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High quality customer interviews are a superpower for figuring out which features to build and which to kill. I've conducted hundreds over the years, working toward product-market fit.

tl;dr When you ask the right questions, body language tells you what matters most. Transcripts tell you the rest.

Here's a complete LLM prompt framework to get started, created from my real-world usage, including the exact interview script I follow.

https://github.com/shawnyeager/interview-analysis

The bare-bones MVP is that you clone this repo, point your LLM at a directory of transcripts, and tell it to go.


Next level: build a lightweight version of this, but on freedom tech.

https://www.aha.io/discovery/overview

Potential components:

  • Soapbox Shakespeare
  • jitsi or WebRTC for video
  • blossom for video storage (encrypted?)
  • routstr or Maple AI for post-interview transcription and—most importantly—patterns and insights from a campaign of interviews