Since fable 5 went down just some time ago(although this is no longer the case), a lot of fable or Mythos related content including models and datasets were completely killed from HF, it seemed like such a blow to the local development community to lose such important files, this is what inspired me to work on my project, it's a p2p decentralized distribution network (aka a torrent site) that pulls files from HF and verifies them through sha256, I've been making slow and steady progress but so far I haven't made a single public post about it. I'm genuinely scared of a number of things happening, that the project won't gain traction, ridicule from more experienced developers, I'm also worried about security vulnerabilities which I'm sure I haven't fully patched yet...

How do I get over this fear of talking about my project? How do I gain stars on GitHub, and community engagement? After all, a decentralized distribution network is nothing without its peers...

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[–] TropicalDingdong@lemmy.world 8 points 1 day ago (1 children)

I mean I support this in terms of decentralization. I think lemmy wont be as receptive as they're allergic to AI.

[–] helix@feddit.org 11 points 1 day ago* (last edited 1 day ago) (1 children)

There's a difference between being allergic to AI and being allergic to LLMs shoved everywhere they don't belong. There's good use cases for AI and LLMs in particular, but I have rarely seen it being used well. Most people who unconditionally support AI usage are incompetent idiots who couldn't do anything without AI.

[–] halm@leminal.space 9 points 1 day ago (1 children)

Fully agree with the last bit. And let's be honest when we admit that there are "good use cases for AI and LLMs". None of us here are doing protein folding or crunching other ginormous datasets for science.

Using Claude to write code you don't have the chops to quality check... doesn't really qualify. That's just choosing convenience over safety. "Move fast and break things" as a service.

[–] helix@feddit.org 1 points 1 day ago* (last edited 1 day ago) (2 children)

Using Claude to write code you don’t have the chops to quality check… doesn’t really qualify.

What if I do have the chops to quality check and actually do treat Claude like a junior coder?

I often use it for annoying tasks like "transform this data structure into the one which is specified in the new major version of the upstream API" and write a test before.

It basically saves me typing things and I would need to test my own code anyway. That's one of the good use cases: glorified autocomplete 😅

[–] copygirl@lemmy.blahaj.zone 4 points 1 day ago (1 children)

What if I do have the chops to quality check and actually do treat Claude like a junior coder?

When you have an actual junior coder, they learn over time, including from their mistakes, until they're a senior coder that can do the same for others. When you're "treating Claude like a junior coder", you're just cleaning up after a mostly unchanging system. See also this article by a Zig contributor.

And having AI do annoying tasks (which you then need to double-check if correct anyway) you're missing out on the opportunity to get better at problem solving by skipping the part where you find a programmatic solution, even if it's a one-time thing. (Though when you work on an open source project, it's nice if others can verify how you got to your solution in the first place.)

[–] helix@feddit.org 2 points 23 hours ago

When you’re “treating Claude like a junior coder”, you’re just cleaning up after a mostly unchanging system.

Good point! As soon as I feel like the LLM isn't helping me but instead costs me more time than it saved, I try not to fall into the sunk cost fallacy.

I found it okay-ish to write documentation and fix smaller things which are just annoying chores. It can "learn" to solve the same issue in slightly different contexts if you write proper documentation. Which has the additional benefit that other humans can actually learn from said documentation aswell.

you’re missing out on the opportunity to get better at problem solving by skipping the part where you find a programmatic solution

I'm already pretty good at problem solving. I know how to solve the things I let AI do. I don't need to solve the hundredth similar issue in a slightly different way just to practice, because you don't learn from success, only through trial and error.

As soon as LLMs generate code which I find to be subpar, too fancy, opaque or complicated, I take it as inspiration/challenge and write a better solution. I don't blindly merge LLM generated code. Just like with a junior coder, I don't babysit LLMs, but at some point I'll just do it myself.

As I said, LLMs are basically glorified autocompletion, and anyone thinking they should have them solve problems is on a path to idiocy and incompetence. You're completely correct in stating that one shouldn't become lazy so they don't forget how to actually do their job. That's when you can be replaced by a shell script.

[–] halm@leminal.space 4 points 1 day ago

What if I do have the chops to quality check and actually do treat Claude like a junior coder?

Says every Dunning-Kruger sufferer who don't and can't 😉 I don't need to doubt your skills and dilligence, just those of every lazy hack who whack out slop projects without a second thought.

Sorry, but I think those outnumber capable, security-minded developers by a large factor.