alt Hacker NewsThe entire premise which he summarizes as:
> A huge reason VCs and tech tycoons put billions into funding LLMs was so they could undermine coders and depress wages
is just pure speculation, totally unsupported, and almost certainly untrue, and makes very little sense given the way LLMs and ChatGPT in particular came about. Every time I read something from Anil Dash it seems like it's this absolutely braindead sort of "analysis".
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Why do you say it's almost certainly untrue? Capital is well known for trying to suppress wages.
I recently heard a C-suite executive at a unicorn startup describe a particular industry as made up of small-scale, prideful craftsmen who will be unable to compete with agentic AI.
I don't know how much "VCs and tech tycoons" want to undermine coders specifically, but they see a huge opportunity to make money by making things much more efficiently (and thus cheaper) than they can be made now. The way to they plan to do that is to reduce the cost of labor. Which means either automating away jobs or making jobs much less specialized so that you don't need a highly-paid craftsman.
Think about Henry Ford setting up an assembly line where a worker sits at the same location and performs the same action all day, every day. You don't need a highly-skilled, highly-paid person with leverage and power to do that job.
Agreed, and the following summary point:
> Vibe coding might limit us to making simpler apps instead of the radical innovation we need to challenge Big Tech
is also pure speculation and doesn't make sense. In fact, enabling people to create small and simple apps could well indeed challenge and weaken dependence on big tech.
I stopped reading and closed the page.
In whatever way this is true, it has very little to do with sticking it to "coders" but is about magically solving/automating processes of any kind. Replacing programmers is small potatoes, and ultimately not a good candidate for jobs to replace. Programmers are ideal future AI operators!
What AI usage has underlined is that we are forever bound by our ability to communicate precisely what we want the AI to do for us. Even if LLMs are perfect, if we give it squishy instructions we get squishy results. If we give it a well-crafted objective and appropriate context and all the rest, it can respond just about perfectly. Then again, that is a lot of what programming has always been about in the first place - translate human goals into actionable code. Only the interface and abstraction level has changed.