Khalid AhmadSenior Software Engineer

Case study

Daily Life Comics

AI-powered comic generation app

Turn your daily story into a shareable anime/webtoon comic starring your recurring character.

Expo
React Native
Next.js
Supabase
Inngest
Google Gemini
fal.ai
Vercel

Role

Technical Founder & Solo Developer

Highlights

  • Built a cross-platform mobile app with Expo and Expo Router
  • Designed an async AI generation pipeline with Inngest background jobs
  • Integrated Google Gemini with fal.ai fallback for image generation
  • Implemented auth, storage, and database with Supabase

Problem

People want a fun, low-effort way to turn their everyday moments into a polished anime/webtoon comic, but generating consistent characters and multi-panel stories with AI is slow, expensive, and easy to get wrong.

Role focus

End-to-end owner across the Expo mobile app, the Next.js API, and the AI generation pipeline — from auth and storage to background job orchestration and cost controls.

Architecture

  • Expo (React Native) + Expo Router mobile app distributed via EAS development/preview builds.
  • Next.js API on Vercel handling auth, generation requests, and AdMob server-side verification.
  • Supabase for authentication, Postgres database, and media storage.
  • Inngest background jobs (comic-generate-free, comic-generate-paid, character-generate) for async AI work and retries.
  • Google Gemini as the primary image model with a fal.ai paid fallback for reliability.

Challenges

  • Keeping a recurring character visually consistent across comics and panels.
  • Managing AI cost with a shared free pool, paid keys, and rewarded-ad quota grants.
  • Reliable async generation with retries so jobs survive transient model failures.
  • Native-only modules (Google Sign-In, AdMob, RevenueCat) requiring real dev builds instead of Expo Go.

Outcomes

  • Shipped a working cross-platform app from character creation to shareable comic output.
  • Async pipeline keeps the UI responsive while generation runs in the background.
  • Fallback model strategy reduces failed generations under load.
  • Admin cost dashboard gives visibility into daily AI spend and free-pool usage.

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