Comment by sysmax
5 days ago
Most of the AI hiccups come from the sequential nature of generating responses. It gets to a spot where adhering to code structure means token X, and fulfilling some common sense requirement means token Y, so it picks X and the rest of the reply is screwed.
You can get way better results with incremental refinement. Refine brief prompt into detailed description. Refine description into requirements. Refine requirements into specific steps. Refine steps into modified code.
I am currently experimenting with several GUI options for this workflow. Feel free to reach out to me if you want to try it out.
hello, im interested in the GUI options you mentioned!
Cool. The part that is released already is described here [0]. You can point at some code and give brief instructions, and it will ask the model to expand them, giving several options.
E.g. if you point at a vector class and just "Distance()" for prompt, it will make assumptions like "you want to add a function calculating distance from (0,0)", "function calculating distance between 2 vectors", etc. It runs pretty fast with models like LLaMA, so you can get small routine edits done much faster than by hand.
The part I am currently experimenting with are one-click commands like "expand" or "I don't like the selected part. Give me other options for it". I think, I'll get it to a mostly usable state around Monday. Feel free to shoot an email to the address in the contact page and I'll send you a link to the experimental build.
[0] https://sysprogs.com/CodeVROOM/documentation/concepts/planni...