I shared a photo of my right hand with popular AI agents and asked for a detailed palmistry reading. Apply all the principles of palmistry and read my hand. Be exhaustive and cross-check against the different schools of palmistry. Tell me what they consistently agree on and what they are differing on. I was more interested in how much they agree with each other than with reality. So I shared all three readings and asked Claude: ...
As AI marches along, another role at risk is the data engineer / database administrator. (Data scientists are already feeling the heat.) A common task for data engineers is to analyze SQL queries - to optimize and standardize. Pavan used Antigravity to analyze 1,500 SQL queries and found: 30% of queries are purely headcount / volume related. Much more than revenue (25%) or engagement (15%). That’s sign of a tactical culture. 70% of the queries are about What happened yesterday? rather than What will happen tomorrow? - again, tactical culture. Here’s the analysis. ...
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. ...