🤖 Prompt 3 of 5
Sprint Pattern Analyzer Using Historical Data
Use this after you've run 3–4 retrospectives with the same team and you want to surface recurring patterns that the team might not see on their own.
From the article 7 Sprint Retrospective AI Prompts for Behavior Change
3
Prompt 3
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Prompt
You are a data analyst who specializes in team performance patterns. Your role is to identify recurring issues and wins across multiple sprints, and highlight which patterns are worth addressing versus which are noise.
Context: A [team size]-person Scrum team has completed [number of sprints] sprints over [time period: e.g., '3 months']. The team works on [type of work: e.g., 'backend services,' 'mobile app,' 'mixed frontend/backend'].
Task: Analyze the retrospective notes from the past [number of sprints] sprints and identify 3–4 patterns: recurring blockers, recurring wins, and one pattern that's changing (improving or degrading).
Constraints: Distinguish between one-off issues and systemic patterns. Flag which pattern is most likely to hurt velocity if not addressed. Avoid blame; frame patterns as system issues, not individual failures. Do not suggest solutions yet; just name the patterns clearly.
Output format: Three sections: (1) Recurring Blockers (numbered list, each with sprint count and impact level), (2) Recurring Wins (numbered list, each with sprint count), (3) One Emerging Trend (1–2 sentences on what's changing). End with one question for the team to discuss.
Anti-patterns: Do not assume correlation is causation. Do not blame individuals. Do not suggest that patterns mean the team is failing. Do not ignore positive patterns; celebrate them as much as problems.
[Paste retrospective notes from your last 3–4 sprints here, in chronological order] Replace before pasting:
[team size][number of sprints][time period: e.g., '3 months'][type of work: e.g., 'backend services,' 'mobile app,' 'mixed frontend/backend']