke registration.

Another fixed registration and changed the database query.

You asked the AI to fix that.

Now the dashboard doesn't load.

So you try another prompt.

Eventually, you're sitting in front of a project where nobody is quite sure what changed, why it broke, or what the AI is going to destroy next.

That's where we come in.

We fix broken vibe-coded apps.

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What is a vibe-coded app?

Vibe coding means using AI to build software through natural-language instructions instead of writing every part of the application yourself.

It's useful.

It's also very easy to take too far.

AI coding tools can generate a working prototype quickly, but the code underneath still needs to deal with real users, real data, authentication, security, failures and changes. Recent research on vibe coding also describes debugging as a mixed process where AI helps, but developers still need to evaluate and verify what it produces. :contentReference[oaicite:1]

The problem usually isn't that AI wrote code.

The problem is that the code kept growing without anyone taking responsibility for the structure underneath it.

That works until the application becomes complicated enough to expose the cracks.

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Your app doesn't need to be thrown away

This is one of the first things we check.

If your AI-generated project is broken, starting from zero isn't automatically the answer.

We first look at what you already have.

We check:

• The project structure
• Authentication
• Database design
• API calls
• State management
• Dependencies
• Environment variables
• Error handling
• Build configuration
• Deployment setup
• Security problems

Then we decide what actually needs fixing.

Some projects need a few targeted repairs.

Some need a serious cleanup.

Some need sections rebuilt.

And occasionally, a project really is better off being replaced.

We won't tell you to rebuild everything simply because the code is ugly.

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What we fix

Authentication problems

AI-generated authentication can look fine during development and still have serious problems.

We deal with issues such as:

• Login failures
• Broken sessions
• Token problems
• Incorrect permissions
• Registration errors
• Password reset failures
• Protected routes that aren't actually protected
• And much more

Authentication is one area where "it works on my laptop" isn't much of a defence.

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Database problems

A prototype database can survive a handful of test users.

Your production database has different expectations.

We fix problems such as:

• Incorrect relationships
• Bad queries
• Duplicate records
• Missing indexes
• Broken migrations
• Data not being saved correctly
• Queries that become slow as data grows
• And much more

We also trace problems back to the application code instead of repeatedly patching the visible error.

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API and backend problems

Sometimes the frontend looks fine until it talks to the backend.

Then you get:

401 Unauthorized
403 Forbidden
404 Not Found
500 Internal Server Error
Or something even less helpful.

We trace the request from the client to the server and back.

That means checking:

• Request payloads
• Authentication
• Validation
• Controllers
• Services
• Database queries
• External APIs
• Error handling

The goal is to fix the actual failure instead of teaching the AI another creative way to hide it.

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AI-Generated Code Cleanup

This is one of the biggest problems with long-running AI projects.

The AI doesn't know that you already have a function doing something.

So it creates another one.

Then another prompt creates a third version.

After enough iterations, you have:

handleUser()
handleUserData()
processUser()
processUserRequest()
processUserUpdate()

Five functions. One job. Nobody knows which one should be used.

We clean this up. That can include:

• Removing duplicate code
• Combining repeated logic
• Separating responsibilities
• Simplifying components
• Removing unused dependencies
• Fixing confusing naming
• Breaking oversized files into sensible modules

The goal isn't to make the code look pretty.

The goal is to make the project easier to change without breaking something else.

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When the AI Keeps Making the Problem Worse

This is usually the point where people get stuck.

You give the AI an error. It suggests a fix. The error changes. You give it the new error. It changes three files. Now there are two errors.

So you give it those. The conversation gets longer and the project gets stranger.

At some point, stop prompting and hand over your problems to us

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Security Problems in AI-Generated Apps

This part gets ignored far too often.

A working application can still be unsafe.

We've seen the pattern repeatedly across AI-built projects:

• Secrets placed in client-side code
• Missing authorization checks
• And much more

These aren't cosmetic problems.

If your app handles customer accounts, payments or private information, they need attention before you send real users into the system.

Current industry discussions around AI-generated code are also putting greater attention on security defects and the difficulty of managing rapidly generated code at production scale.

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Your App Works. But Can It Survive Real Users?

A demo and a production application are different things.

A demo might have:

• 1 user
• 10 records
• 1 API request

Production might have:

• 1,000 users
• 100,000 records
• Thousands of API requests

That's when problems appear.

We look for things such as:

• Slow database queries
• Unnecessary API requests
• And much more

You don't need a massive infrastructure setup for every application.

You need the infrastructure your application actually requires.

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We Work With the Code You Already Have

You don't have to explain your entire project from memory.

Send us the project. Tell us what is broken. We'll inspect the code and determine what you're dealing with. And even if you can tell what the issue is, just describe and we will take it up from there.

That can be a:

• Lovable project
• Bolt project
• Replit project
• Cursor-built application
• Claude Code project
• ChatGPT-generated application
• Custom React or Next.js application
• Node.js backend
• React Native mobile app
• Other AI-assisted software project

The tool you used to create it isn't the important part.

The code is.

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What the Rescue Process Looks Like

1. We Inspect the Project

We don't start randomly changing files. First we understand what exists.

2. We Reproduce the Problem

If we can't reproduce it, we're guessing. We don't like guessing.

3. We Find the Root Cause

We trace the error through the application instead of repeatedly treating symptoms.

4. We Fix the Affected Code

The fix should solve the problem without creating three new ones.

5. We Test It

We verify the original problem and check related functionality.

6. We Clean Up Where Necessary

If the broken feature depends on bad structure, we fix the underlying code instead of leaving another patch behind.

7. We Get You Back to Shipping

The objective isn't to spend six months rewriting your project.

It's to get your application into a state where you can keep building it.

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When Should You Ask for Help?

You probably need a proper code review if:

• Every AI fix breaks something else.
• You don't understand parts of your own codebase anymore.
• Authentication keeps failing.
• Your database contains inconsistent data.
• Production is slower than development.
• You can't deploy the application.
• The AI keeps rewriting the same files.
• You are afraid to touch working code.
• You have stopped adding features because fixing old ones takes too long.

That last one is usually a pretty good sign.

Your application has stopped being a project and started being a hostage situation.

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We Don't Hate Vibe Coding

Vibe coding isn't the enemy.

Used properly, AI can dramatically reduce the time required to build software. Current developers are using tools such as Cursor, Claude Code and other AI coding agents to build real applications faster.

The problem comes when generated code gets shipped without being reviewed, tested or maintained.

You can use AI to build the first version.

You can use AI to build the tenth version.

Someone still needs to understand what the application is doing.

That's the difference between having an AI-generated prototype and having software you can actually maintain.

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Your Vibe-Coded App Is Broken. We Can Fix It.

You don't necessarily need to start over.

You don't need another twenty prompts.

And you definitely don't need to spend another weekend asking an AI to fix the fix that broke the previous fix.

We rescue broken AI-generated applications.

We inspect the existing code, find the problems, fix what needs fixing, clean up the parts that have become difficult to maintain, and help get the application ready for real users.

If you built it with AI, that's fine.

Bring us the code. We'll deal with the mess.

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Tell us:

• What you built
• Which AI tool you used
• What's currently broken
• What you need the application to do

We'll start with the code you already have.