On Thursday, 16 October 2025 at 20:19:56 UTC, monkyyy wrote:
The "zed" free trail is able to write a small d program by
check if it runs and it will compile... but its a free trail
and it auto ran formatting and its a fucking bloated ide, that
makes my fans spin, that is half broken scaling. Etc.
So its probably time to start poking at the open source tooling
and ripping out the stupidity and giving it the d docs directly.
Who's doing what? Whats handles d to some degree?
I know it's not an agent but this is how I use AI.
I am using llama.cpp locally and I run
Qwen3-Coder-30B-A3B-Instruct-Q5_K_M
gpt-oss-20b-Q5_K_M.gguf
gpt-oss-20b-Q4_K_M.gguf
Qwen3-30B-A3B-Thinking-2507-Q6_K.gguf
For my uses, the Qwen models have been the best for D, I aim to
try most models released on huggingface.
But most models do not know D well. It's easy for them to go off
on a tangent and start saying the compiler is too old or the
library is wrong.
Would be really nice to get a fine tuned model on the D language
and library. Generating the documentation in plain text form to
aid training would help.
I use codeblocks for editing and project management, fossil for
source code control.
My workflow is to prepare the query in a codeblocks window and
then paste into llama html query page. If I have a D module that
works and I know it doesn't need modifying, I generate simple
documentation (comments, function signatures) for that module and
paste that instead of the source to reduce context use.
It takes seconds to copy the result paste into codeblocks and hit
build.
I have projects generated that have more than 3k lines of code
over multiple modules. Even if it's simple code the speed at
which the AI can generate the code beats typing.
Regards,
Mark.
