AI

I was – and I still am – a cynic when it comes to how AI will affect software development (whole “it’s an amplifier” argument + unchanged incentives). Still, after finding a flow which fits my brain, I cannot imagine working without it. Doing TDD when “devopsing” is hard, so the default observed in the wild was “get it right and pray we do not need to touch it” most of the time. Which often meant that Infrastructure-As-Code made things simpler, but reproducibility was not something you really wanted to depend on. ...

There is a huge problem I have not seen discussed in the context of AI. Documentation—just like code—can rot when subjected to unrestricted AI use, and this is not something that can be easily, if at all, fixed. Missing, misleading or outdated documentation forces rushed explorations focused on how, not why—which tightens competition for resources between research, design, and implementation. Good documentation warns about dead ends and explains constraints, allowing teams to reach better decisions faster. Yet, having a good knowledge base was hard before AI, and I’m convinced that it will get even harder with it. ...

I’m in a bind. On the one hand, I’m a big proponent of passive, boring investing—on the other, this approach taken to the logical conclusion of sitting on my hands steers me toward extreme over-exposure to AI. The main issue is that if you try to have low-maintenance exposure to the global stock market, ~60%+ of your ETF(s) exposure will be toward the USA. Then, ~30%+ of it will be the Magnificent Seven (Nvidia, Alphabet, Apple, Microsoft, Amazon, Meta, and Tesla). Which is a pretty sizable bet, all of which can be considered an AI play. ...