$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

  1. Find a keyword with strong popularity/difficulty ratio and verified competitor revenue.
  2. Study competitors; define the single core feature that solves the main user problem.
  3. Plan with AI — generate a development roadmap, feature list, and UX structure before building.
  4. Build a clean MVP with only the features needed to deliver value.
  5. Ship, release, and move immediately to the next app — let data decide winners.
  6. 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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