Insight Pipeline & Repository (AI-assist)

Context and why it matters in 2026

Build a clean insight pipeline from capture to synthesis, then store findings in a simple, searchable repository. Keep methods light, evidence grounded, and use AI for speed where it helps. No heavy frameworks, just practices your team can repeat every week.

In modern product teams, progress depends on clear playbooks and measurable outcomes. This module gives you practical steps you can apply immediately while keeping alignment with the broader Product Discovery curriculum.

Step-by-step playbook

1. Step 1: What is an insight pipeline?
2. Step 2: How to capture research insights during user sessions
3. Step 3: How to assign note taking roles for user interviews
4. Step 4: How to use AI transcription without losing accuracy
5. Step 5: How to use reusable session templates
6. Step 6: How to build a tagging taxonomy for user research

Templates and examples

• What is an insight pipeline?
• How to capture research insights during user sessions
• How to assign note taking roles for user interviews
• How to use AI transcription without losing accuracy
• How to use reusable session templates
• How to build a tagging taxonomy for user research

If you are working on AI-enabled workflows, review the glossary terms Prompt library and Reflection loop for reusable implementation patterns.

Metrics to track

• Module completion rate from first to last lesson.
• Lesson-to-lesson progression drop-off points.
• Time to complete versus the estimated 145 minutes.
• Retention into the next module and downstream lesson activity.

FAQ