https://archive.ph/hMZPi

Remember when tech workers dreamed of working for a big company for a few years, before striking out on their own to start their own company that would knock that tech giant over?

Then that dream shrank to: work for a giant for a few years, quit, do a fake startup, get acqui-hired by your old employer, as a complicated way of getting a bonus and a promotion.

Then the dream shrank further: work for a tech giant for your whole life, get free kombucha and massages on Wednesdays.

And now, the dream is over. All that’s left is: work for a tech giant until they fire your ass, like those 12,000 Googlers who got fired six months after a stock buyback that would have paid their salaries for the next 27 years.

We deserve better than this. We can get it.

  • expr
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    1 year ago

    Learning frameworks has never been hard, and frankly does not make up the majority of a developer’s job. Maybe you do it while onboarding. Big whoop. Any good developer can do that fairly easily, and LLMs are entirely superfluous. Worse yet, since they are so commonly confidently incorrect, you have to constantly check if it’s even correct. I’d prefer to just read the documentation, thanks.

    A mature engineering organization is not pumping out greenfield projects in new languages/frameworks all the time. Greenfield is usually pretty rare, and when you do get a greenfield project, it’s supposed to be done using established tools that everyone already knows.A tiny fraction of a developer’s job is actually writing code. Most of it is the soft skills necessary to navigate ambiguous requirements and drive a project to completion. And when we do actually program, it’s much more reading code than it is writing code, generally to gain enough understanding of the system in order to make a minor change.

    LLMs are highly overrated. And even if it does manage to produce something useful, there’s much more to a codebase itself. There’s the socialization of knowledge around it and the thought process that went into it, none of which you gain when using an LLM. It’s adequate for producing boilerplate no one reads anyway, but that’s such a small fraction of what we even do (and hopefully, you can abstract away that boilerplate so you’re not writing it over and over again anyway).