For those who say, "I have an idea but can’t code" or "I want to quickly create a prototype," Rork is here to generate an app from natural language and guide you all the way to store publication. This article carefully explains how I tried it and the points to watch out for.
Rork receives praise for being "easy to build apps without coding" and "great for quickly creating an MVP", but also criticism for "numerous bugs" and "lack of customization". From Momen article
Reddit comments include:
“Their concept is very nice, looks solid but it crashes and freezes a lot”
“First of all, there is no way I can make any code change manually in their web-IDE... Support from them even after paying is just absent.”
1. App Overview
A web and mobile compatible app that centralizes household management. Integrates calendar, task management, shopping list, home maintenance logs, garbage schedule, and budgeting with real-time sharing among family members.
2. Users
Entire family (multiple accounts / permission settings)
Optional sharing with non-family members (e.g., housekeepers, repair contractors)
3. Functional Requirements
3.1 Calendar & Scheduling
Unified view of all family schedules (color-coded)
Toggle between personal and shared events
Set responsible and participating members
Reminders via push/email
Google Calendar / iCal sync
3.2 Chores & To-Do Management
Task registration (assignee, due date, priority)
Recurring tasks (e.g., weekly cleaning)
Checklist-based progress tracking
Task completion history (visualizing chore distribution)
3.3 Shopping List
Category-based lists (food, daily goods, etc.)
Voice input / barcode scan for adding items
Collaborative editing
Store-specific purchase history
Automatic "out of stock" notifications (e.g., milk quantity tracking)
3.4 Home Repair & Maintenance
Repair log (date, details, contractor, photos)
Inspection scheduling (e.g., AC cleaning, roof inspection)
Attachment of quotes/receipts
Reminders (semi-annual/annual)
3.5 Garbage Schedule
Register local collection calendar
Notifications the day before/on the day (time-specific)
Waste sorting notes
3.6 Money Management
Expense/income logging (by category)
Monthly/annual reports (graphs)
Spending ratio by family member
Budget setting & over-budget alerts
Bank/credit card statement import (CSV/OFX)
3.7 Common Features
Account management (family & individual levels)
Permission settings (e.g., children read-only)
Cloud data sync
Offline mode (sync upon reconnection)
Multi-language support (JP/EN)
4. Non-functional Requirements
Supported Devices: iOS / Android / Web
UI: Simple, intuitive, suitable for all family members
Performance: <0.5s response, store >10,000 records
Security: User auth (OAuth2/password), HTTPS encryption, AES256 data encryption
Backup: Daily cloud backup
Notifications: Push (mobile), email
Data Sharing: Real-time family sync
Extensibility: API-based (REST/GraphQL)
Reliability: 99.9% uptime (cloud hosting)
5. Additional UI/UX Ideas
Dashboard showing today's schedule, tasks, garbage day, shopping list
Voice assistant integration (Google Home, Alexa)
Stickers/comments for tasks/events
AI-based auto-categorization (receipt photo scanning)
Bundled push notifications to reduce noise
Some buttons were non-functional, requiring 2–3 rounds of chat refinement.
Rork is highly effective for cases where you want to quickly bring an idea to life and test it, but it has limitations in stability and support. Fully automated operation is difficult — final quality assurance and review handling still require human intervention.
2025-08-10
An experimental article on extracting characters and emotions from the fairy tale 'Little Red Riding Hood' using LangExtract.
2025-08-08
This paper proposes a novel method called Query-Guided Activation Refilling (ACRE) aimed at improving efficiency and performance in processing long contexts within Large Language Models (LLMs). By combining a two-layer KV cache and query-guided refilling, the approach enables processing of contexts beyond the native context window, significantly enhancing the practicality of long-context information retrieval.
2025-08-08
This paper proposes a novel method, "Desiview," for automatically identifying desirable review comments (DRC) that lead to code changes in code reviews. By constructing a high-quality dataset using Desiview and fine-tuning and aligning the LLaMA model, we demonstrate a significant improvement in DRC generation capability. This approach is expected to greatly contribute to code review automation and software development support.