A Firebase-first Android application for coordinating household chores through bidding, assignment, and progress tracking. I founded the project in 2025 and built the app independently from concept to Play Store testing.
Make household chores feel fair without negotiation overhead.
Octidy turns an everyday coordination problem into a product workflow: people create chores, household members bid the number of points they would accept, the lowest bid wins, and completed work updates household progress transparently.
Ownership
End-to-end delivery from concept to Play Console testing.
I handled the full development lifecycle: product definition, architecture, Firebase data modeling, responsive Compose UI, offline behavior, realtime sync, background deadlines, notifications, testing, Git workflow, documentation, production packaging, and Play Console deployment.
Users authenticate with Firebase Auth, create or join houses with invite codes, and keep separate spaces for roommates, couples, or families.
Bidding
Members bid on chores before a deadline. The app assigns the task to the lowest bidder and handles ties explicitly instead of hiding edge cases.
Accountability
Recurring chores, due dates, calendar views, local notifications, and progress statistics keep effort visible over time.
Implementation details
Engineering choices
Modern Android UI
Used Kotlin, Jetpack Compose, Navigation Compose, semantic typography, and responsive layouts for compact phones and tablets.
Realtime data layer
Structured a Firebase-first architecture around Firestore snapshot listeners, offline persistence, cached reads/writes, repository flows, ViewModels, and Hilt.
Background work
Used WorkManager for task deadlines and reminders, with Android notification channels and deep links into the relevant task flow.
Workflow
Collaborator-ready process, even as a solo project.
The project includes Git workflows and documentation intended to make future collaboration easier. I also used LLM-assisted programming to accelerate implementation where it improved speed without sacrificing code quality.
Related work
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A Firebase-first Android application for coordinating household chores through bidding, assignment, and progress tracking. I founded the project in 2025 and built the app independently from concept to Play Store testing.
Make household chores feel fair without negotiation overhead.
Octidy turns an everyday coordination problem into a product workflow: people create chores, household members bid the number of points they would accept, the lowest bid wins, and completed work updates household progress transparently.
Ownership
End-to-end delivery from concept to Play Console testing.
I handled the full development lifecycle: product definition, architecture, Firebase data modeling, responsive Compose UI, offline behavior, realtime sync, background deadlines, notifications, testing, Git workflow, documentation, production packaging, and Play Console deployment.
Product behavior
Core app flows
Households
Users authenticate with Firebase Auth, create or join houses with invite codes, and keep separate spaces for roommates, couples, or families.
Bidding
Members bid on chores before a deadline. The app assigns the task to the lowest bidder and handles ties explicitly instead of hiding edge cases.
Accountability
Recurring chores, due dates, calendar views, local notifications, and progress statistics keep effort visible over time.
Implementation details
Engineering choices
Modern Android UI
Used Kotlin, Jetpack Compose, Navigation Compose, semantic typography, and responsive layouts for compact phones and tablets.
Realtime data layer
Structured a Firebase-first architecture around Firestore snapshot listeners, offline persistence, cached reads/writes, repository flows, ViewModels, and Hilt.
Background work
Used WorkManager for task deadlines and reminders, with Android notification channels and deep links into the relevant task flow.
Workflow
Collaborator-ready process, even as a solo project.
The project includes Git workflows and documentation intended to make future collaboration easier. I also used LLM-assisted programming to accelerate implementation where it improved speed without sacrificing code quality.