441–450 of 728 posts
I don't know if I'm doing something wrong, but every time I ask gemini 2.5 for code it outputs SO MANY comments. An exaggerated amount of comments. Sections comments, step comments, block comments, inline comments, all the gang.
Google's models are pretty good, but their API(s) and guarantees aren't. We were just told today that 'quota doesn't guarantee capacity' so basically on-demand isn't prod capable. Add to that that there isn't a second vendor source like Anthropic and OpenAI have and Google's reliability makes it a hard sell to use them unless you can back up the calls with a different model family all together.
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Try dropping the entire api docs in the context. If it’s verbose, i usually pull only a subset of pages. Usually I’m using a minimum of 200k tokens to start with gemini 2.5.
That's more than 222 novel pages: 200k tk = 1/3 200k words = 1/300 1/3 200k pages
That generally seems right to me, given how much we hold in our heads when you’re discussing something with a coworker.
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> no amount of prompting will get current models to approach abstraction and architecture the way a person does I find this sentiment increasingly worrisome. It's entirely clear that every last human will be beaten on code design in the upcoming years (I am not going to argue if it's 1 or 5 years away, who cares?) I wished people would just stop holding on to what amounts to nothing, and think and talk more about wha…
I’ve been thinking about the SWE employment conundrum in a post-LLM world for a while now, and since my livelihood (and that of my loved ones’) depends on it, I’m obviously biased. Still, I would like to understand where my logic is flawed, if it is. (I.e I’m trying to argue in good faith here) Isn’t software engineering a lot more than just writing code? And I mean like, A LOT more? Informing product roadmaps, balan…
Power saws really reduced time, lathes even more so. Power drills changed drilling immensely, and even nail guns are used on roofing project s because manual is way too slow.
All the jobs still exist, but their tools are way more capable.
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> fine and useful And crippled, incomplete, and deceiving, dangerous.
That's normal for any professional tool, but it's not normal to be so upset about it. A saw will take your finger off, but you still want to use it for woodworking.
No: that in context is a plaster cast saw that looks vibrational but is instead a rotational saw for wood, and you will tend to believe it has safety features it was really not engineered with.
For plaster casts you have to have to plan, design and engineer a proper apt saw - learn what you must from the experience of saws for wood, but it's a specific project.
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I'm always impressed by the ability of the comment section to come up with more reasons why decent design and architecture of source code just can't happen: * "it's too hard!" * "my coworkers will just ruin it" * "startups need to pursue PMF, not architecture" * "good design doesn't get you promoted" And now we have "AI will do it better soon." None of those are entirely wrong. They're not entirely correct, either.
> * "my coworkers will just ruin it" This turns out to be a big issue. I read everything about software design I could get my hands on in years, but then at an actual large company it turned out to not help, because I'd never read anything about how to get others to follow the advice in my head from all that reading.
Asking one to make changes to such a code set, and you will get whatever branch the dice told the tree to go down that day.
To paraphrase, “LLMs are like a box of chocolates…”.
And if you have the patience to try and tack the AI to get back on track, you probably could have just done the work faster yourself.
Interestingly, when compering benchmarks of Experimental 03-25 [1] and Experimental 05-06 [2] it seems the new version scores slightly lower in everything except on LiveCodeBench. [1] https://storage.googleapis.com/model-cards/documents/gemini-... [2] https://deepmind.google/technologies/gemini/
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What they do is extraordinary, but it's not just a claim, they actually do, their doing so is evidence. Here someone just claimed that it is "entirely clear" LLMs will become super-human, without any evidence. https://en.wikipedia.org/wiki/Extraordinary_claims_require_e...
Again - I'd argue that the extraordinary success of LLMs, in a relatively short amount of time, using a fairly unsophisticated training approach, is strong evidence that coding models are going to get a lot better than they are right now. Will it definitely surpass every human? I don't know, but I wouldn't say we're lacking extraordinary evidence for that claim either. The way you've framed it seems like the only evi…
Just recently a lot of people (me included) got hit with a surprise bill, with some racking up $500 in cost for normal use
I certainly got burnt and removed my API key from my tools to not accidentally use it again
Example: https://x.com/pashmerepat/status/1918084120514900395?s=46
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I’ve been thinking about the SWE employment conundrum in a post-LLM world for a while now, and since my livelihood (and that of my loved ones’) depends on it, I’m obviously biased. Still, I would like to understand where my logic is flawed, if it is. (I.e I’m trying to argue in good faith here) Isn’t software engineering a lot more than just writing code? And I mean like, A LOT more? Informing product roadmaps, balan…
I think an analogy that is helpful is that of a woodworker. Automation just allowed them to do more things at in less time. Power saws really reduced time, lathes even more so. Power drills changed drilling immensely, and even nail guns are used on roofing project s because manual is way too slow. All the jobs still exist, but their tools are way more capable.