It's better that everyone is loud about it then everyone giving up and being silently irritated. At least if people complain it's possible to read the room
Tbh, I still wonder why people even bother releasing such tools that were shitted out by an LLM in an hour or two, these are basically the modern equivalent of a hastily cobbled together 10-liner shell script (still useful, but not something you'd ever put up as its own Github project).
Everybody else can write such tools now by themselves in at most an hour, and they get a tool that's more personalized to their tastes. And why have a readme at all when it's just LLM mumbo-jumbo - that sort of mumbo-jumbo is written for LLMs to consume, not humans.
In theory, there is some value in deciding what the LLM ought to shit out, and checking that it works, and maybe even making a design decision or two to try and create something that would be relevant or useful for many people. And then others can possibly save an hour or two, and the data centre can save some water and electricity.
That's 6 more commits than I'm used to seeing for these sorts of efforts, honestly. (But I will cede that people might be doing all the changes locally and then pushing a single commit, without any real understanding of how version control works.)
If folks do this; I'd love for them to also be in the habit of shipping their prompts + harness configuration too. If we are moving to another code abstraction, then that becomes the source code to modify, adapt and extend.
I mean -- compilers used to annoy developers who knew how to hand-roll machine code, with bad outputs and inefficient algorithms, till the compilers got better than most of them...
I appreciate it when people say something is slop. Saves me from wasting my time looking at it.
How many slop ideas have come to the front page, never to be heard from again because the execution isn’t actually any good? I’m guessing most of them.
Just because the ReadMe is slop, doesn’t mean the code is slop. People are starting to make apps for themselves now and open-sourcing them so they’re not putting much thought into the ReadMe or distribution.
This just means ReadMe’s are less important now. I just have my terminal agent dig into the code and tell me what features are there. If the app is actually useful.
Even before AI, there were so many projects with subpar ReadMes, no screenshots, etc. But once you use the software, you realize how good it is.
Source: I maintain a massive collection of open-source alternatives and quality of open-source alternatives have increased a lot
For many new coders, LLMs are so good at writing the code, asking it to write the ReadMe sounds like a good idea. Clearly it’s the first impression your project makes so handwriting it is important.
Being turned off by the project because of the ReadMe is your prerogative. I’m just suggesting you dig into the code sometimes, the ReadMe is not the be all, end all.
> For many new coders, LLMs are so good at writing the code, asking it to write the ReadMe sounds like a good idea. Clearly it’s the first impression your project makes so handwriting it is important.
The point is that if they looked at the result they'd question themselves. And the fact that they don't is a violation of the social contract: I can hardly be expected to care about your work, if you don't.
Perhaps we should have README.md and README.ai the latter containing a bunch of stuff that humans don't want to read but agents can use to answer questions humans ask
You can produce good code and good projects with Claude doing all the work. This might even be an example of one, but the description on GitHub makes so little sense that I stopped reading before I figured out what it even does.
And every comment on HN calling out vibe-coded slop has this same complaint comment in turn. OP has an actual complaint, your complaint is just "stop complaining".
It’s not stop complaining as much as it is please contribute something of substance instead of venting hot air into a comment thread where everyone is already aware.
1/3 of articles warrantying such a comment means it is still important information. If it was 100% of the articles I would agree that it gives no information, but with 1/3 one cannot claim it does not contribute information.
The problem is that not everyone thinks like you. You're dictating what is and isn't a signal to others. OP left a comment to signal to people like me. It saved me a click.
I thought it was a fine informative readme, starts with the problem, outlines the core of the solutions, and some limitations. Everything I want to know in the first few paragraphs. No need to spend human time to improve it.
An llm response here would be more respectful than a downvote without a comment.
And it’s quite disrespectful to dismiss a project that may have taken a lot of time and thought, even with agents, to build, and just dismiss it because the readme was created by an agent.
I'd be interested to see if using DiffusionGemma-as-Jev helps as you can feed the image directly into the model and it'll make decisions based on the image embeddings.
I had a long talk with chat gpt about this today as well. I think its duable and prolly not too hard either, also you could do lotsa funky stuff with stitched frames of a video in one 4x4 grid for example and send that as one image for analysis. that way temporal understanding can be had for fractions of a second by jev... also because vlm works in pixel space you can get around the whole state machine issue as well, so many possibilities...
not sure how this is innovative they show the System-1 model can play Doom right in the announcement [1] :
>Doom
>We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI. The engineer behind it was worried about making 10 queries a second (which ends up costing ~$7/hour), but the rest of us agreed that was lower than expected! This is so fun we intend to not only release an in-depth walkthrough, but also host some events to hack on this.
