This AI App Building Method Cloned a $7 Million Per Month iOS App Without Writing a Single Line of Code

The $84 Million App Clone Built With AI in 10 Prompts That Is Now Live on the App Store

Vibe coded apps are taking the internet by storm in 2026, and what you are about to read is the most convincing proof that AI has completely changed what it means to build a mobile app from scratch.

Two builders sat down with nothing but a clear idea, a mobile-first AI coding tool called Vibe Code, and a plan to clone one of the most profitable iPhone apps on the market right now.

The app they chose to clone is called Cleanup, a phone storage cleaner that pulled in $7 million in revenue in a single month and sits comfortably at $84 million per year in earnings, with over 50 million active users swiping through their photos every month.

If you are someone who uses tools like ProfitAgent to build automated online income systems, then this story is going to hit differently because it shows exactly what is possible when you combine AI tools with the right execution strategy.

The entire vibe coded build was done on an iPhone and an iPad, synced together in real time, with zero use of a desktop computer during the building phase, and the finished app was submitted to the Apple App Store before the session ended.

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What the App Actually Does and Why It Was the Right Clone Target

The app concept is brilliantly simple, and that simplicity is a big part of why it generates so much revenue.

It works exactly like Tinder but for your photo library, meaning you swipe left on a photo to delete it and swipe right to keep it, and the whole thing is designed to make clearing up your iPhone storage feel fun and addictive rather than like a chore.

The original app, Cleanup, dominates the App Store with a subscription model that charges users around $34 per month, which works out to nearly $400 per year for what is essentially a photo management tool that most people could not live without once they try it.

The vibe coded version they set out to build needed to match the core features of this app, including duplicate photo detection, blurry photo scanning, a Tinder-style swipe interface, folder-based swiping, a trash bin for safe deletions, and a clean native iOS design that felt professional from the very first screen.

Every single one of those features was built using natural language prompts inside the Vibe Code app, with no traditional coding involved, which is exactly the kind of workflow that tools like AutoClaw are designed to complement when you are building and automating online business systems at scale.

How the First Prompt Set the Foundation for the Entire Vibe Coded App

The very first prompt was carefully crafted to give the AI a full picture of what the app needed to accomplish.

It instructed the AI to search the internet, find the Cleanup app, understand its core value proposition, understand what it does for users, and then recreate the entire thing as a native iOS app with full access to the device’s photo library.

That single prompt generated an app that loaded over a thousand photos, displayed a bottom navigation bar, and surfaced a duplicate photo scan that found 251 duplicate images taking up 7.9 gigabytes of storage space, all within the first build cycle.

This is what vibe coded development looks like at its best, you describe the outcome you want in plain English, and the AI builds the functional structure around that description immediately.

The app was running live on both an iPhone and an iPad simultaneously because both devices were signed into the same Vibe Code account, meaning any change made on one device reflected on the other in real time, which is one of the most powerful features of this vibe coded workflow.

How Bugs Were Fixed One Prompt at a Time Throughout the Build

Every real app has bugs, and the vibe coded version was no different, but the way those bugs were handled is what makes this process so teachable.

The first bug discovered was a state error where deleted photos would still show up in the app gallery until the user navigated away and came back, which was resolved with a single direct prompt that described the exact behavior and asked for an immediate fix.

One of the most important lessons shared during this build is that it is almost always better to fix one thing at a time rather than bundling three or four changes into a single prompt, because the AI performs more reliably and the results are more predictable when the scope is narrow and focused.

The Tinder swipe feature was the most complex part of the build and also the first time the app threw a real crash error, which happened the moment the swipe tab was opened for the first time.

The fix was handled by copying the error message directly from the device and pasting it back into the AI with a short explanation of exactly when the error occurred, and the agent resolved it in the next build cycle.

This back-and-forth between testing on a real device and prompting for fixes is the core rhythm of vibe coded development, and it is a rhythm that anyone can learn because it does not require any coding knowledge at all.

How the Trash Bin Feature Solved the Biggest UX Problem in the Entire App

The swipe-to-delete experience had one persistent problem that took several prompts to solve properly.

Every time a user swiped left to delete a photo, the iOS device would show a native confirmation popup, and in the moment that popup appeared, the card stack behind the photo would shuffle and replace the next image with a random one instead of keeping the correct sequence.

Multiple approaches were tried to fix the stack ordering logic, but the breakthrough came when the decision was made to stop deleting photos immediately on swipe and instead move them to a trash bin first.

