One of the great drawbacks of AI tools, is they allow anyone to build stuff... even if they have no ideas or knowledge.
It used to be that ShowHN was a filter: in order to show stuff, you had to have done work. And if you did the work, you probably thought about the problem, at the very least the problem was real enough to make solving it worthwhile.
Now there's no such filter function, so projects are built whether or not they're good ideas, by people who don't know very much
It's a bit parallel to that thing we had in 2023 where dinguses went into every thread and proudly announced what ChatGPT had to say about the subject. Consensus eventually become that this was annoying and unhelpful.
That is what Show HN has become. Nobody cares what code Claude shat in response to a random person prompt. If I cared, I would be prompting Claude myself.
Let's see, how to say this less inflamatory..
(just did this) I sit here in a hotel and I wondered if I could do some fancy video processing on the video feed from my laptop to turn it into a wildlife cam to capture the birds who keep flying by.
I ask Codex to whip something up. I iterate a few times, I ask why processing is slow, it suggests a DNN. I tell it to go ahead and add GPU support while its at it.
In a short period of time, I have an app that is processing video, doing all of the detection, applying the correct models, and works.
It's impressive _to me_ but it's not lost on me that all of the hard parts were done by someone else. Someone wrote the video library, someone wrote the easy python video parsers, someone trained and supplied the neural networks, someone did the hard work of writing a CUDA/GPU support library that 'just works'.
I get to slap this all together.
In some ways, that's the essence of software engineering. Building on the infinite layers of abstractions built by others.
In other ways, it doesn't feel earned. It feels hollow in some way and demoing or sharing that code feels equally hollow. "Look at this thing that I had AI copy-paste together!"
And for something that is, as you said, impressive to you, that's fine! But the spirit of Show HN is that there was some friction involved, some learning process that you went through, that resulted in the GitHub link at the top.
I saw this come out because my boss linked it as a faster chart lib. It is ai slop but people loved it. [https://news.ycombinator.com/item?id=46706528]
I knew i could do better so i made a version that is about 15kb and solves a fundamental issue with web gl context limits while being significantly faster.
AI helped do alot of code esp around the compute shaders. However, i had the idea of how to solve the context limits. I also pushed past several perf bottlenecks that were from my fundamental lack of webgpu knowledge and in the process deepened my understanding of it. Pushing the bundle size down also stretched my understanding of js build ecosystems and why web workers still are not more common (special bundler setting for workers breaks often)
Btw my version is on npm/github as chartai. You tell me if that is ai slop. I dont think it is but i could be wrong
In the past, new modders would often contribute to existing mods to get their feet wet and quite often they'd turn into maintainers when the original authors burnt out.
But vibe coders never do this. They basically unilaterally just take existing mods' source code, feed this into their LLM of choice and generate a derivative work. They don't contribute back anything, because they don't even try to understand what they are doing.
Their ideas might be novel, but they don't contribute in any way to the common good in terms of capabilities or infrastructure. It's becoming nigh impossible to police this, and I fear the endgame is a sea of AI generated slop which will inevitably implode once the truly innovative stuff dies and and people who actually do the work stop doing so.
AI agent coding has introduced to writing software a sort of interaction like what brands have been doing to social media.
In which case, I kinda disagree. Substandard work is typically submitted by people who don't "get it" and thus either don't understand the standard for work or don't care about meeting it. Either way, any future submission is highly likely to fail the standard again and waste evaluation time.
Of course, there's typically a long tail of people who submit one work to a collection and don't even bother to stick around long enough to see how the community reacts to that work. But those people, almost definitionally, aren't going to complain about being "gatekept" when the work is rejected.
There is this real disconnect between what the visible level of effort implies you've done, and what you actually have to do.
It's going to be interesting to see how our filters get rewired for this visually-impressive-but-otherwise-slop abundance.
Last year though I purchased the next book in the series and I am 99% sure it was AI generated. None of the characters behaved consistently, there was a ton of random lewd scenes involving characters from books past. There were paragraphs and paragraphs of purple prose describing the scene but not actually saying anything. It was just so unlike every other book in the series. It was like someone just pasted all the previous books into an LLM and pushed the go button.
I was so shocked and disappointing that I paid good money for some AI slop I've stopped following the author entirely. It was a real eye opener for me. I used to enjoy just taking a chance on a new book because the fact that it made it through publishing at least implied some minimum quality standard, but now I'm really picky about what books I pick up because the quality floor is so much lower than in the past.
Honestly: there is SO much media, certainly for entertainment. I may just pretend nothing after 2022 exists.
