I take the point, but I think the author picked a poor analogy. Cooking even an excellent steak is actually not that hard. In fact, I'd argue that it's among the easiest things to master/make at a top level quality at home. Does it require some modicum of attention and understanding? Sure. But starting with a high quality cut, owning a meat-thermometer, and knowing about reverse searing is about all it takes to reliably and easily get a near perfect steak every time.
There are far, far better cooking examples out there.
I'm more of a coffee nerd than a steak aficionado but I've often made the comparison between those two. In both cases, the enthusiast considers their skill in making coffee/cooking steak to be a differentiator and they immerse themselves deeply into the process, skills, and tools. But for both coffee beans and steak the most important factor for a good end product is starting with high quality inputs. In other words, most of the work is being done by the farmers, the processors, and the quality of the raw stock (the cow or the coffee plant). Your job at the very end of that long value adding chain is to not ruin the hard work that others have put into it.
I'm not sure if this analogy holds up in the AI software metaphor that the author of the blog post is making.
I don't know if I agree with the take I've written below, but I think you can make the analogy work:
It has been argued, even in the before-AI-times, that most professional software is just gluing together open source tools and libraries. Your job isn't to write software, it's to set up redis and postgres and a programming language and a react frontend or whatever in a way that lets them do what they're there to do. Most modern programming is just configuration of pre-existing tools. It doesn't really matter how good your code is as long as it isn't terrible, Real Programmers already did 95% of the necessary work before you decided to build your little app.
MostlyStable · · focus · HN ↗
There are far, far better cooking examples out there.
MerrimanInd · · focus · HN ↗
I'm not sure if this analogy holds up in the AI software metaphor that the author of the blog post is making.
miyoji · · focus · HN ↗
It has been argued, even in the before-AI-times, that most professional software is just gluing together open source tools and libraries. Your job isn't to write software, it's to set up redis and postgres and a programming language and a react frontend or whatever in a way that lets them do what they're there to do. Most modern programming is just configuration of pre-existing tools. It doesn't really matter how good your code is as long as it isn't terrible, Real Programmers already did 95% of the necessary work before you decided to build your little app.