Measuring talking time with LLMs

I record my conversations these days, mainly for LLM use. I use them in 3 ways:

  1. Summarize what I learned and the next steps.
  2. Ideate as raw material for my Ideator tool: /blog/llms-as-idea-connection-machines/
  3. Analyze my transcript statistics.

For example, I learned that:

  • When I’m interviewing, others ramble (speak long per turn), I am brief (less words/turn) and quiet (lower voice share). In one interview, I spoke ~30 words per turn. Others spoke ~120. My share was ~10%.
  • When I’m advising or demo-ing, I ramble. I spoke ~120 words per turn in an advice call, and took ~75% of the talk-time.
  • This pattern is independent of meeting length and group size.

I used Codex CLI (command-line tool) for this, with the prompt:

Go through the transcripts in this folder and estimate the % of time Anand was speaking vs others, by conversation.

Then I prompted for correlations and interpretations. This combines three things I find powerful:

  1. LLMs writing & running code
  2. LLMs interpreting the results
  3. Running on local data in my machine

LLMs working on local docs (not data) is new to me. I plan to do much more with it.