>The not-so-quiet goal of the LLM push by big tech was to homogenise intellectual labour such that it can be made fungible. When labour is fungible you can swap it out whenever you like for an alternative, decreasing the bargaining power of workers. Software development was one of the last ‘guild fields’ and now we are seeing its industrialisation occur.

I think that the industrialization of software development already happened decades ago. The common professional software development methodologies, both waterfall and sprint-based, ARE the industrialization of software development. Isn't modern "agile", sprint-based software development methodology directly influenced by Japanese manufacturing methods? I don't know when software development actually was a guild field, and my personal experience doesn't reach back this far, but based on what I've read at least, it seems to me that even back in the 1990s it was already not a guild field.

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jerf a day ago | parent | next [-]

A "guild field" is not a well-defined matter, but I think it's still the easiest engineering field to sit at home on your personal gear and learn skills that can get you hired in a real job with a future without attending any professional school for the field.

In fact the four-year degree you'll get from school is getting increasingly distant from the skills I actually want out of a new grad. It's not impossible to bridge the gap or anything but my transition into the commercial realm in the early 2000s was a cakewalk compared to the sheer number of things I'm asking a new grad to learn as soon as they're settled in at their desk... source control, CI/CD, bug trackers, devops, and that's just the beginning of that list not the end.

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fwip a day ago | parent | next [-]

New grads have learnt git and issue trackers as part of standard coursework. Not sure about CI or devops.

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skydhash a day ago | parent | prev [-]

> In fact the four-year degree you'll get from school is getting increasingly distant from the skills I actually want out of a new grad

Those skills are easily taught. But in every run of the mill project I’ve been on, I’ve been really happy about all the maths and other science stuff I’ve been taught at college. It’s easier to grasp the web DOM, React, and git when you already know about trees and the related algorithms. Easier to learn SQL after opening some books on relational theory (basically the first chapter on database theory) and learning about projections. And definitely easier to learn the nature of distributed systems.

Learning how to use Bash and Ansible is a walk in the park after that.

	▲	0x696C6961 a day ago \| parent [-]
		There's a big difference between understanding the underlying concepts vs being proficient with a tool.

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jgord a day ago | parent | prev [-]

I personally look at react-foo and see something thats the opposite of how I want to work as a software craftsman [ small code, lispy / function flavored style, opinionated, few dependencies ]

For similar aesthetic reasons, have only dabbled with code-gen LLMs. Im happy to vibe code css and html but not, well actual code. I'm aware of my own double standard, Im fine with median-reverting banal css and html.

I do worry about some aspects of LLMs :

- google giving AI code snippets so easily, prevents traffic to sites like stack-overflow, where discussion happens

- vibe coding means less people hit the actual hard parts of coding, which result in learning to think as a developer. Thence where the next generation of developers who understand code ?

- code will become a magical, inscrutable black box where no-one understands how it works. DNNs and LLMs have this feature already. At least with LLM discovered math, the proof in lean exists, which is independent at how it was arrived at / searched for.

- if I write a novel, and the DNN AI detects it as AI slop with 68% probability, then what recourse do I have to prove its human written ?

- circular training : subsequent rounds of LLMs trained not on human input, but on LLM slop of the previous generation [ the %ge of which increases ]

- you will own nothing : fortunately it looks like self-hosted open weight LLMS will remain a thing, but the massive spend by hyperscaler companies on Datacenters/GPUs/RAM has driven down supply and driven up prices of CPU, GPU, RAM for enthusiasts / gamers / home AI nerds / garage startups .. which might stifle innovation.