Skip to content

Instantly share code, notes, and snippets.

@zgordan-vv
Created January 13, 2026 16:16
Show Gist options
  • Select an option

  • Save zgordan-vv/c441dc884a316fd46432736a504cecfe to your computer and use it in GitHub Desktop.

Select an option

Save zgordan-vv/c441dc884a316fd46432736a504cecfe to your computer and use it in GitHub Desktop.
Technical steps
# Idea Catalyst MVP - Implementation Plan
## Overview
This document outlines the step-by-step implementation plan for the Idea Catalyst MVP based on the PRD requirements.
## MVP Features
1. Interest setup (3-7 areas)
2. Voice idea capture
3. Idea database with list view
4. Weekly similarity analysis
5. Highlighted ideas + likes
6. Basic profile
---
## Phase 1: Project Setup & Architecture
### Step 1.1: Choose Technology Stack
- **Mobile Framework**: React Native (cross-platform for iOS + Android)
- **State Management**: Redux Toolkit or Zustand
- **Database**: SQLite (local) or Realm for mobile persistence
- **Voice Recording**: react-native-audio-recorder-player or expo-av
- **Speech-to-Text**:
- iOS: Native Speech Framework
- Android: Google Speech-to-Text API
- Or: Cloud service (Google Cloud Speech-to-Text, AWS Transcribe)
- **Similarity Analysis**:
- Embeddings: OpenAI API, Sentence Transformers, or local model
- Similarity calculation: Cosine similarity
- **Backend (if needed)**: Node.js/Express or Firebase for cloud features
### Step 1.2: Initialize Project
- [ ] Create React Native project structure
- [ ] Set up development environment (iOS Simulator, Android Emulator)
- [ ] Configure build tools and dependencies
- [ ] Set up version control (Git)
- [ ] Create folder structure:
```
/src
/components
/screens
/services
/store
/utils
/database
/models
```
### Step 1.3: Database Schema Design
- [ ] Design database schema:
- **Interests Table**: id, name, created_at, user_id
- **Ideas Table**: id, text, transcription, audio_file_path, created_at, user_id
- **IdeaLikes Table**: id, idea_id, created_at
- **SimilarityScores Table**: id, idea_id_1, idea_id_2, similarity_score, analysis_date
- **UserProfile Table**: id, themes, interests_history, created_at, updated_at
---
## Phase 2: Core Data Layer
### Step 2.1: Database Setup
- [ ] Install database library (SQLite/Realm)
- [ ] Create database connection service
- [ ] Implement database initialization
- [ ] Create migration system for schema updates
- [ ] Write database helper functions (CRUD operations)
### Step 2.2: Data Models
- [ ] Create Interest model
- [ ] Create Idea model
- [ ] Create SimilarityScore model
- [ ] Create UserProfile model
- [ ] Implement model validation
---
## Phase 3: Interest Setup Feature
### Step 3.1: Interest Setup UI
- [ ] Create onboarding screen for interest setup
- [ ] Design input interface (text input or selection)
- [ ] Add validation (3-7 interests required)
- [ ] Implement interest tags/chips UI
- [ ] Add ability to add/remove interests
- [ ] Create "Get Started" button
### Step 3.2: Interest Storage
- [ ] Save interests to database
- [ ] Implement interest retrieval
- [ ] Add interest update functionality
- [ ] Create interest management screen (for later editing)
---
## Phase 4: Voice Idea Capture
### Step 4.1: Voice Recording Setup
- [ ] Install and configure audio recording library
- [ ] Request microphone permissions (iOS & Android)
- [ ] Test recording functionality
- [ ] Implement recording state management (idle, recording, processing)
### Step 4.2: Recording UI
- [ ] Create main idea capture screen
- [ ] Design large, prominent record button
- [ ] Add visual feedback during recording (waveform, timer)
- [ ] Implement stop recording button
- [ ] Add cancel/retry functionality
### Step 4.3: Speech-to-Text Integration
- [ ] Integrate speech-to-text service
- [ ] Implement transcription on recording stop
