Kids fresh out of college with crippling student debt and no jobs should just buy increasingly expensive GPUs capable of running the best local models. Well done, problem solved.
> Where are these hyper productive small companies running laps around bigger ones right now?
Getting bought by the bigger companies as it is currently the goal of most start-up since no one cares about monopolies and anti competitive behavior nowadays.
Really? What is this reddit? If you are going to resort to name calling at least provide some genuine facts? Show me what in their Zig fork was too much? You assume Zig is “finished” being built? Because thats a bold claim, seems every major Zig change is some very major shift in the language. Zig is where Rust was before it did the borrow checker system.
If you find it that hard to keep those feelings to yourself in the context of contributing to rust, and are too stubborn to make a one character change to pronouns when you’re addressing people, I have to imagine that you’re utterly incapable of working in any professional context, where you’re expected to conform to many more things that make less sense. This seems like a problem with you.
That sex determines if you're a man or a woman, and gender is irrelevant? I do, but I'm being asked to believe the inverse, or to act as if I do.
> many more things that make less sense
I can think of nothing remotely like being asked to call a man a woman. Id be happy to be wrong about that, but this is nothing like homosexuality, racism or any other "ism" We've seen before.
Believing in the capabilities of _upcoming_ LLMs that you have never actually used shows that you buy into marketing and hype very easily. No one really knows what the future will look like and there's an equally plausible one where post-subsidy token economics become impossible to justify for most use cases.
To answer "what better way," clearly using the skills regularly is much better. Letting them atrophy for potentially multiple years and then trying to resurrect them repeatedly doesn't seem like a recipe for maintaining sharp skills to me.
That's definitely optimal, but I don't think a lot of people are going to have that opportunity. It's not really in the short-term interest of a company to have people spending time on that.
I think you should be very picky about generated PRs not as an act of sabotage but because very obviously generated ones tend to balloon complexity of the code in ways that makes it difficult for both humans and agents, and because superficial plausibility is really good at masking problems. It's a rational thing to do.
Eventually you are faced with company culture that sees review as a bottleneck stopping you from going 100x faster rather than a process of quality assurance and knowledge sharing, and I worry we'll just be mandated to stop doing them.
It's disappointing that this is clearly being downvoted due to disagreement - it's a valid perspective. We have very little evidence of the overall impact of aggressively generating code "in the wild" and plenty of bad examples. No one knows what this ends up looking like as it continues to meet reality but plenty are taking a large productivity improvement as a given.
>Here are some well known names who are now saying they regularly use LLM's for development. For many of these folks, that wasn't true 1-2 years ago:
This is a huge overstatement that isn't supported by your own links.
- Donald Knuth: the link is him acknowledging someone else solved one of his open problems with Claude. Quote: "It seems that I’ll have to revise my opinions about “generative AI” one of these days."
- Linus Torvalds: used it to write a tool in Python because "I know more about analog filters—and that’s not saying much—than I do about python" and he doesn't care to learn. He's using it as a copy-paste replacement, not to write the kernel.
- John Carmack: he's literally just opining on what he thinks will happen in the future.
You're going to get a lot of "skill issue" comments but your experience basically matches mine. I've only found LLMs to be useful for quick demos where I explicitly didn't care about the quality of implementation. For my core responsibility it has never met my quality bar and after getting it there has not saved me time. What I'm learning is different people and domains have very different standards for that.
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