FR version is available. Content is displayed in original English for accuracy.
Advertisement
Advertisement
⚡ Community Insights
Discussion Sentiment
75% Positive
Analyzed from 2317 words in the discussion.
Trending Topics
#code#llms#software#more#better#don#things#writing#themselves#language
Discussion (42 Comments)Read Original on HackerNews
Developers should write their own code and use LLMs to design and verify. Better, faster architecture and planning, pre-cleaned PRs and no skill atrophy or loss of understanding on the part of the developer.
I come in knowing what I need to build and at least one idea or more of how it should be done. I present the problem, constraints, potential solutions, and ask for criticisms and alternatives. I can keep it as broad as possible or I can get more granular like struct layouts, api endpoints, etc. I go back and forth until there's an approach I prefer and then I code that approach.
| it can code pretty well given a very tight and limited scope.
It's wildly better at tight and limited scope than large scale changes but even then I would rather code it myself.
I've had this conversation with managers in multiple organizations this year: "Yes, you could totally vibe code that instead of paying for a SaaS. But you have strict contractual and professional obligations about data security. Do you want to be deposed and asked, 'So, did you really just vibe code the system that led to the data leak? Did the vibe coders have any professional qualifications? Did they even look at the code?'"
Similarly, a backend server that handles 8 million users a day is expected to stay up.
Now, there are 10,000 things that have less demanding requirements. I'm actually really delighted that people are able to vibe code their own tools with minimal knowledge of software engineering! We have been chronically underproducing niche software all along.
But if your software already has on-call shifts (and SLAs, etc) like the GP, then I think you want to be smart about how you combine human expertise with LLMs.
Funny, I thought that the major hurdle is improving accuracy and reliability, as it's always been. Engineering is necessary and useful, but it's a much simpler problem, which is why everyone is jumping on it.
It does? You mean "it tests itself faster", which is not really a test now, is it?
I'm sure it was very difficult to program in machine code, but if now (or soon) anyone can just write software using a LLM without any sort of learning it changes everything. LLMs can plan and create something usable from simple instructions or ideas, and they will only get better.
I think LLMs will be (and already are) useful for many more things than programming anyway.
Did you read the section "Power to the People?" ? In it, the author dismantles your thesis with powerful, highly plausible arguments.
Would there even be a debate in the tech community if such unassailable arguments existed? The author is entirely entitled to his opinion, just as I am allowed to disagree with him (not sure why I am also downvoted). The good thing is, if I'm right, we will see it in less than 10 years.
I don't buy that's true. The "only" part, anyway. Look at how UX with software has evolved. This is gonna be an old man yells at clouds take, but before smartphones, there were hotkeys. And man, you could fly with those things. The computers running things weren't as fast as they are today, but you could mash in a a whole sequence thru muscle memory, and just wait for it to complete. Now, you have to poke at your phone, wait for it to respond, poke at it some more. It's really not great for getting fast at it. AI advancement is going to be like that. Directionally generally it will be better, but there's going to be some niche where, y'know what, ChatGPT-4o really had it in a way that 5.5 does not. (Rose colored glasses not included.)
> (although I’m personally skeptical of the “10x programmer” concept, the software industry overall does seem to accept it as true)
To be fair, this statement from Brooks doesn't entirely match with the "10x programmer" we talk about. My take on it is when someone says "10x programmer" today, they mean 10x more productive than the average, not 10x more productive than the worst. Brooks' statement is about the latter. If he'd looked at the difference between average and best, I would assume you'd get something more like a 2x or 4x programmer.
Just one more harness bro. Just one more agentic swarm. Please bro, just one more Claude Max subscription. Please bro.
You’re definitely right that people adopt agentic workflows and are disappointed or worse, but the point is the disappointment has already reduced substantially and will continue to do so. We know this because we know the scaling laws, and also because learning theory has been around for many decades.
We're almost 6 months into all this AI-code madness and I've yet to see that "rapid improvement" you mention. As in software products that are genuinely better compared to 6 months ago, or new software products (and good software products at that) which would have not existed had this AI craze not happened.
I think the biggest benefit language models have provided me is in the auxiliary aspects to programming: search, debugging, rubber ducking, planning, refactoring. The actual code generation has been mixed.
I had an LLM try and implement a fairly involved feature the other day, providing it with API spec details, examples from other open source libraries, and plenty of specifications. It's also something readily available in training data as well, but still fairly involved.
On first glance it looked great, and had I not spent the time to investigate deeper I would have missed some glaring deficiencies and omissions that render its implementation worthless. I am now going back and writing it by hand, but with language models providing assistance along the way, and it's going much better.
I think people are being unrealistic by thinking that the usage of language models in their side projects represent something broader. It's almost the perfect situation for language models: small, greenfield code bases, no review, no responsibility, and no users. It goes up on GitHub with a pretty readme, and then off to social media where they post about how developers are "cooked". It's just not a very realistic test.
In the end we will probably see large productivity increases by integrating language models, but they won't be replacing developers but rather augmenting them.
I honestly couldn't force myself to finish yet another blog post about how "we're not yet sure what impact LLMs will have on society" or whatever beleaguered point the author was attempting to make.
"Some random person's take on LLMs" was maybe interesting in 2024. Today it is not even remotely interesting.
There are a gazillion more interesting things happening today that ought to be of interest to the median HN reader. Can we talk about those instead?
It sounds like you actually do want to talk about how much you don't want other people to talk about LLMs.
i was doing an ML Sec phd a year or two before all this hype took off. i took one of the OG transformer papers along to present at our official little phd reading group when the paper was only a few months old (the details of this might be a bit sketchy here, was years ago now).
now i want nothing to do with the field in any way shape or form. i’m just done.
edit -- i got incredibly angry after writing this comment. pure hatred and spite for all the charlatans and accompanying bullshit.
I'm reminded of this scene from the Matrix: https://www.youtube.com/watch?v=cD4nhYR-VRA where the older wise man discusses societies reliance on AI
"Nobody cares how it works, as long as it works"
We're done. I for one welcome our new AI Overlords, or more accurately still welcome the tech bro billionares who are pulling the strings
There are, IMHO, fewer reasons to believe they will be able to do that rather than not, though.
The current state of the art is irrelevant. Only the first couple of time derivatives matter.
I would say I got better at both of those over the last 12-18 months. Are your skills static?
Really? That's like someone during an economic boom saying "The economy is the worst it'll ever be. There is no reason to expect things to not continue to improve".
Until recently. dramatic pause
And then AI happened.
The article goes on to assume there’s no 10x gain to be had but misses one big truth.
Needing to type the code is an enormous source of accidental difficulty (typing speed, typos, whether you can be arsed to put your hands on the keyboard today…) and it is gone thanks to coding agents.