This trash bin approach meant that swiping left would simply add a photo to a holding area, and the user could then review and empty the trash all at once, which removed the iOS confirmation popup from the swipe loop entirely and fixed the stack shuffle problem at the same time.

The trash bin also felt more aligned with how Apple’s own Photos app handles deleted images, which made the experience feel native and trustworthy to users who are already familiar with the iPhone ecosystem.

If you are building an online business that depends on delivering real value to users, tools like ProfitAgent can help you automate the promotional and monetization side of that business while you focus on building the product itself.

How the App Icon and Branding Were Created Using ChatGPT in Minutes

Once the core functionality of the vibe coded app was solid, attention shifted to branding, and the app needed a name, a logo, and a landing page before it could be submitted to the App Store.

The name chosen was Photo Monkey, and the domain photomoney.app was purchased on Namecheap while the app was still being built, which shows the kind of parallel execution that makes this type of workflow so efficient.

The app icon was generated inside ChatGPT using a series of short prompts that asked for a cartoon monkey holding a photo and putting it in a trash bin, styled in the way that top 10 App Store icons are typically designed, with a clean square format and no white background.

The final icon showed a cheerful cartoon monkey with a blue background, a small gorilla photo in one hand, and a trash bin nearby, which gave the app a personality that matched its playful swipe-based interface perfectly.

The landing page was built using a tool called V0 and deployed to Vercel, and it included the two pages that Apple requires for any App Store submission, a terms of service page and a privacy policy page, both of which were created and linked before the submission was sent.

How the Vibe Coded App Was Submitted to the App Store Without Opening Xcode

Getting the app into the Apple App Store was handled through a terminal process called NPX Test Flight, which was run inside Cursor after the code was connected to the laptop via SSH from the Vibe Code app.

The SSH connection was set up directly from within the Vibe Code app by pressing three dots in the editing menu, selecting connect via SSH, and following the email instructions that were sent automatically, which included the password needed to authenticate the connection.

Once connected, the app icon was dragged into the project files in Cursor and renamed to icon.png, and then a single prompt asked the AI to move it into the correct folder and apply it as both the app icon and the splash screen.

The permissions list, known as the Info.plist file, was also updated by asking the AI inside Cursor to analyze the codebase and add the correct purpose strings for every permission the app needed, including full photo library access, which Apple requires before any app can be approved.

After those two changes were committed, the NPX Test Flight command was run in the terminal, the builder logged into their Expo and Apple App Store Connect accounts through the prompts, confirmed a series of yes or no questions about encryption and provisioning, and the build was submitted to the cloud for processing.

The entire submission process from SSH connection to build confirmation took only a few minutes, and the app appeared inside App Store Connect before the session was over, waiting for Apple’s review response.

Automating the traffic and monetization side of a launch like this is where a tool like AutoClaw becomes extremely valuable, because getting the app built is only half the battle, and driving consistent targeted users to it is what turns a good vibe coded app into a real revenue machine.

What This Entire Vibe Coded Build Teaches You About Building Apps in 2026

The most important lesson from this entire session is that building a real, functional, App Store-ready mobile app in 2026 no longer requires a development team, months of planning, or even a computer during the building phase.

The vibe coded workflow used here proves that a clear idea, a good prompting strategy, and a willingness to test on a real device and iterate quickly is enough to produce an app that competes directly with one generating $84 million per year.

The design work is always the easiest part and should always come last, because locking in the core functionality first means you will never accidentally break something that already works just by trying to make it look better.

Prompting for one change at a time, being specific about what should not change when you are asking the AI to fix something, and always testing on a real device before moving to the next feature are the three habits that separate fast vibe coded builds from slow and frustrating ones.

The trash bin feature, the auto-scan on launch, the folder-based swipe mode, the real-time sync between iPhone and iPad, and the Tinder-style animation all came from clear and focused natural language prompts, and every single one of those prompts was written by someone describing what they wanted to see, not what code they wanted to write.

Tools like ProfitAgent exist precisely for moments like this, because once your vibe coded app is live and getting downloads, you need a system that works in the background to bring in income and traffic without requiring you to be present every hour of the day.

The combination of vibe coded app development and automated income tools like AutoClaw is what makes building in 2026 feel genuinely different from any previous era of online entrepreneurship, because the barrier to entry has never been lower and the upside has never been higher.

We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.