**Product / Feature Name:** TaskBuddy – AI Task Assistant  
**Date:** 03/10/2025  
**Author:** Avi Levi  
**Version:** 1.0  

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## 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.

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## 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

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## 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

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## 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

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## 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

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## 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)

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## 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.

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## 8. 🖼️ UX / UI References
- Clean, minimalist UI inspired by Apple Reminders and Notion.  
- Dark and light mode.  
- Sample wireframes: [Figma link – Demo](https://www.figma.com/)  
- Interaction pattern: swipe to mark complete, tap to edit.

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## 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.

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## 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 |

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## 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

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## 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.

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## 13. ✍️ Approvals & Stakeholders
| Role | Name | Approval |
|------|------|----------|
| Product | Avi Levi | ✅ |
| Design | Dana Cohen | ⏳ |
| Engineering | Amir Shalev | ⏳ |
| Legal | Yael Ben-David | ⏳ |

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## 14. 📚 Appendix
- Competitive research: Todoist, Motion, Notion AI  
- Market analysis reports (Q2 2025)  
- Technical architecture diagram (link)