Diffusion models are the new cool kid on the block which means a lot of research interest but also a lot of low hanging fruit. I don’t think the ideas of GANs will be completely obsolete though. For example the VAE in stable diffusion is trained using an adversarial loss - without it the decoded images would be much more blurry.

Another important skill is being able to understand what is truly crucial to a solution versus what is nice to have. For example you mention VAEs which are used to encode the images in latent space for stable diffusion etc. Based on some experiments I've done you don't actually need a VAE - a vanilla convolutional auto-encoder is good enough since you don't actually sample from the latents - the diffusion takes care of that.