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$10K/month from 28 apps: a portfolio betting strategy for indie devs
Executive overview
Max, a full-time iOS engineer, went from $200 to $10,000 per month in eight months by abandoning the single-app obsession in favour of shipping dozens of small, focused apps. The core insight is that speed and detachment beat polish and perfection: build one feature, ship it, forget it, and let the App Store tell you what works. Four apps generate roughly $1,500 each, the rest contribute small amounts — a textbook 80/20 distribution. Total infrastructure costs run under $300/month on a $10K gross, keeping margins high from day one.
Finding profitable ideas with keyword research
- ASO tool Astro is the primary idea source; Max searches categories he wants to build in or use himself.
- Target keywords with at least 20% popularity and 60–70% difficulty — high enough to have a real market, low enough to rank.
- Look for clusters of related keywords targeting the same user group (e.g., physics AI, chemistry AI, math AI all target students) — one codebase can feed multiple app listings.
- Validate by checking competitor revenue in Sensor Tower; minimum benchmark is €100–200/month from top competitors, otherwise skip the market.
- The goal is to enter markets that already pay, not to create demand from scratch.
Building lean and shipping fast
- Study two or three competitor apps, then identify only the single core feature tied to the target keyword — ignore everything else.
- Prompt ChatGPT or Gemini with the keyword plus UI/UX constraints to generate a full implementation plan before writing a line of code.
- Reuse UI components aggressively: drag-and-drop settings screens, onboarding flows, and paywalls from previous projects; up to 90% of code can be copied across apps.
- Use Cursor or Claude to map out all screens and flows upfront so there are no surprises mid-build.
- App assets (screenshots, icon) are templated in Figma from previous projects; descriptions are generated by AI.
- Record build time: two hours from idea to App Store submission. Typical range: a few hours to one week.
The six-step launch playbook
- Find a keyword with strong popularity/difficulty ratio and verified competitor revenue.
- Study competitors; define the single core feature that solves the main user problem.
- Plan with AI — generate a development roadmap, feature list, and UX structure before building.
- Build a clean MVP with only the features needed to deliver value.
- Ship, release, and move immediately to the next app — let data decide winners.
- Return to apps showing organic traction; polish, fix bugs, and add paid ads to double down on natural growth.
Reading the data and scaling winners
- Every new app gets an App Store launch boost; after it fades, monitor whether downloads stabilise, grow, or decline.
- Apps that stabilise or grow have proven organic fit — these are the ones worth improving.
- Paid ads are only added to proven winners, avoiding ad spend on unvalidated ideas.
- The portfolio acts as a self-filtering system: ship many bets, scale only the ones the market validates.
Tech stack and costs
| Tool | Use | Monthly cost |
|---|---|---|
| Flutter | App framework | $0 |
| Fastlane | Automated shipping | $0 |
| Cursor | AI coding | $20 |
| Firebase | Backend, auth, DB, hosting | $5–10 |
| OpenAI | Image recognition, AI features | ~$200 |
| Gemini | AI features | $50 |
| Mixpanel | Analytics | $0 (free plan) |
| Astro | iOS keyword/ASO data | $10 |
| AppFollow / Fox Data | iOS & Android data | $0 (free plan) |
Total costs: approximately $285–295/month against $10,000 revenue.
Mindset: the shipping muscle
- The single biggest mistake Max made for years was treating one app as precious — pouring time into polish and extra features that never moved the needle.
- The shift came from discovering Adam Sleitel's "ship many simple apps" framework on YouTube.
- Don't add one more "killer feature" before launch — ship bug-free with one feature and let users respond while you're already building the next app.
- Building software is commoditising rapidly; execution speed and reusability of components will increasingly determine who wins.
- The portfolio model means no single failure matters — volume creates the signal.
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