Well nothing about the Doom demo or this entire model is new new either, is it? I don't even think Typesafe themselves are claiming anything novel, they say that they're focusing on practicality instead of chasing big numbers and AGI. Classifiers are older than generative models and are used everywhere. Fast classifiers are used in sampling machinery of every big model and for automation in agentic game plugins for years, except they're usually small and finetuned for the task, not general-use.
I think many people wondered why non-generative models are so underused on a big scale, well here's a long overdue attempt to market that which evidently goes well with people being interested in this again. The field has been captured by the vibe coding and valuation-goes-up hype and a bit. AI has a ton of low hanging fruits that are much more practical than using one tool that gets most attention for everything.
Curious about people’s experience here. I am working on a small model, verify by jev, and escalate to big model. Some cases, the small model is not a model but some regex.
It's a quick proof of concept of computer use powered by Jev, a new general-purpose classifier model. Here it takes the description of the interface (it can't do images yet) and outputs commands. It's faster and many times cheaper than using frontier generative models like GPT to do the same.
This is only tangentially related but is Jev trained on the same kind of data as the rest of the LLM world? (i.e. unethical)
At a glance it addresses two out of three of my "load bearing points" against AI, which is the cost to run the things, and that they can be used to generate slop.
If it was trained ethically that would "close the gap".
If this was talking about buying the best apples are the supermarket, sure, complain away about the use of an LLM to talk about apples.
But it's really a specious argument about something that likely only exists because an LLM is good at creating that type of project.
Everybody else can write such tools now by themselves in at most an hour, and they get a tool that's more personalized to their tastes. And why have a readme at all when it's just LLM mumbo-jumbo - that sort of mumbo-jumbo is written for LLMs to consume, not humans.
In practice, well.
I mean -- compilers used to annoy developers who knew how to hand-roll machine code, with bad outputs and inefficient algorithms, till the compilers got better than most of them...
Awesome!
I think these repo owners should be required to film themselves reading out their Claudemade readmes with a straight face.
Every honest caveat. Every seam. Every "Frames lie, so the walk prunes hard".
How many slop ideas have come to the front page, never to be heard from again because the execution isn’t actually any good? I’m guessing most of them.
This just means ReadMe’s are less important now. I just have my terminal agent dig into the code and tell me what features are there. If the app is actually useful.
Even before AI, there were so many projects with subpar ReadMes, no screenshots, etc. But once you use the software, you realize how good it is.
Source: I maintain a massive collection of open-source alternatives and quality of open-source alternatives have increased a lot
Being turned off by the project because of the ReadMe is your prerogative. I’m just suggesting you dig into the code sometimes, the ReadMe is not the be all, end all.
The point is that if they looked at the result they'd question themselves. And the fact that they don't is a violation of the social contract: I can hardly be expected to care about your work, if you don't.
Just the bare minimum effort to do that would be nice.
Slop is an instant tab close for me. If something’s good, it’ll come around again. I’ll catch it when there's some evidence that it’s worth my time.
I wish they'd just use Astra instead. It doesn't write this awful prose.
I'd say "imagine if half the posts on HN aren't worth your time" but this is genuinely how it feels nowadays. I'm not sorry
And it’s quite disrespectful to dismiss a project that may have taken a lot of time and thought, even with agents, to build, and just dismiss it because the readme was created by an agent.
>Doom >We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI. The engineer behind it was worried about making 10 queries a second (which ends up costing ~$7/hour), but the rest of us agreed that was lower than expected! This is so fun we intend to not only release an in-depth walkthrough, but also host some events to hack on this.
[1] https://typesafe.ai/blog/introducing-system-one-models-and-j...
I think many people wondered why non-generative models are so underused on a big scale, well here's a long overdue attempt to market that which evidently goes well with people being interested in this again. The field has been captured by the vibe coding and valuation-goes-up hype and a bit. AI has a ton of low hanging fruits that are much more practical than using one tool that gets most attention for everything.
are you the author? If so - what are your notes on using Jev in this scenario?
It's also now on openrouter and cloudflare
cheap-confirm-escalate
Using jev as the confirm step.
> Every piece of reasoning the frontier model does for free has to be rebuilt here as deterministic state.
EDIT: Not to shit on this though. I totally believe that some smart mixture of LLM-reasoning + Jev-style + determinism is going to be pretty amazing.
Also see recent discussion https://news.ycombinator.com/item?id=49717558#49718350
At a glance it addresses two out of three of my "load bearing points" against AI, which is the cost to run the things, and that they can be used to generate slop.
If it was trained ethically that would "close the gap".