You’ve made a few of erroneous conjectures which are orthogonal to my argument. But I’ll call out one: LLM is bad at code completion and it’s use not have to be limited to (final) code writing. Thus my theses on “what” vs “how”
OSS projects have already started to recognize that LLM is just a tool and how you use that tool matters a lot more than whether you are using said tool at all. Lets bring StackOverflow for analogy: we didn’t ban browsers for code development because one can navigate to StackOverflow and copy-paste some really crappy code. LLMs are SO on steroids (actually trained on SO topics). So grabbing LLM to get a sense of direction or shape is an OK use in general, but copy-pasting it’s results blindly is silly and dangerous.
There’s a second argument that AI is ruining OSS communities which I believe is true, but refusing to accept AI code is a self-defeating action. Why? Because AI training needs unadulterated source of knowledge, one not tainted with AI and OSS communities rejecting AI would be that source. Also: if OSS community did not use AI it would hardly stop it from continuing it’s growth in Enterprise. So there’s not much of a winning strategy there either.
Which brings us to GrapheneOS decision and given above reasons I think it’s a well-balanced decision.
From reading about Omarchy and community reactions it sounds like DHH is a successful grifter, milking money from corps with pictures of agentic promised land. HOWEVER grift will go bust at some point: does anyone remember SaaSpocalipse that did not materialize,along with numerous articles from people with degrees pointing out that there’s no data supporting claim that AI is actually making money for it’s peddlers or consumers. AI grifts will continue until “market” will finally acknowledge it for what it is (it’s just a new shiny tool, no more) and all the myths go bust and investors will want their money back. So - yes money got “stolen” from actual OSS projects that keep world’s lights on, yes vibecoding has not been proven to scale or endure multiple decades like Debian, Gentoo, Fedora etc. so it’ll collapse from technical standpoint, but it WILL collapse unless DHH will start applying those grants towards hiring engineers. Token money are not worth paper they are printed on so everybody just chill and let this trainwreck go off the cliff on it’s own. Shame DO got into it though… but for all the major cloud platforms who isn’t supporting fascism? What differs is the scale.
your points support my statement though: how vs what is the real question here. LLM is fine performing repetitive mundane tasks that we find boring and uninteresting. Like refactoring small chunks of code out or “search and replace” when context matters more than matching string etc. Also, let’s assume someone had enough bitcoin mining gear laying about to repurpose it into LLM training infra and trains his/her small model on stuff they care for, suddenly we lose all the other arguments and use of LLM becomes more acceptable. So blanket ban at this point is not going to achieve any of the goals, really. Consider that majority of developers were mandated to use LLMs for work, consequently their skill shape changed, for project to draw from that pool of developers you need to offer comparable tools.
Context matters too: Graphene has to deal with AOSP, which lost it’s development transparency a while ago and Graphene developers likely have to contend with big (likely LLM-generated) code dumps within mainline AOSP with each new release, so to keep up with that onslaught they either need to expand developer base (and we just said that pool is shrinking) or leverage LLM to cut through that mess. Again “how” tool is used matters a great deal.