alt Hacker NewsI'm this person, and I do find AI to be quite helpful, though I'm mostly just playing around at this point.
I'm the daughter and granddaughter of programmers, and I learned the basics of how to code as a kid. I'm good at it and have a knack for it, but I didn't want to do it for 8+ hours a day and then spend my nights on it as well, so I didn't pursue it as a career. I did an undergraduate degree in Linguistics, which has been really helpful for having an intuitive sense for what 'language as data' can accomplish and for a strong understanding of the difference between language as data and language as meaning. I studied formal logic systems. Then I did a graduate degree in Library Science and worked in libraries for a decade and a half.
I can organize and define systems very well, and I'm trained in how to wheedle information people don't consciously know out of them without them knowing I'm doing it. I've spent enough time around actual devs to understand where my limitations are and when to loop in someone who knows more to check my work, and when it's important for the work to be super accurate versus when I can learn by fucking around. (Front end and design? Fuck around! Database structure? Fuck around but with an exceptionally robust backup system kept outside of the AI tools' purview + don't fuck around in prod. Storing credentials and people's information? Ask someone.)
The problem companies are going to have is I'm very disinclined to work for them doing this, particularly if they want us because they think we're going to be cheaper. Most people who are in this category a.) could be devs and opted not to, and there's a reason for that and/or b.) are the children, cousins, etc. of programmers. We're not stupid: we know we're just as disposable as they're trying to make devs.
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Having descended from a humanities social background and blundered into professional programming rather incidentally, a lot of this resonates with me.
I've frequently been credited as a person who can really string all the disparate elements of tacit knowledge together into a unified fabric in our particular subdomain, and helped a lot of people plug Swiss cheese gaps in their knowledge that way and come away with the feeling that it's all been tied together theoretically.
However, it's not immediately obvious to me how, in our LLM psychosis cultural moment, this facility shoots to the top of the value chain.
> which has been really helpful for having an intuitive sense for what 'language as data' can accomplish and for a strong understanding of the difference between language as data and language as meaning.
100%. I think, intuitively, software developers understand that there's a strong connection here, but most fail to translate that into practice. It always amuses me when someone comments on the triviality of creating CRUD apps. Setting aside the fact that people usually get the mechanics of it wrong (despite it being a solved problem), they overlook the difficulty of producing a good information design.I've developed software in a variety of industries, and I would say maybe 5% of the designs I inherit are well-done and represent the concepts they're trying to model in an elegant, parsimonious way. Rather, most examples are replete with ambiguity, orthogonal concepts smashed together into single elements, and misleading naming and relationships.