cross-posted from: https://lemmy.world/post/49193875
DConf2026 mostly has proAI talks, with the biggest standout being Adam Wilson’s talk about integrating LLMs into developing the next version of the standard library.
This lead to a lot of debate within the community, with even some pro-genAI people calling it out, and there’s even an open letter calling for rethinking the use of genAI, and some increased interest in the OpenD fork. It is also found out that people did try to volunteer for the new standard library (including me), but were rejected with the excuse of “we already have things in the works”.
I’m also interested into some D alternatives that’s not Rust (🤮🤮🤮🤮🤮 - no I’m not a Lunduke fan, but a gamedev, also no “const by default” languages!), has metaprogramming capabilities, and no (mandatory) header files (🤮🤮🤮🤮🤮), in case I decide to leave. I have a game engine that could be ported, its resource management needs to decoupled for D’s garbage collection though.


God yes I can relate to that. I have a similar “full vibe-coder” coworker who sent me a PR for something that amounted to 1,000’s of lines of code changes. I rejected it out-of-hand. We had a long conversation about readable PRs, breaking work up into chunks, etc. Of course he had Claude do all that for him but… at least the PR was “better”.
And the same trouble with him not having any clue what he just produced actually did. I 100% agree that’s a problem. But it’s kinda the same problem we had before LLM, though maybe a bit super-charged. That fella’s code before Claude was terrible as well. So technically the code itself is better now so… I guess that’s a win?
Yeah - give bad drivers faster cars and people will die faster. I hear that. We do need to train people better on how to use these tools. It’s definitely NOT “go vibe code a thing into existence and then drop it on others to maintain”. But I don’t think “bury your head in the sand and hope it goes away” is the right approach either.
Sure. But you can do that with LLMs too. They have strengths and weaknesses as well. But to understand how to use these tools appropriately you need to gain experience with them. To know when they tend to produce good results (well known and well documented languages and libraries) and when to be more “sus” about them (obscure libraries, poorly documented applications (coughOraclecough)).
The more you use them the more you get to see when it’s struggling.