I think I got the last one of those, but mine did come with a “free” phone app to open/close the door. The app turned into an advertising platform about 3 years after I put the opener in - no options out, gotta see the ads if I want to use my opener via app.

Never forget: Han shot first.

When I get an oil change now I also get “three free months” of Sirrius Satellite radio… racket and a half subscription seeking scum.

I purchased a used car from an individual, it had some hacky alarm system spliced in under the dash which malfunctioned quite comically at the grocery store (if it weren’t for the fear of being stranded with a car full of frozen foods) after we had owned the car about a month. That one was such a mess, I managed to identify its components and clip it out, leaving the factory harness undisturbed - would have been a bit more challenging if the system had actually cut some wires that later needed to be re-spliced.

have a larger profile in the surveillance capitalism machine.

This is why, when I’m not watching, I’ll set Netflix to stream movies I like.

Well, aren’t you quaint. Next thing you’ll be asking for is seed corn that you can replant year after year from the corn it grows, heated seats in your cars without a subscription payment, replaceable batteries in your battery powered electronics.

easily looked up via a search engine,

Search engines have been evolving toward chatbots for 20+ years. Ever since they started fighting back against SEO, search engines became more and more opinionated about what they were going to serve and what they were going to ignore. Of course, along the way, most of the advertising supported ones slowly (and not so slowly) succumbed to the financial pressure of a little quid-pro-quo or we take our money elsewhere…

LLMs are going to go the same way, probably much faster. Some, like Grok, didn’t need any pressure put on them at all. https://www.npr.org/2025/07/09/nx-s1-5462609/grok-elon-musk-antisemitic-racist-content

Everybody, everywhere has paid all sorts of services to “polish their online reputation” for decades.

I worked in a building where the entire floor beneath us was full of “reputation repair specialists” who did nothing all day but make people look better online, for money. It’s not surprising that they are being replaced by bots.

what you’re trying to say with arbitrary numbers pulled out of the air about the amount of “coders” and potential users

No matter how wonderful and loved a project (aka business) is, it has expenses. A project like Codeberg’s expenses scale with the number of users and how they use the system.

This policy allows them to get rid of the worst offenders and point to the policy as their reason.

Agreed. However, at the scale they are operating at, I wouldn’t be surprised if they end up using a LLM assisted AI implementation to give them short lists of projects to review as potential “worst offenders”.

It’s like pornography - they’ll know it when they see it.

I think they’re great for what they’re doing, but, truthfully, any “free use” system which has non-zero operating costs for bandwidth and storage is going to have potential problems that can’t be waived away with simple policy statements. 8 billion people on this planet, maybe only 80 million coders, maybe only 8 million active in creation of projects that would end up on Codeberg, but AI probably tripled that number to at least 24 million people, and those people (including myself) are making 3-300x larger projects with AI, not only because they can now, but because AI needs that extra documentation to successfully implement larger projects… just like teams of human programmers do, but AI makes it faster with less humans in the loop.

On the “people count” Github cites 180 million “individual users” but, how many of those are work/home/alt/other accounts of the same person?

Humans with brains will decide on a per-project basis.

This is a good way to clear the “worst of the problems” - but a hopeless whack-a-mole task to get rid of problems altogether.

I’ve got a blockchain based project - hosted on Codeberg no less - that has nothing like an ICO or other get rich quick scheme attached, it’s about as sincere of an open transaction processing platform as you can get.

But a quick read will come away with “this is a Cryptocurrency project” - so… am I banned? Even worse, although I started it 8 years ago, I made a quick pass with Claude code recently to clean things up and implement some of the lagging parts… now I’m double-banned from Codeberg, right?

I’m glad they have principles, but one-word labels are really inadequate to separate “good” from “bad” - it’s almost always more complicated than that.

I just don’t see how an open resource like Codeberg could possibly economically make even the smallest of dents in their slop problems without using some automated methods themselves. Even if it’s entirely human driven decisions, they’ll be making mistakes. Will they be like Google and render themselves deaf to appeals?

I can see them having problems / frustration with terabytes of junk showing up 10x faster than it used to because people have the new text generation tools and are just spewing massive “projects” of no value with them, and I would assume when they find an account that’s full of this junk they want to trim it out of their running expenses (consider that they’re also going to be crawled by stealth trainers who read everything they have publicly available)… but, then… no matter how they go about identifying “junk” there will be false positives.

I have some projects I initially wrote over 20 years ago that I like to look back at and tweak around a little every now and then… even if nobody has looked at a project for years, that doesn’t really mean nobody cares about it - so algorithms for activity are going to hit stuff like that.

Billy the graphic designer that never coded “makes” an app using Claude, he is vibe coding

See, I don’t know Billy, and I don’t know what his app looks like. If Billy is a logically thinking, good graphic designer who communicates well with his clients, understands what they want, and can express all that in logically coherent statements, Billy’s first app using LLMs might be great. Probably not, but it stands a chance. Everybody starts somewhere.

If Billy just says "hey, like, I want an app that runs on Android and iPhone and desktops too, and I want it to do this list of random stuff, some of which is internally conflicting, and while I’m at it I’m going to spec that I want it in Scala, because reptiles are cool (like cold blooded, get it?) Yeah, Billy’s first app is only likely to be awesome for Billy.

Now, when I fire up Claude Fable and ask it to make me a webserver in Python, how does Codeberg determine if my app is “Vibe coded” or not?

As someone who can code, has coded for 40 years for a living, I’ll say: LLMs can be heavily abused to write a lot of garbage. I’ll also say: give a human enough time, and they can write almost as much garbage but they usually get discouraged by all the errors and crashes and have the good sense to give up - but these humans armed with LLMs can at least make stuff that runs.

I’ll also say: LLMs can be used as very effective tools, if you exercise the kind of care and planning that has always been required to write “good” (whatever your definition of “good” may be) software. They do speed up development - some development ends up in a good place, some… not so much. It was always like this even long before LLMs, but LLMs help get to those endpoints much faster.

And: false positives? How much fun is it to go to clone your repo and find it locked because something (probably an AI algorithm) decided your project was “vibe coded”?

What I want to know is: if you’ve got a product that has been market tested and proven for a decade to be creepy, why do you pick a celebrity with a creepy dad to promote it? Are they just trying to own that sliver of market share that doesn’t care?

What AI “decision making” does in our processes is: write the reports exactly like the procedure says they should be written, and fills them with whatever you want to hear - looking up convenient references to back up your opinions. You probably should double check the references yourself to be sure they actually exist (though I think AI is getting better at checking its own work for things like this lately) - but… yeah. Ask it once and it will give you “an opinion” that doesn’t take into account all of the factors that matter to you. So, as you explain all the factors, it also becomes obvious what you want to hear, so after several rounds the obliging AI eventually not only “sees things your way” but can pile on the BS as deep as you ask it to to back up those opinions. What would have taken days to research and write can be done in an hour or so.