AI-Assisted Sprint Planning Prompt

A structured prompt for using AI to prepare sprint planning artifacts — story analysis, sprint goal candidates, capacity model, and risk identification — before the human planning conversation begins.

Syntax

scrum-master-ai

Sprint [N] Planning Preparation

Team context:
- Team size: [n developers]
- Sprint duration: [2 weeks]
- Upcoming PTO/absences: [list]
- Historical velocity by story type: [AI-heavy: X, mixed: Y, human-primary: Z]
- Previous sprint velocity: [n points]

Backlog items for consideration:
[Paste story titles and rough descriptions]

Please provide:
1. Flag any stories with ambiguous acceptance criteria
2. Identify dependency risks between stories
3. Suggest AI-appropriate vs. human-primary classification for each story
4. Draft 3 candidate sprint goals
5. Recommended commitment range given capacity and story mix
6. Top 2 risks this sprint

Example

scrum-master-ai

// Sample output excerpt:

ambiguousStories: [
  {
    story: "Improve checkout performance",
    issue: "No definition of performance target — improve by how much? Measured how?",
    suggestion: "Add: reduce checkout page load time to <2s on 3G connection, measured by Core Web Vitals LCP"
  }
]

agentSuitability: {
  "User authentication token refresh": "AI-heavy — well-specified, bounded, testable",
  "Redesign onboarding flow": "Human-primary — requires UX judgment and user empathy",
  "Add CSV export to reports": "Mixed — standard pattern but edge cases need human attention"
}

sprintGoalCandidates: [
  "Customers can complete checkout without performance delays on any connection",
  "The checkout pipeline is observable, measurable, and meeting our performance contract",
  "Performance debt in checkout is resolved and production-validated"
]