Project Management

Sprint Retrospectives

AI-facilitated sprint retrospectives with automated action item tracking and sentiment analysis.

Claude Code Cursor Copilot

Overview

Sprint retrospectives are essential for continuous improvement, and AI agents can enhance the process by analyzing sprint data, facilitating structured feedback, and tracking action items across sprints.

Agents can generate retrospective summaries from git history, PR reviews, and issue trackers. They identify patterns in team velocity, common blockers, and recurring issues. This data-driven approach complements traditional retrospective formats like Start-Stop-Continue or Mad-Sad-Glad.

Action items from retrospectives can be automatically converted into trackable issues, with the agent monitoring progress in subsequent sprints. This closes the feedback loop and ensures retrospective insights translate into concrete improvements.

Who Is This For?

Generate sprint summaries from git and issue data
Track retrospective action items across sprints
Identify recurring blockers and patterns
Create structured retrospective documents from team input

Installation

Setup for Claude Code

Create a retros/ directory in your project for retrospective data

Configuration

// retro-template.json
{
  "sprint": "Sprint 24",
  "date": "2026-03-07",
  "format": "start-stop-continue",
  "sections": {
    "start": [],
    "stop": [],
    "continue": []
  },
  "action_items": []
}