From Fired Software Engineer to Profitable App Founder in 30 Days

About a month ago, the creator behind the YouTube channel "Andy Tries Coding" was fired from their corporate software engineering job. Instead of immediately job hunting, they set an ambitious goal: build a profitable iOS app without knowing how to code in Swift, and document the journey to reach five-figure monthly recurring revenue (MRR). Inspired by solo indie developers on X (formerly Twitter) who were hitting massive financial numbers, they dove headfirst into the development scene.

Here is a breakdown of how they built, troubleshot, and launched a profitable AI app in just one month, and how you can apply these indie-dev strategies to your next tech project.

💡 Finding the Idea and the "Twist"

The app idea was a polished clone of a proven, highly profitable concept: an AI-powered calorie tracker where users simply snap a picture of their dish to instantly get its calories and macronutrients.

However, releasing a simple clone isn't enough to get downloads. You need a twist. Drawing on a personal passion for running, the creator tailored the app to focus on how different types of food give you different amounts of energy and affect how you feel. This minimum viable product (MVP) approach ensured they weren't wasting time on unnecessary features, but rather solving a specific problem for a specific niche.

🛠️ The AI Tech Stack: Cursor, Xcode, and Microservices

To build the app without knowing Swift, the developer relied heavily on Cursor, an AI coding assistant, alongside Xcode and the iOS simulator.

For the core functionality—analyzing food images—they had to make a critical tech choice. Pre-built APIs cost upwards of $100 per month for commercial use, and building a custom AI model from scratch using TensorFlow and Python would take far too long. The winning solution was a pay-as-you-go microservice that charged a low price per picture analyzed, keeping overhead incredibly low. To design the UI, they pulled mockup inspirations from Dribbble and Mobbin, feeding them into Cursor to build the app's structure.

🐛 Navigating Bugs, Onboarding, and Monetization

Building with AI isn't a magical, bug-free process. The developer faced heavy friction trying to get the backend to successfully connect to the AI model, analyze the response, and store the image in a database. Furthermore, Cursor struggled to fix UI bugs related to zoomed-in sections because the issues were buried too high up in the UI hierarchy.

Knowing that a great product is useless if it doesn't convert, they focused heavily on the user flow:

• Analytics: They integrated PostHog to track exactly where users were dropping off during the onboarding steps.

• Authentication: They easily implemented Google and email login using Cursor, but had to create a hard-coded email bypass just for Apple reviewers, who refused to use the app's magic link flow.

• Monetization: They used RevenueCat to build a drag-and-drop custom paywall. This process was riddled with confusing App Store Connect errors, like missing subscription metadata and incomplete bank details, which they had to manually solve through Google and Reddit searches.

🍏 Surviving the Apple App Store Review

Exactly one month after starting, they submitted the app to the App Store—and were immediately rejected.

Apple requires tedious setups like dedicated web pages for Terms of Service and Privacy Policies. More importantly, Apple caught a massive bug: the app's hard paywall was accidentally blocking users from taking pictures of their food even after they paid for the subscription. After fixing the paywall bug and missing description links, the app was finally approved and went live.

📈 The Launch Results

In its very first week, the app generated actual revenue strictly from organic traffic, as Apple's algorithm naturally pushes new apps to users in their first few days on the store. To keep the momentum going, the creator launched a community for mobile app developers called "App Builders" and plans to leverage Instagram Reels to market the app and scale their MRR