ai-automation 5

At The Curzon Hotel, my key card didn’t work. But every time I went to the reception, they’d send a bellboy who would use the same key card, jiggle it a bit, pull it in and out a few times, and the door would open. Every night. For five nights. I just couldn’t get the knack of it. I’ve been at the other end of this. People often reach out to me saying, “Anand, this software isn’t working.” Then I go do the same thing they did, and it works. (Sometimes, I just need to watch them do it and it works.) ...

When AI does the entry-level work, what you should learn depends on what it costs to be wrong. AI is replacing entry-level roles, especially technical ones. In the US, Stanford found that since late 2022, employment in AI-exposed jobs like software and customer support fell 16% relatively for 22-25 year-olds. Employment for older workers in the same jobs stayed steady. Matt Beane at UCSB saw this happen in robotic surgery even before AI. Surgeons used to train the next batch of residents. But robotic consoles let surgeons do what residents did earlier, so they stopped bothering with residents. ...

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. ...

Slides for my DataHack Summit talk (controversially) titled RIP Data Scientists are at https://sanand0.github.io/talks/2025-08-21-rip-data-scientists/ Summary: as data scientists we explore, clean, model, explain, deploy, and anonymize datasets. I live-vibe-coded each step with DGCA data in 35 minutes using ChatGPT. Of course, it’s the tasks that are dying, not the role. Data scientists will leverage AI, differentiate on other skills, and move on. But the highlight was an audience comment: “I’m no data scientist. I’m a domain person. I’ll tell you all this: If you don’t follow these practices, you won’t have a job with me!” ...

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