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.
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.
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".
I wish they'd just use Astra instead. It doesn't write this awful prose.
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".
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.
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
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...
LLMs are an additional way to generate code, but it's not like code generation or "low-code" tools are a new thing that made compilers and programming languages obsolete.
LLMs "just" allow to provide the code generation input directly in human language. But whether providing such a specification in "sloppy" human language instead of a precise specification language is actually a good thing for long term projects is still arguable (as convenient as it is).
Mathematicians and engineers invented their own precise "DSLs" (e.g. math notation and blueprints) for exactly this reason, and high-level programming languages are nothing else than "specification languages" that don't leave room for the ambiguities of "natural languages", and it's still not clear to me how having both a natural language specification and a precise specification in form of source code side by side can be considered a good thing. It's easy to say of course that the "natural language specification" is the single source of truth and the source code is a throwaway output artifact, but then you're back at having a specification written in a language that's useless for expressing precise intent.
(and this is also the fundamental difference between compilers and LLMs and why I believe that comparing LLMs to compilers is wrong: determinism. The output artifacts of a compiler are literally throw away. Nobody in their right mind would commit object files into version control, while nobody in their right mind would not commit the source files generated by LLMs into version control, because creating the source files from scratch would yield different results on each run).
Releasing the harness as part of LLM-generated projects still makes sense of course :)
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.
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.
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.