Wait, what? That's a great benefit?
Let’s be honest, this was always the case. The difference now is that nobody cares about the implementation, as all side projects are assumed to be vibecoded.
So when execution is becoming easier, it’s the ideas that matter more…
It used to be that getting to that point required a lot of effort. So, in producing something large, there were quality indicators, and you could calibrate your expectations based on this.
Nowadays, you can get the large thing done - meanwhile the internal codebase is a mess and held together with AI duct-tape.
In the past, this codebase wouldn't scale, the devs would quit, the project would stall, and most of the time the things written poorly would die off. Not every time, but most of the time -- or at least until someone wrote the thing better/faster/more efficiently.
How can you differentiate between 10 identical products, 9 of which were vibecoded, and 1 of which wasn't. The one which wasn't might actually recover your backups when it fails. The other 9, whoops, never tested that codepath. Customers won't know until the edge cases happen.
It's the app store affect but magnified and applied to everything. Search for a product, find 200 near-identical apps, all somehow "official" -- 90% of which are scams or low-effort trash.
— Tom Cargill, Bell Labs
Some day I’m going to get a crystal ball for statistics. Getting bored with a project was always a thing— after the first push, I don’t encounter like 80% of my coding side projects until I’m cleaning— but I’ll bet the abandonment rate for side projects has skyrocketed. I think a lot of what we’re seeing are projects that were easy enough to reach MVP before encountering the final 90% of coding time, which AI is a lot less useful for.
My experience is the opposite. It’s so much easier to have an LLM grind the last mile annoyances (e.g. installing and debugging compilation bullshit on a specific raspberry pi + unmaintained 3p library versions.)
I can focus on the parts I love, including writing them all by hand, and push the “this isn’t fun, I’d rather do something else” bits to a minion.
That’s not really the part I’m talking about. My gut says that if tests are a blocker for weekend projects, people just don’t bother writing them. I certainly wouldn’t imagine them taking much longer to code than the core functionality.
In my experience, which seems to resonate with a lot of people, AI quickly stands up really useful boilerplate and very convenient purpose-built scaffolding… but is a lot less useful helping you solve actual problems in a way that makes sense to people that have those problems. Especially if you’re using a less-mainstream language or some other component.
I’ve seen variation of this question since first few weeks /months after the release of ChatGPT and I havent seen an answer to this from leading figures in the AI coding space, whats the general answer or point of view on this?
printn(n,b) {
extrn putchar;
auto a;
if(a=n/b) /* assignment, not test for equality */
printn(a, b); /* recursive */
putchar(n%b + '0');
}
I don't think we need to wait a generation either. This probably was a part of their personality already, but a group of people developers on my job seems to have just given up on thinking hard/thinking through difficult problems, its insane to witness.
Long-term, this is will do enormous damage to society and our species.
The solution is that you declare war and attack the enemy with a stream of slop training data ("poison"). You inject vast quantities of high-quality poison (inexpensive to generate but expensive to detect) into the intakes of the enemy engine.
LLMs are highly susceptible to poisoning attacks. This is their "Achilles' heel". See: https://www.anthropic.com/research/small-samples-poison
We create poisoned git repos on every hosting platform. Every day we feed two gigabytes of poison to web crawlers via dozens of proxy sites. Our goal is a terabyte per day by the end of this year. We fill the corners of social media with poison snippets.
There is strong, widespread support for this hostile posture toward AI. For example, see: https://www.reddit.com/r/hacking/comments/1r55wvg/poison_fou...
Join us. The war has begun.
Nice. I hope you are generating realistic commits and they truly cannot distinguish poison from food.
The cost of detecting/filtering the poison is many orders of magnitude higher than the cost of generating it.
Thing is I worked manually on both of these a lot before I even touched Claude on them so I basically was able to hit my wishlist items that I don't have time to deal with these days but have the logic figured out already.
I have two projects right now on the threshold of "Show HN" that I used AI for but could have completed without AI. I'm never going to say "I did this with AI". For instance there is this HR monitor demo
https://gen5.info/demo/biofeedback/
which needs tuning up for mobile (so I can do an in-person demo to people who work on HRV) but most all being able to run with pre-recorded data so that people who don't have a BTLE HR monitor can see how cool it is.
Another thing I am tuning up for "never saw anything like this" impact is a system of tokens that I give people when I go out as-a-foxographer
https://mastodon.social/@UP8/116086491667959840
I am used to marketing funnels having 5% effectiveness and it blows my mind that at least 75% of the tokens I give out get scanned and that is with the old conventional cards that have the same back side. The number + suit tokens are particularly good as a "self-working demo" because it is easy to talk about them, when somebody flags me down because they noticed my hood I can show them a few cards that are all different and let them choose one or say "Look, you got the 9 of Bees!"
