231–240 of 259 posts
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Which every AI tool I’m aware of respects and ignores by default.
Why is it that they can add new env variables then?
You know what. After seeing all these articles about AI/LLM for these past 4 years, about how they are going to replace me as software developers and about how I am not productive enough without using 5 agents and being a project manager. I. Don't. Care. I don't even care about those debates outside. Debates about do LLM work and replace programmers? Say they do, ok so what? I simply have too much fun programming. I…
So much of my professional SWE jobs isn't even programming - I feel like this is a detail missed by so many. Generally people just stereotype SWE as a programmer, but being an engineer (in any discipline) is so much more than that. You solve problems. AI will speed up the programming work-streams, but there is so much more to our jobs than that.
Most of the work brought to me gets done before I even think about sitting down to type.
And it's interesting to see the divide here between "pure coder" and "coder + more". A lot of people seem to be in the job to just do what the PM, designer and business people ask. A lot of work is pushing back against some of those requests. In conversations here in HN about "essential complexity" I even see commenters arguing that the spec brought to you is entirely essential. It's not.
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This is a qualitative methods paper, so statistical significance is not relevant. The rough qualitative equivalent would instead be "data saturation" (responses generally look like ones you've received already) and "thematic saturation" (you've likely found all the themes you will find through this method of data collection). There's an intuitive quality to determining the number of responses needed based on the topi…
So, I upvoted your comment bc I genuinely believe there is something in your comments worth learning from, but... > This is a qualitative methods paper, so statistical significance is not relevant. I have never heard of a "qualitative methods paper" and it sounds like something a researcher would do to push a narrative with "qualitative data" rather than data that could be measured. Tell me why I am wrong.
[1] https://en.wikipedia.org/wiki/Qualitative_research
[2] https://en.wikipedia.org/wiki/List_of_research_universities_...
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>By comparison, in the last week I've prototyped six applications at levels that would take me days to weeks individually [...] I don't doubt that the models have got better, but you can go back two or three years and find people saying the exact same stuff about the latest models back then.
I don't think that's true of three years ago - that's taking us back into GPT-3 territory. And two years ago we were mostly still stuck with GPT-4 which had an 8,000 input context limit, very challenging to get real coding work done with that. Easy enough to prove though, find some examples of people saying that 2-3 years ago and I shall concede the point!
I see that 2023 LinkedIn has (deservedly) gone down your memory hole, but it is very easy to find innumerable examples of people saying this kind of thing:
https://www.reddit.com/r/ChatGPTCoding/comments/11zu7l7/i_bu...
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So, I upvoted your comment bc I genuinely believe there is something in your comments worth learning from, but... > This is a qualitative methods paper, so statistical significance is not relevant. I have never heard of a "qualitative methods paper" and it sounds like something a researcher would do to push a narrative with "qualitative data" rather than data that could be measured. Tell me why I am wrong.
You're not necessarily wrong, but the phrase "push a narrative," the scare quotes around "qualitative data," and your initial comment suggest to me that you are not familiar with qualitative research but have a bias or mistrust against it (no judgment, just stating my observation). If you would like to know more about it, this[1] provides a reasonable overview, and if you would like to know much more, I can ask my sp…
I can confirm that, yes, I do have an arguably paranoid bias and/or mistrust against information that is not quantifiable in nature nor is simple enough for me (an idiot) to understand easily.
Appreciate the thoughtful response. Don't ask the spouse, just enjoy the new year. I'll figure it out.
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I don't think that's true of three years ago - that's taking us back into GPT-3 territory. And two years ago we were mostly still stuck with GPT-4 which had an 8,000 input context limit, very challenging to get real coding work done with that. Easy enough to prove though, find some examples of people saying that 2-3 years ago and I shall concede the point!
GPT-4 was released in March 2023, so it pretty clearly comes under the heading of “two or three years” ago. It’s only three months shy of its third birthday. I see that 2023 LinkedIn has (deservedly) gone down your memory hole, but it is very easy to find innumerable examples of people saying this kind of thing: https://www.reddit.com/r/ChatGPTCoding/comments/11zu7l7/i_bu...
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2025 has been a wild year for agentic coding models. Cutting-edge models in January 2025 don't hold a candle to cutting edge models in December 2025. Just the jump from Sonnet 3.5 to 3.7 to 4.5, and Opus 4.5 has been pretty massive in terms of holistic reasoning, deep knowledge as well as better procedural and architectural adherence. GPT-5 Pro convinced me to pay $200/mo for an OpenAI subscription. Regular 5.2 model…
> Just the jump from Sonnet 3.5 to 3.7 to 4.5, and Opus 4.5 has been pretty massive in terms of holistic reasoning, deep knowledge as well as better procedural and architectural adherence. I don't really agree. Aside from how it handled frontend code, changes in Sonnet did not truly impact my overall productivity (from Sonnet 3.7 to 4 to 4.5, i did not try 3.5). Opus 4.5/Codex 5.2 are when the changes truly happenned…
I also chat with these models for long hours about deep, complicated STEM subjects and am very impressed with the level of holistic knowledge and wisdom compared to models a year ago. And the abstract math story has gotten sooooo much better.
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Ok I will bite. Every single example you gave is in a hobby project territory. Relatively self-contained, maintainable by 3-4 devs max, within 1k-10k lines of code. I've been successfully using coding agents to create such projects for the past year and it's great, I love it. However, lots of us here work on codebases that are 100x, 1000x the size of these projects you and Karpathy are talking about. Years of domain…
Everything is made of smaller parts. I'd like to think we can sub divide a code base into isolated modules at least.
I'd put it in line with monolith vs microservices... You're shifting complexity somewhere, if it's on orchestration or the codebase. In the end, the piper gets paid.
Also, not all problems can be broken down cleanly into smaller parts.
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I don't think that's true of three years ago - that's taking us back into GPT-3 territory. And two years ago we were mostly still stuck with GPT-4 which had an 8,000 input context limit, very challenging to get real coding work done with that. Easy enough to prove though, find some examples of people saying that 2-3 years ago and I shall concede the point!
GPT-4 was released in March 2023, so it pretty clearly comes under the heading of “two or three years” ago. It’s only three months shy of its third birthday. I see that 2023 LinkedIn has (deservedly) gone down your memory hole, but it is very easy to find innumerable examples of people saying this kind of thing: https://www.reddit.com/r/ChatGPTCoding/comments/11zu7l7/i_bu...