- [ ] Add loading state during transcription
- [ ] Handle transcription errors
- [ ] Display transcribed text for user confirmation/edit
### Step 4.4: Idea Storage
- [ ] Save transcribed idea to database
- [ ] Store audio file path (optional: keep audio for later)
- [ ] Add timestamp to idea
- [ ] Link idea to user
- [ ] Implement idea retrieval
---
## Phase 5: Idea Database & List View
### Step 5.1: Idea List Screen
- [ ] Create ideas list screen
- [ ] Design list item component (text, date, like button)
- [ ] Implement list rendering with FlatList/ScrollView
- [ ] Add pull-to-refresh functionality
- [ ] Implement sorting (newest first, oldest first)
### Step 5.2: Idea Details
- [ ] Create idea detail view
- [ ] Display full idea text
- [ ] Show creation date/time
- [ ] Add edit functionality (optional for MVP)
- [ ] Add delete functionality
### Step 5.3: Navigation
- [ ] Set up navigation between screens
- [ ] Add bottom tab navigation or drawer
- [ ] Implement navigation from list to detail view
---
## Phase 6: Similarity Analysis Engine
### Step 6.1: Embedding Generation
- [ ] Choose embedding service (OpenAI, local model, or cloud)
- [ ] Implement embedding generation for ideas
- [ ] Cache embeddings in database
- [ ] Handle API rate limits and errors
### Step 6.2: Similarity Calculation
- [ ] Implement cosine similarity calculation
- [ ] Create function to compare two idea embeddings
- [ ] Batch process all idea pairs
- [ ] Store similarity scores in database
- [ ] Set similarity threshold (e.g., 0.7+ for "similar")
### Step 6.3: Repetition Detection
- [ ] Track idea creation timestamps
- [ ] Identify ideas with high similarity scores
- [ ] Flag ideas that appear multiple times over time
- [ ] Create "recurring ideas" list
### Step 6.4: Combination Detection
- [ ] Analyze high-similarity idea pairs
- [ ] Identify complementary ideas (different but related)
- [ ] Create "idea combinations" suggestions
- [ ] Store combination suggestions
### Step 6.5: Interest Matching
- [ ] Generate embeddings for user interests
- [ ] Compare each idea embedding with interest embeddings
- [ ] Calculate interest relevance scores
- [ ] Store interest-idea connections
---
## Phase 7: Weekly Analysis & Highlighting
### Step 7.1: Analysis Scheduler
- [ ] Implement weekly analysis trigger
- [ ] Add manual "Analyze Now" option
- [ ] Create background job or scheduled task
- [ ] Track last analysis date
### Step 7.2: Analysis Execution
- [ ] Run similarity analysis on all ideas
- [ ] Identify recurring ideas
- [ ] Find idea combinations
- [ ] Calculate interest matches
- [ ] Generate analysis results
### Step 7.3: Highlighted Ideas UI
- [ ] Create "Highlights" or "Insights" screen
- [ ] Display recurring ideas section
- [ ] Display idea combinations section
- [ ] Show interest-matched ideas
- [ ] Add visual indicators (badges, colors) for highlights
### Step 7.4: Like Functionality
- [ ] Add like button to idea items
- [ ] Implement like/unlike toggle
- [ ] Store likes in database
- [ ] Display like count
- [ ] Create "Liked Ideas" view
---
## Phase 8: Basic Profile
### Step 8.1: Profile Data Collection
- [ ] Track idea themes (extract from idea text)
- [ ] Monitor interest changes over time
- [ ] Count ideas per interest
- [ ] Track liked ideas patterns
### Step 8.2: Profile Screen
- [ ] Create profile screen
- [ ] Display main themes (top 3-5)
- [ ] Show interest distribution chart/graph
- [ ] Display total ideas count
- [ ] Show liked ideas count
- [ ] Add basic statistics (ideas per week, etc.)
### Step 8.3: Profile Updates
- [ ] Implement profile recalculation on new ideas
- [ ] Update profile after analysis runs
- [ ] Cache profile data for performance
---
## Phase 9: UI/UX Polish
### Step 9.1: Design System
- [ ] Define color palette
