AI Backlog Generator for Product Teams
Turn product context and objectives into INVEST-ready, JIRA-syncable user stories with AI, market research, and prioritization.
Product Managers often struggle to balance competing demands from sales, engineering, and users. BackLogAI enforces a disciplined approach to backlog creation by combining context-driven inputs, market research, AI drafting, and INVEST validation. It ensures every story aligns with strategic business goals before it ever hits your JIRA board.
ai backlog management, jira story generator, product management ai, invest user stories, kotlin multiplatform, fastapi, market research automation, backlog prioritization, moscow prioritization, serpapi
Every backlog item generated by this system answers three critical questions:
- Why now? (Urgency) ⏰
- Why this? (Value) 💎
- Why us? (Strategic Fit) 🎯
BackLogAI prioritizes features based on a weighted score across five dimensions:
| Pillar | Focus | Key Question |
|---|---|---|
| 1. User Value | ❤️ Solving Pain Points | "Will this feature actually be used and loved?" |
| 2. Commercial Impact | 💰 Revenue & Deals | "Does this help close deals or reduce churn this quarter?" |
| 3. Strategic Horizon | 🔭 Future Demand | "Are we building for the market of 2027, or reacting to 2026?" |
| 4. Competitive Positioning | ⚔️ Market Differentiation | "Is this a catch-up feature or a differentiator?" |
| 5. Technical Reality | 🛠️ Feasibility & Debt | "Is the technical 'price tag' worth the business value?" |
graph LR
A[Context + Objective] --> B[Market Research]
B --> C[Story Generation v2]
C --> D[INVEST Validation]
D -->|Warnings| C
D --> E[Prioritization]
E --> F[JIRA Sync]
style A fill:#f9f,stroke:#333,stroke-width:2px
style C fill:#bbf,stroke:#333,stroke-width:2px
style F fill:#bfb,stroke:#333,stroke-width:2px
- Input: User provides context + objective and optional signals (persona, segment, constraints, metrics, competitors).
- Process:
- Research: SerpAPI pulls relevant market and competitor signals (cached + rate-limited).
- Generation: AI drafts stories (
As a... I want... So that...) withGiven/When/Thenacceptance criteria. - Validation: INVEST checks produce warnings and a quality score, with an optional revision pass.
- Scoring: Computes priority score + MoSCoW classification.
- Output:
- JIRA-ready description with research summary, NFRs, metrics, risks, and rollout plan.
- Direct sync to JIRA.
- Cross-platform UI (Android + iOS implemented).
To run BackLogAI effectively, you need to configure external services in your .env file.
- Sign up/Login: OpenAI Platform
- Create Key: Go to API Keys -> Create new secret key.
- Set Env:
OPENAI_API_KEY=sk-... - Note: If you have issues logging in, try accessing platform.openai.com directly instead of auth subdomains.
- Sign up: SerpAPI
- Free tier: 250 searches/month
- Set Env:
SERPAPI_API_KEY=...
- URL: Your Atlassian domain (e.g.,
https://your-domain.atlassian.net). - Username: Your Atlassian email address.
- API Token: Go to Atlassian Security -> Create API token.
- Set Env:
JIRA_URL=https://your-domain.atlassian.net JIRA_USERNAME=your.email@example.com JIRA_API_TOKEN=your_api_token JIRA_PROJECT_KEY=KAN
See ARCHITECTURE.md for detailed system design.
| Layer | Stack |
|---|---|
| Backend API | Python 3.11+, FastAPI, Uvicorn |
| AI & Research | OpenAI API, SerpAPI (market search) |
| Backlog Logic | INVEST quality checks, MoSCoW prioritization, story decomposition |
| Integrations | Jira REST API, SMTP-compatible notification workflow |
| Client Apps | Kotlin Multiplatform + Compose (Android, iOS, macOS Desktop) |
| Build & Delivery | Gradle, Docker, GitHub |
See IMPLEMENTATION_PLAN.md for the phased development plan.
This project is licensed under the MIT License - see the LICENSE file for details.