Product / Feature Name: TaskBuddy – AI Task Assistant Date: 03/10/2025 Author: Avi Levi Version: 1.0
1. 📝 Overview / Purpose
TaskBuddy is a mobile productivity app that helps users organize tasks intelligently using an AI assistant. The app provides smart suggestions, schedules tasks automatically, and tracks daily progress.
Problem: Many users struggle to prioritize and stick to daily plans, leading to low productivity. Why now: With the rise of AI adoption in daily tools, there’s an opportunity to deliver a personal “productivity coach” experience in a lightweight app.
2. 🎯 Goals & Objectives
- Primary Goals:
- Help users complete at least 80% of their daily planned tasks.
- Increase daily app engagement (DAU) by 30% within 3 months.
- Secondary Goals:
- Gather anonymized behavioral data to improve AI task recommendations.
- Offer integration with Google Calendar and Notion.
- KPIs:
- Task completion rate
- Daily Active Users (DAU)
- Retention after 30 days
- Number of AI-generated suggestions accepted
3. 👥 Target Users / Personas
- Primary:
- Knowledge workers, freelancers, and students aged 20–40 who use their phones to manage daily life.
- Secondary:
- Professionals looking for a “second brain” assistant for productivity.
Key Pain Points:
- Overwhelmed by long task lists
- Poor prioritization
- Forgetting commitments and deadlines
4. 🌍 Scope
In Scope:
- Mobile app (iOS + Android)
- Task creation, editing, and prioritization
- AI-based task suggestions and scheduling
- Push notifications and reminders
- Basic analytics dashboard for users
Out of Scope (for MVP):
- Desktop version
- Collaboration / team features
- Voice assistant integration
5. 🧭 User Stories / Use Cases
Main User Stories:
- “As a user, I want to create a task quickly so I can capture my thoughts on the go.”
- “As a user, I want the app to suggest when to do each task so I don’t have to plan manually.”
- “As a user, I want to see my daily progress so I stay motivated.”
Edge Cases:
- No internet connection → local task storage
- Conflicting AI suggestions → user override options
- Overdue tasks → carry over with smart rescheduling
6. 🧠 Functional Requirements
- Task CRUD (Create, Read, Update, Delete)
- AI scheduling engine that analyzes:
- Task priority
- User habits
- Calendar availability
- Notifications engine for reminders and nudges
- Offline mode for basic task usage
- Secure user authentication (OAuth2 / Email-Password)
7. 🧩 Non-Functional Requirements
- Performance: Tasks should sync in <2 seconds.
- Security: All data encrypted (AES-256).
- Accessibility: WCAG 2.1 AA compliance.
- Scalability: Support up to 100K daily active users without degradation.
- Reliability: 99.5% uptime for backend services.
8. 🖼️ UX / UI References
- Clean, minimalist UI inspired by Apple Reminders and Notion.
- Dark and light mode.
- Sample wireframes: Figma link – Demo
- Interaction pattern: swipe to mark complete, tap to edit.
9. 🔄 Dependencies & Assumptions
- Dependencies:
- OpenAI API for task suggestions
- Firebase for backend, notifications, and authentication
- Google Calendar API for integration
- Assumptions:
- Users have basic familiarity with to-do list apps.
- AI suggestions are supplementary, not mandatory.
10. 🧭 Timeline / Milestones
| Milestone | Description | Target Date |
|---|---|---|
| ✅ MVP Definition | Core features, no integrations | Nov 2025 |
| 🧪 Beta Launch | Closed beta with 500 users | Jan 2026 |
| 🚀 Public Launch | App Store & Play Store | Mar 2026 |
11. 📏 Metrics & Success Criteria
- 80% task completion rate for active users
- 25%+ 30-day retention
- 50% of daily users interact with AI suggestions
- 4.5★+ rating on App Stores within 3 months
12. ⚠️ Open Questions & Risks
Open Questions:
- Should AI suggestions run locally or via cloud only?
- How to handle multilingual users at launch?
Risks:
- Over-reliance on third-party APIs (e.g., outages)
- Mitigation: Fallback to local scheduling.
- Privacy concerns around AI data processing
- Mitigation: Clear consent flow and anonymization.
13. ✍️ Approvals & Stakeholders
| Role | Name | Approval |
|---|---|---|
| Product | Avi Levi | ✅ |
| Design | Dana Cohen | ⏳ |
| Engineering | Amir Shalev | ⏳ |
| Legal | Yael Ben-David | ⏳ |
14. 📚 Appendix
- Competitive research: Todoist, Motion, Notion AI
- Market analysis reports (Q2 2025)
- Technical architecture diagram (link)