self-analysis 4

Instead of learning and applying new Codex features, I asked it to analyze my sessions and tell me what I’m under-using. I'd like you to analyze my Codex sessions and help me use Codex better. sessions/ has all my past Codex sessions. Search online for the OpenAI Codex release notes for the latest features Codex has introduced and read them - from whatever source you find them. Then, create a comprehensive catalog of Codex features. Then, analyze my sessions and see which feature I could have used but didn't and make a comprehensive list. Then summarize which features I should be using more, how, what the benefits are, and with examples from my sessions. Document these in one or more Markdown files in this directory. Write scripts as required. Commit as you go. It did a thorough job of listing all the new features and analyzing my gaps. ...

I record my conversations these days, mainly for LLM use. I use them in 3 ways: Summarize what I learned and the next steps. Ideate as raw material for my Ideator tool: /blog/llms-as-idea-connection-machines/ 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: ...

ChatGPT can now search through your chats with the new memory feature. As an LLM Psychologist, I research how LLMs think. Could LLMs research how I think? I asked three models: Based on everything you know about me, simulate a group chat between some people who are debating whether or not to add me to the group, by talking about my personality flaws The models nailed it! Here are 12 flaws they found. ...

Microsoft ported its PowerPoint Speaker Coach to Teams. Since September, it’s given me suggestions covering 11 hours in 77 calls (I speak ~10 min/call.) I say “uhh” a lot. That’s intentional I use the filler word “uhh” in 70% of my calls. That did not surprise me. I do that intentionally. On a poor network, they know I’m still connected They know I’m going to say something I sound less confident. That invites critique I can learn from But I also use filler words like “You know” and “I mean” in half the calls, and “like”, “actually”, and “basically” in a fifth. That’s NOT intentional, and I’ll be conscious. ...