Is anyone using an AI product for coding with any success?

I ask this question after two recent incidents:

(1) I was searching google for answers to an issue compiling an older, abandoned FOSS C project... I am not fluent in C... and wound up
interacting with Gemini. It got me on the right track in the sense that we fixed the compile error (caused by compiler and library updates) and got it running.
(2) reading about and using Claude's BBS, which was apparently written with
the assistance of AI.

In my personal case, I found that Gemini was good up to a point, but had trouble remembering what we were working on after a while -- after we got
into the weeds about squashing some memory leaks. We got sidetracked a little and then it completely forgot what we were doing. It also hallucinated
some.

However, after interacting with Claude's BBS and seeing what it looks like,
I have a very old C project (DOS!) that I wouldn't mind running by some
other AI product to see if it could help me fix a nagging bug. I also have a few other ideas I wouldn't mind trying out.

So I am wondering if anyone has had success with AI, which AI, free or
paid, and maybe if it is some AI that you are hosting yourself (and, if so,
is it linux based?)?

Thanks!


* SLMR 2.1a * A seminar on Time Travel will be held 2 weeks ago....
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Re: Using AI for coding
By: Dumas Walker to ALL on Fri Feb 20 2026 10:17 am

Is anyone using an AI product for coding with any success?
In my personal case, I found that Gemini was good up to a point, but had trouble remembering what we were working on after a while -- after we got into the weeds about squashing some memory leaks. We got sidetracked a little and then it completely forgot what we were doing. It also hallucinated
some.

Sounds like you need to raise the tokens so it can remember what you are doing.

So I am wondering if anyone has had success with AI, which AI, free or
paid, and maybe if it is some AI that you are hosting yourself (and, if so, is it linux based?)?

I host locally using llama.cpp on a i9 64 GB ram Dell 5280 workstation and two RTX 3060 GPUs with 12 GB each. llama.cpp utilizes both GPUs to give me a combined 24 GB of vram. I created a new door called Quantasia that uses both cloud and local LLMs, and I like the response times of llama.cpp that Quantasia achieves when hitting a local bot based on it.

Lonewolf
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