It seems silly, but I know I'm more likely to review an implementation if can learn more about the author's state of mind by their style.
As I may have noted before, humans are the problem.
I don't particularly care if people question that, but the source repo is on GitHub: they can see all the edits that were made along the way. Most LLMs wouldn't deliberately add a million spelling or grammar mistakes to fake a human being... yet.
As for knowing what I'm talking about. Many of my blog posts are about stuff that I just learned, so I have many disclaimers that the reader should take everything with a grain of salt. :-) That said: I put a ridiculous amount of time in these things to make sure it's correct. Knowing that your stuff will be out there for others to criticize if a great motivator to do your homework.
Side note: I’d think installing Anubis over your work would go a long way to signaling that but ymmv.
presumably if this is true, it should be obvious by the quality of your product. If it isnt, then maybe you need to need to rethink the value of your artisanal hand written code.
> author (pilot?) hasn't generally thought too much about the problem space
I’ve stopped saying that “AI is just a tool” to justify/defend its use precisely because of this loss of thought you highlight. I now believe the appropriate analogy is “AI is delegation”.
So talking to the vibe coder that’s used AI is like talking to a high level manager rather than the engineer for human written code
These days I do see a lot of people choosing software for the money. Notably, many of them are bootcamp graduates and arguably made a pivot later in life, as opposed to other careers (such as medicine) which get chosen early. Nothing wrong with that (for many it has a good ROI), but I don’t think this changed anything about people with technical hobbies.
When you’re young, you tend not to choose the path the rest of your life will take based on income. What your parents want for you is a different matter…
* some people want to show off a fun project/toy/product that they built because it's a business they're trying to start and they want to get marketing
* some people want to show off a fun project/toy/product that they built because it's involves some cool tech under the hood and they want to talk shop
* some people want to show off a fun project/toy/product that they built because it's a fun thing and they just want some people to have fun
It's taken me about month; currently at ~500 commits. I've been obsessed with this problem for ~6 weeks and have made an enormous amount of progress, but admittedly I'm not an expert in the domain.
Being intentionally vague, because I don't want to tip my hand until it's ready. The problem is related to an existing open source tool in a particular scientific niche which flatly does not work on an important modern platform. My project, an open source repo, brings this important legacy tool to this modern platform and also offers a highly engaging visual demo that is of general interest, even to a layperson not interested in programming or this particular scientific niche.
I genuinely believe I have something valuable to offer to this niche scientific community, but also as a general interest and curiosity to HN for the programming aspects (I put a lot of thought into the architecture) as well as the visual aspects (I put a lot of thought into the design and aesthetics).
Do you have any advice on how to present this work in a compelling way to people who understandably feels as burned out on AI slop as you do?
I'm not an anti-AI luddite, but for gods sake talk about (ie. submit) something else!
Having too may subs could get out of hand, but sometimes you end up with so much paperwork generated so fast that it needs its own dedicated whole drawer in your filing cabinet ;)
It's still early and easy to underestimate the number of visitors who would absolutely love to have the main page more covered in absolute pure vibe than it is recently.
I would like to hear opinions as to why the non-human touch is preferred, that could add something that not many are putting into words.
Hopefully it's not a case of the lights being on but nobody's home :(
You'll be inventing a lot of novel cicular apparatus with a pivot and circumferencrial rubber absorbers for transportation and it'll take people serious efforts to convince you it's just a wheel.
I mean it's a real problem, but it's also a solved problem, and also not a problem that comes up a lot unless you're doing the sort of engineering where you're using a CAD tool already.
I don't doubt it's useful, and seems pretty well crafted what little I tried it, but it doesn't really invite much discussion.
Agreed. r/ProgrammingLanguages had to deal with this recently in the same way HN has to; people were submitting these obviously vibecoded languages there that barely did anything, just a deluge of "make me a language that does X", where it doesn't actually do X or embody any of the properties that were prompted.
One thing that was pointed out was "More often than not the author also doesn't engage with the community at all, instead they just share their project across a wide range of subreddits." I think HN is another destination for those kinds of AI slop projects -- I'm sure you could find every banned language posted on that forum posted here.
Their solution was to write a new rule and just ban them outright. Things have been going much better since.
https://www.reddit.com/r/ProgrammingLanguages/comments/1pf9j...
concur, perhaps a dedicated or alternative, itch.io like area named "Slop HN:..."