I find they're pretty good at some coding tasks. For example, it's very easy to make a reasonable UI given a sample JSON payload you might get from an endpoint. They're good at doing stuff like crafting farily complex SQL queries or making shell scripts. As long as the task is reasonably focused, they tend to get it right a lot of the time. I find they're also useful for discovering language features working with languages I'm not as familiar with. I also find LLMs are great at translation and transcribing images. They're also useful for summaries and finding information within documents, including codebases. I've found it makes it a lot easier to search through papers where you might want to find relationships between concepts or definitions for things. They're also good at subtitle generation and well as doing text to speech tasks. Another task I find they're great at is proofreading and providing suggestions for phrasing. They can also make a good sounding board. If there's a topic you understand, and you just want to bounce ideas off, it's great to be able to talk through that with a LLM. Often the output it produces can stimulate a new idea in my head. I also use LLM as a tutor when I practice Chinese, they're great for doing free form conversational practice when learning a new language. These are a just a few areas I use LLMs in on nearly daily basis now.