Category: Thoughts

A few days ago I was reading a fascinating essay by David Bessis that made me think deeply about something we all take for granted: intelligence. Bessis, a mathematician and author of Mathematica: A Secret World of Intuition and Curiosity, presents a thesis that challenges many of our deeply held beliefs about the origin of cognitive differences between people.

What’s most interesting about his approach is not so much the conclusion -which I’ll get to- but the path he traces to get there, a path that mixes mathematics, neuroscience, and a good dose of personal experience.

A few days ago I watched a video that has given me a lot to think about. Jeffrey Way, founder of Laracasts and one of the most influential people in the Laravel/PHP community, shared a brutally honest reflection on how artificial intelligence is transforming his business and his profession.

The video starts with a phrase that leaves you cold: “I’m done”. It’s not a goodbye to programming, but an acceptance of the reality to come.

A few days ago I discovered Tangible Media Collection, a website that has resonated deeply with me. It’s a collection of some 1700 objects related to information storage: from vinyl records and magnetic tapes to punch cards and optical discs. But it’s not just a collection of technological objects; it’s a testament to human curiosity.

The Collection Born from a Lost Tape

The story of how this collection started is fascinating. In 2001, John Wallace (the collector) found a computer tape from the late 80s in a desk drawer. He knew what it contained: an archive of computer-generated images from his grad school days, the product of late nights and weekends in the computer lab. But the tape drive that could read it was long gone.

A necessary reflection on the “AI-Native Engineer”

I read Addyo’s article about the “AI-Native Software Engineer” and, as a Principal Backend Engineer who has seen technological promises come and go for years, I have quite sincere opinions about it. Not all are comfortable to hear.

I’ve seen enough “revolutions” to separate the wheat from the chaff. And there’s a lot of both here.

What’s really working (honestly)

1. AI as copilot, not as pilot

The article’s metaphor about treating AI as a “junior programmer available 24/7” is accurate. In my experience working with teams, I’ve seen developers use GitHub Copilot and Claude effectively to: