I use gemini and cursor for enterprise software implementation, but they often suggest incorrect solutions to edge cases and unique config requirements. An AI that has a higher likelihood of being accurate is very appealing. I'll give Sup AI at try over the next few days at work.
Also, discovering HLE was great... scrolling through some of the questions brings back memories of college organic chem.
I've felt your pain. Models aren't always trained well enough on edge cases and configs.
Would love to hear how Sup works out for you.