Current trends in GenAI

I was reading a book “Hands on large language Model” – i do read many papers before too but there is always something that you miss out on as papers are just complex often undermining basics. In this book, i am seeing many topics which seem outdated. As i started studying modern ML (transformer based ML) just this year, i wanted to ask if certain topics are still relevant for today?

Training an embedding model and benchmarking an embedding model? (Until now, i have only used pre trained embedding models never did my own benchmarking)

If i am making an email spam or not spam classifier for an AI app, would you prefer to use model directly or prefer to pretrain it?

If you would like to pretrain it, where would you get your data from? Maybe from huggingface?

Feel free to add any other suggestions. I can already make agentic apps, can kind of train transformers as well. My target is to learn how to use these models even more effectively by learning pre training or any other concepts (maybe revise prompt engineering as well). Any other topic, I shouldn’t miss is also welcome.