SKILL

Workflow Post Launch Learning

Run the Post-Launch Learning workflow (instrumentation -> dashboard -> results -> retro -> lessons)

Published by @product-on-purpose·0 agent reads / 30d·0 saves·

Run the Post-Launch Learning workflow to set up measurement, evaluate results, and capture learnings after a feature ships.

This workflow uses multiple skills in sequence. For each step, read the skill instructions and follow them to create the artifact.

Workflow Steps

Step 1: Instrumentation Spec

Use the measure-instrumentation-spec skill from skills/measure-instrumentation-spec/SKILL.md.

Define event tracking and analytics instrumentation requirements for the shipped feature.

Step 2: Dashboard Requirements

Use the measure-dashboard-requirements skill from skills/measure-dashboard-requirements/SKILL.md.

Specify the analytics dashboard including metrics, visualizations, and data sources.

Step 3: Experiment Results

Use the measure-experiment-results skill from skills/measure-experiment-results/SKILL.md.

Document the results of the feature launch with analysis and recommendations.

Step 4: Retrospective

Use the iterate-retrospective skill from skills/iterate-retrospective/SKILL.md.

Facilitate a team retrospective covering the full feature lifecycle.

Step 5: Lessons Log

Use the iterate-lessons-log skill from skills/iterate-lessons-log/SKILL.md.

Distill retrospective findings into durable lessons for organizational memory.

Output

Create all five artifacts in sequence. Steps 1-2 should happen at or before launch; Steps 3-5 after data accumulates.

Reference the Post-Launch Learning workflow at _workflows/post-launch-learning.md for additional guidance.

Context from user: $ARGUMENTS

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