- [ ] Choose typography
- [ ] Create reusable component library
- [ ] Design consistent spacing and layout
### Step 9.2: Animations & Transitions
- [ ] Add smooth screen transitions
- [ ] Implement loading states
- [ ] Add success/error feedback
- [ ] Create micro-interactions
### Step 9.3: Accessibility
- [ ] Add screen reader support
- [ ] Ensure proper contrast ratios
- [ ] Test with accessibility tools
- [ ] Add keyboard navigation support
---
## Phase 10: Testing & Quality Assurance
### Step 10.1: Unit Testing
- [ ] Write tests for database operations
- [ ] Test similarity calculation functions
- [ ] Test embedding generation
- [ ] Test data models
### Step 10.2: Integration Testing
- [ ] Test voice recording flow
- [ ] Test speech-to-text integration
- [ ] Test analysis pipeline
- [ ] Test data persistence
### Step 10.3: Manual Testing
- [ ] Test on iOS device/simulator
- [ ] Test on Android device/emulator
- [ ] Test with various idea lengths
- [ ] Test with multiple interests
- [ ] Test weekly analysis trigger
- [ ] Test edge cases (no ideas, single idea, etc.)
### Step 10.4: Performance Testing
- [ ] Test with large number of ideas (100+)
- [ ] Optimize similarity calculation performance
- [ ] Test app startup time
- [ ] Monitor memory usage
---
## Phase 11: Deployment Preparation
### Step 11.1: App Configuration
- [ ] Configure app icons and splash screens
- [ ] Set up app metadata (name, description)
- [ ] Configure app permissions
- [ ] Set up app signing (iOS & Android)
### Step 11.2: Build & Distribution
- [ ] Set up iOS build configuration
- [ ] Set up Android build configuration
- [ ] Create production builds
- [ ] Test production builds on devices
- [ ] Prepare for App Store submission (iOS)
- [ ] Prepare for Google Play submission (Android)
---
## Technical Considerations
### Performance Optimization
- Batch similarity calculations to avoid blocking UI
- Cache embeddings to reduce API calls
- Use background processing for analysis
- Implement pagination for idea lists
### Error Handling
- Handle network errors gracefully
- Provide fallback for speech-to-text failures
- Handle database errors
- Add retry mechanisms for API calls
### Security & Privacy
- Encrypt sensitive data at rest
- Secure API keys (use environment variables)
- Implement user data privacy controls
- Comply with data protection regulations
### Scalability
- Design database schema for future growth
- Plan for cloud sync (Phase 2)
- Consider API rate limits
- Optimize for large datasets
---
## Dependencies & Services
### Required Services
- Speech-to-Text API (Google Cloud, AWS, or native)
- Embedding API (OpenAI, or local model)
- (Optional) Cloud storage for audio files
### Key Libraries
- React Native core
- Navigation library (React Navigation)
- Audio recording library
- Database library (SQLite/Realm)
- HTTP client (Axios/Fetch)
- Date/time utilities
---
## Success Criteria
The MVP is complete when:
- [ ] Users can set up 3-7 interests
- [ ] Users can record ideas by voice and see transcriptions
- [ ] Ideas are stored and displayed in a list
- [ ] Weekly analysis identifies similar and recurring ideas
- [ ] Users can like ideas
- [ ] Basic profile shows themes and statistics
- [ ] App works on both iOS and Android
- [ ] Core features are stable and tested
---
## Next Steps After MVP
Phase 2 features (not in MVP):
- AI-assisted planning
- Advanced analytics
- Cloud sync
- Collaboration features
- Export functionality
- Advanced profile insights
---
## Notes
- Start with iOS or Android first, then port to the other platform
- Consider using Expo for faster development and easier deployment
- Keep MVP scope minimal - focus on core value proposition
- Iterate based on user feedback before adding Phase 2 features
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment