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Description
🎯 Business Outcome
Brief Description: Reduce time spent in refinement by developing a Refinement Agent Team that ensures Jira tickets are properly refined in a timely fashion through AI automation.
📊 Success Metrics
- Reduce average refinement time from X hours to Y hours per ticket
- Achieve 90% ticket readiness for cold-start execution by engineering
- Decrease refinement meeting duration by 50%
- Improve engineering velocity by 25% through better-prepared tickets
🎨 Scope & Context
Problem Statement: Engineering teams spend excessive time in refinement meetings due to poorly prepared tickets that lack necessary context, detailed breakdowns, and clear acceptance criteria.
User Impact: Engineering teams can start work immediately with well-refined tickets that include all necessary context from existing RFEs, code, and architectural documents.
Strategic Alignment: This evolutionary change fits within existing agile frameworks while dramatically improving engineering productivity and reducing time-to-market.
🗺️ Related Epics
This outcome will be delivered through the following epics:
- Epic: RAT Architecture & Design - System design and architectural decisions
- Epic: Data Source Integration - Connect to RFEs, code repos, ADRs
- Epic: AI Agent Development - Build specialized refinement agents
- Epic: Jira Integration & Workflow - Integrate with existing Jira processes
- Epic: Testing & Validation - Ensure system reliability and effectiveness
✅ Definition of Done
- All epics under this outcome are completed
- Success metrics are achieved and validated through A/B testing
- User acceptance testing passed with engineering teams
- Documentation and training materials created
- Stakeholder sign-off from engineering leadership
📝 Notes
This is an evolutionary improvement that works within existing agile processes. The system will coalesce information from multiple data sources to generate detailed feature breakdowns with all necessary attributes for immediate engineering execution.