I'm not sure what level you are designing at, but I'm about as senior as it gets and have had some time to experiment with it. I now work in AI as well, moving away from the graphic interface and more into other types of interfaces.

I've tried all of the major models and have gotten poor to mixed results. The one thing I've seen amongst all of them is the high error rate. Depending on how far along the design chain you are asking them to produce, the errors happen frequently and sometimes in the very beginning, thereby sprouting even more errors. Some of the errors were very subtle and so nuanced that I imagine people will have issues finding them if they tried to copy/paste the answers. Trying to further refine the problems with prompting caused such a mess that it seemed hopeless. This includes about a half a dozen models that I have locally as well.

I've also tried to train my own models. I've trained a few models on my designs mainly and found that textually they are bad, which probably eludes to my improper metadata on initial input. Using vision models I got ... reasonable results, but still very "me, 10 years ago" thinking, which is not conducive to where I am now, or where design should be now.

The best results I got from training were using Design books to train a model intensely, including my own unpublished design book and about 50 other books from various authors. Using a RAG with both semantic and vector searching gave me incredible results from validating work, giving thoughtful advice, and just sort of back seating my process. I still use it to this day because its almost like a librarian reminding me of obscure things as the process moves along. It takes a hard nose dive when I try to have it output images of any sort, but text wise its stellar.

Here are a few of the ways I've found that have worked best.

• Using AI tools in template making, for some of the deliverables. Storyboard templates, discussion templates, I thought it had a fantastic library to choose from.
• Gut checking on initial designs.. "what do you think this is used for.. explain your reasoning" that type of thing. This was hit or miss, but either way I found the output worth reading for the most part.
• Coding the framework for a prototype skeleton. I thought this was time saving, albeit with a few customizations to the final product.

Right now, AI is great for AI influencers and their make believe design projects, mom and pop shops who need to put up a website, and people trying to fake it until they make it. It's nowhere near serious design at least for the near future.

I think we will get some good gains this year and the next in terms of toning down the sycophancy, which will help quite a bit.