For anyone browsing Malachain, here is a clear starting point on the subject.
A large language model is a program trained on a very large collection of text to predict which word is likely to come next. By repeating that prediction many times it can write paragraphs, answer questions and summarise documents. It does not look facts up the way a search engine does unless it is connected to one, which is why it can sound confident and still be wrong.
Used well, these tools are good at drafting, rephrasing and explaining ideas in simpler words. Treat their output as a first draft from a fast but unreliable assistant. Check names, numbers and quotations against a trusted source, avoid pasting private or confidential information into public services, and say when a text was produced with help from such a tool.
If you try any of these ideas, start small and adjust them to your own situation. What works for one person will not suit everyone, and it is fine to keep only the parts that help. Writing down what you changed, and what happened, makes it much easier to see after a few weeks whether the effort was worthwhile.
The most useful step is usually the first one. Pick a single suggestion, try it for a couple of weeks, and then decide whether it is worth keeping. Small, steady improvements last longer than ambitious plans that are hard to maintain once everyday life gets busy again.
It also helps to talk the subject through with friends or colleagues who have tried something similar. Their experience points out the details that guides leave out: how long things really take, which costs were unexpected, and which shortcuts turned out to be a mistake.