Quit Betting on One App, Went From $200 to $10,000/Month: A Side-Hustle iOS Developer Who Shipped 28 Apps in 8 Months

Dollar amounts include an approximate yen figure at ¥150/$1.

The Developer Who Gave Up on “One Big Masterpiece”

Max is an iOS developer with 8 years of software engineering experience and a father of two. He’s still working his full-time job and builds apps outside working hours, a familiar profile for a side-hustle developer. But the way he generates numbers runs opposite to the usual pattern.

Over 8 months, he shipped 28 apps. Monthly revenue is $10,000 (about ¥1.5M). Before he changed his approach, revenue was $200/month. His current revenue is 50 times that.

He puts it bluntly: “A lot of people think you need one big app to win.”

The Portfolio by the Numbers

The top 4 apps together add up to roughly $6,000. Out of the total $10,000, 60% comes from 4 apps. That is, 14% of the apps generate 60% of revenue. He himself acknowledges “the 80/20 rule is at work here.”

What He’s Actually Building

He’s not building massive apps. He researches 2–3 competitors, identifies the users’ single biggest pain point, and implements only that one core feature. Within a category like “student apps,” for example, he expands sideways across related keywords, physics AI, chemistry AI, math AI.

Development is in Flutter. He reuses roughly 90% of the code from past projects, drag-and-drop buttons, screens, onboarding flows, and paywalls are all built to be reused as UI components from the start. Design assets are pulled from his own Figma templates, App Store descriptions are generated by feeding keywords to ChatGPT, and releases are automated with Fastlane. This accumulated system is how the 2-hour record is possible.

The Turning Point: The Day He Watched YouTube

The moment the trajectory changed is clear: watching content by the YouTuber Adam Sleiter.

Before that, Max was pouring his time into building one “perfect app”, a passion project of sorts. Revenue at the time was $200/month. After watching Sleiter’s content, he switched his strategy to “ship a high volume of simple apps fast,” and abandoned that one app.

The before-and-after contrast is stark:

The most important part of this pivot is that the party deciding what to build shifted from himself to the market. Post-pivot, he uses the ASO tool Astro to research keywords and decides whether to build based on these conditions:

• Keyword popularity score of 20+
• Difficulty of 60–70
• Competitors already earning $100–200+/month on that keyword (confirmed via Sensor Tower)

The third is decisive. Choosing only keywords where competitors are already earning money is effectively a declaration that he won’t validate demand himself. Instead of spending months figuring out if a market exists, he only enters places where a market has already been proven to exist.

Why Mass Production Worked

First, the app store shoulders the cost of validation. The App Store has a keyword search that acts as a demand gateway, and competitor revenue can be estimated with external tools. You can confirm “this demand exists and is generating money” before you build. Unlike a web service, there’s no need to build acquisition from zero, winning store search rankings alone generates traffic. This is the premise on which a portfolio strategy is viable.

Second, marginal cost approaches near zero. 90% code reuse, templated Figma assets, ChatGPT-generated metadata, Fastlane automation. Design costs paid on app one carry forward to app two and beyond, so per-app time investment drops as volume increases. Shipping 28 apps in 8 months, nearly one a week, isn’t talent, it’s the result of designing for reuse.

Third, a system for cutting losses quickly. His operating process is organized into 6 steps: (1) find a keyword with a good popularity-to-difficulty ratio that’s already generating revenue, (2) study competitors and pick a single core feature, (3) use AI tools to rapidly design the screen flow and feature breakdown, (4) build the minimum viable MVP, (5) ship and observe, kill what doesn’t grow, let the data decide, (6) go back to what did grow and polish it, fix bugs, add ads.

“Once an app is published, you let go and move to the next project,” he says. “Don’t waste time polishing your app, thinking you need one more killer feature. Ship it and let users tell you what they think.” Polish only happens after the data says it’s growing. This ordering is the mechanism that concentrates resources into 4 of 28 apps.

Assumptions Not to Overlook

There are several caveats worth flagging in these numbers.

The $285–295/month tool cost breaks down as OpenAI $200, Gemini $50, Cursor $20, Astro $10, Firebase $5–10. More than half is metered AI API usage. As he adds more apps built around image recognition or AI processing, this cost rises, and even apps that fail to grow still incur API costs. The $10,000/month figure is what’s left after this variable cost.

Revenue concentrated in the top 4 apps is both a strength and a fragility. If any of those 4 sink due to a store algorithm change or a competitor entering the space, monthly revenue would visibly drop. The 24 apps that earn “very little” won’t fill that gap. The portfolio can be described as spreading risk, but in practice it’s a dependency on 4 apps.

There’s also a boost from the store’s new-release bump. As he himself observes, the App Store gives new releases initial exposure that then tapers off. The structure that keeps shipping baked into sustaining traffic also means the decay starts the moment you stop.

And it’s not disclosed how many of the 28 were complete failures. Everything besides the top 4 is described only as earning “very little”. The labor behind those 24 apps remains unquantified.

How Far Can You Copy This

What’s copyable is the decision ordering: don’t start from what you want to build, start from a keyword you can confirm is already generating revenue. Narrow to a single core feature. Don’t polish after launch, go back only to what the data shows is growing. None of this order requires capital or connections.

What’s hard to copy is 8 years of iOS development experience and reusable code assets. Only someone who can write code robust enough to reuse can claim “90% reuse.” Someone who can’t design onboarding and paywalls from scratch on their first app can’t ship 28 apps in 8 months. The 2-hour record is only possible on top of prior accumulated work.

Another point not to overlook: he’s still working full-time the whole time. Because living expenses are covered by his day job, the business survives even when 24 apps miss. Running the same odds of a gamble with no income to fall back on is a different level of difficulty.

The “mass-produce simple apps” strategy is a probability game. It assumes a low hit rate per app and pushes through with trial count and low per-trial cost. If you copy only the volume without understanding this structure, you’ll rack up costs without ever hitting.

Related Reading

• The Solo Developer Running Multiple Products in Parallel — Photo AI
• The Market Where Small Products Trade Hands — a VBA Tool Sold on Microns