This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
For the svg generation, it would be an interesting experiment to seed it with increasingly poor initial images and see at what point if any the models don’t anchor on the initial image and just try something else
Hi Simon, it is very likely that I am misunderstanding your comment, however:
Do you use chatbot UIs like chatgtp.com, claudi.ai, LibreChat for coding, instead of something Cursor, Windsurf, Kiro, etc?
If that is the case, I am really curious about this. Or, did you just mean for benchmarking various models via simple chat UIs?
In either case case I'll often reset the context by starting a new session.
The whole "context engineering" concept is certainly a thing, though I do dislike throwing around the word "engineer" all willy-nilly like that. :)
In any case, thanks for the response. I just wanted to make sure that I was not missing something.
I’d be curious if the approach would be improved by having the model generate a full pelican from scratch each time and having it judge which variation is an improvement. Or if something should be altered in each loop, perhaps it should be the prompt instead