Why is AI training still so unfriendly for normal users?

Genuine question. Why does almost every AI training setup still feel extremely engineer-focused? Most tools I’ve tried expect people to already understand things like: CUDA VRAM LoRA settings Docker dependency issues quantization optimizers terminal commands training configs Even simple fine-tuning workflows become confusing fast. I’ve been thinking a lot about whether there’s room for a much more beginner-friendly approach where users could basically: upload dataset → train → test → deploy while the system handles things like: GPU selection safe limits preventing huge billing mistakes deployment setup logs model storage Do people here actually want simpler AI training workflows, or do most users eventually learn the technical side anyway? Curious what the biggest pain points are for people who’ve tried training models themselves.