That's why taking a step back and seeing what's actually hard in the process and bad with the output, felt like it made more sense to chase after, rather than anything else.
FWIW I ran your binary and was pleasantly surprised, but my low expectations probably helped ;)
The next challenge I think would be to prove that no reference implementation code leaked into the produced code. And finally, this being the work product of an AI process you can't claim copyright, but someone else could claim infringement so beware of that little loophole.
I think the focus with LLM-assisted coding for me has been just that, assisted coding, not trying to replace whole people. It's still me and my ideas driving (and my "Good Taste", explained here: https://emsh.cat/good-taste/), the LLM do all the things I find more boring.
> prove that no reference implementation code leaked into the produced code
Hmm, yeah, I'm not 100% sure how to approach this, open to ideas. Basic comparing text feels like it'd be too dumb, using an LLM for it might work, letting it reference other codebase perhaps. Honestly, don't know how I'd do that.
> And finally, this being the work product of an AI process you can't claim copyright, but someone else could claim infringement so beware of that little loophole.
Good point to be aware of, and I guess I by instinct didn't actually add any license to this project. I thought of adding MIT as I usually do, but I didn't actually make any of this so ended up not assigning any license. Worst case scenario, I guess most jurisdictions would deem either no copyright or that I (implicitly) hold copyright. Guess we'll take that if we get there :)