681–690 of 783 posts
Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected , thanks to Solow's productivity paradox [1]. Which is that information technology similarly (and seemingly shockingly) didn't produce any net economic gains in the 1970's or 1980's despite all the computerization. It wasn't until the mid-to-late 1990's that information technology finally started to show clear benef…
This title is so click bait-y and misleading compared to what the actual article is about it's tough not to feel disappointed this is on the front page. @dang
p.s. @dang doesn't work reliably - hn@ycombinator.com is the way to get a message delivered
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Hard miss. GP is right, and your assumptions say more about you than about me. :^)
> Hard miss. GP is right, and your assumptions say more about you than about me. :^) No. If that's the case, your statement was unclear: since you didn't specify who else thinks those people were cattle, the implication is that you think it. Especially since you prefaced your statement with "I’d argue." And the interpretation... > It seems more like they're implying it's those at the top think that about other people…
I never said it was clear? Two commenters got it right, two wrong, so it wasn’t THAT unobvious.
> What indication has "the top" given to show they have that kind of foresight and control? The closest is the AI-bros advocacy of UBI, which (for the record) has gone nowhere.
Tech bros selling “no more software engineers” to cost optimizers, dictatorships in US, Russia, China pressing with their heels on our freedoms, Europe cracking down on encryption, Dutch trying to tax unrealized (!) gains, do I really need to continue?
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In my experience the example you give here is exactly the kind of problem that AI powered code reviews are really good at spotting, and especially amongst codebases with tens of thousands of lines of code in them where a human being might well get scrolling blindness when quickly moving around them to work.
The AI is the one which made the mistake in the first place. Why would you assume it's guaranteed to find it? The few times I've tried giving LLMs a shot I've had them warning me of not putting some validations in, when that exact validation was exactly 1 line below where they stopped looking. And even if it did pass an AI code review, that's meaningless anyway. It still needs to be reviewed by an actual human before…
I didn't say they were guaranteed to find it: I said they were really good at finding these sorts of errors. Not perfect: just really good. I also didn't make any assumption: I said in my experience, by which I mean the code you shared is similar to a portion of the errors that I've seen LLMs find.
Which LLMs have you used for code generation?
I mostly use claude-opus-4-6 at the moment for development, and have had mostly good experiences. This is not to say it never gets anything wrong, but I'm definitely more productive with it than without it. On GitHub I've been using Copilot for more limited tasks as an agent: I find it's decent at code review, but more variable at fixing problems it finds, and so I quite often opt for manual fixes.
And then the other question is, how do you use them? I tend to keep them on quite a short leash, so I don't give them huge tasks, and on those occasions where I am doing something larger or more complex, I tend to write out quite a detailed and prescriptive prompt (which might take 15 minutes to do, but then it'll go and spend 10 minutes to generate code that might have taken me several hours to write "the old way").
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> I see people thinking modern AI models can’t generate working code. Really? Can you show any examples of someone claiming AI models cannot generate working code? I haven't seen anyone make that claim in years, even from the most skeptical critics.
10 days ago someone was making this claim about copilot on legacy code: https://news.ycombinator.com/item?id=46932609 > Github Copilot has been great in getting that code coverage up marginally but ass otherwise.
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True, but you'd be surprised how much you can tighten up a codebase by asking a heftier model to do a security review and suggest fixes.
At what point do people really know if it has been tightened up if they never look at the code?
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What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.
[dead]
"What would you say you do here?" --Office Space
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Do you use an agent harness to have it review code for you before you do? If not, you don't know how to use it efficiently . A large part of using AI efficiently is to significantly lower that review burden by having it do far more of the verification and cleanup itself before you even look at it.
> Do you use an agent harness to have it review code for you before you do? Right now you need to be Uncle Moneybags to do this in your personal life. If you're lucky, your employer is footing the bill but otherwise... Ugh. It's like converting your app running perfectly fine on a cheap VPS to AWS Lambda. In theory , it's fine but in reality the next bill you get could make you faint.
The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion. Other white collar busines…
I’m confused what kind of software engineer jobs there are that don’t involve meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate that, thinking about market positioning, etc? If you weren’t doing much of that before, I struggled to think of how you were doing much engineering at all, save some more niche extremely technical roles where many of those questions were alre…
Isn't like half of our industry just churning out JS file after JS file to yet again change how facebook looks?
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Do you use an agent harness to have it review code for you before you do? If not, you don't know how to use it efficiently . A large part of using AI efficiently is to significantly lower that review burden by having it do far more of the verification and cleanup itself before you even look at it.
This is correct, but part of the issue is that it significantly increases token usage costs. Some companies are doing: - PRD and spec fulfillment review - code review + correction loops - security review + corrections - addl. test coverage and tidying - addl. type checks and tidying - addl. lint checks and tidying - maybe more I haven't listed And these are run after each commit, so you can only imagine the costs per…
The question is what your time is worth for the company, and which tasks costs less to have an agent automate than having you do.