Insight Pipeline & Repository (AI-assist)
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.
145 minutes29 lessons
Lessons
1
What is an insight pipeline?
2
How to capture research insights during user sessions
3
How to assign note taking roles for user interviews
4
How to use AI transcription without losing accuracy
5
How to use reusable session templates
7
How to build a tagging taxonomy for user research
8
How to avoid over tagging in your note system
9
How to use AI assisted tagging effectively
10
How to link evidence to every insight
11
How to handle sensitive user data safely
12
How to normalize metadata for search
13
Quality checks for raw notes
14
How to run affinity mapping without the mess
15
How to name themes in plain language
16
How to deal with contradictions and outliers in research
17
triangulation for higher confidence insights
18
How to write compelling one paragraph insights
19
How to score the strength of an insight
20
Do not jump into mapping yet
21
How to design a simple repository structure
22
Specialized tool or general workspace
23
How to backfill legacy research fast
24
How to create effective saved searches
25
How to share findings with short digests
26
How to keep your repository clean
27
Access control and privacy basics
28
How to use AI summaries with human review
29
How to build a reusable clip library
30
How to onboard new teammates with a repo tour
Part of Product Discovery
Master product discovery: methods, cadence, and opportunity mapping that turn insights into action.
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