How to actually deploy machine learning without breaking the stack

A blueprint to stop losing customer insights in disconnected Google Docs and Slack threads.

The exact handoff sequence to turn a 45-minute user interview into actionable product requirements in minutes.

A method to automate video capture and transcription without interrupting the conversation flow.

The architecture for a self-updating, searchable research repository.

A custom prompting strategy to force ChatGPT to synthesize patterns across dozens of distinct interviews.

Capture is solved, synthesis is not: Recording calls is easy, but extracting patterns across twenty different user interviews remains a manual bottleneck for most product and consulting teams.

Integration over isolation: This stack connects frictionless capture (Fathom) with structural storage (Dovetail) and macro-analysis (ChatGPT).

Eliminate manual tagging: By defining a strict taxonomy and using AI to pre-sort data, operators can bypass hours of manual spreadsheet work.

Speed to insight: Moving from raw conversation to categorized product brief takes minutes instead of days, accelerating the feedback loop between customers and builders.