It is both subtle and obvious, yet many are missing this: if you want/need a deep subject matter expert in virtually any subject, write a narrative biography describing your expert using the same language that expert would use to describe themselves; this generates a context within the LLM carrying that subject matter expertise, and now significantly higher quality responses are generated. Duplicate this process for several instances of your LLM, creating a home brewed collection of experts, and have them collectively respond to one's prompts as a group privately, and then present their best solution. Now there is a method of generating higher reliability responses. Now turn to the fact that the LLMs are trained on an Internet corpus of data that contains the documentation and support forums for every major software application; using the building blocks described so far, it is not difficult at all to create agents that sit between the user and pretty much every popular software application and act as co-authors with the user helping them use that application.
I have integrated 6 independent, specialized "AI attorneys" into a project management system where they are collaborating with "AI web developers", "AI creative writers", "AI spreadsheet gurus", "AI negotiators", "AI financial analysts" and an "AI educational psychologist" that looks at the user, the nature and quality of their requests, and makes a determination of how much help the user really needs, modulating how much help the other agents provide.
I've got a separate implementation that is all home solar do-it-yourself, that can guide someone from nothing all the way to their own self made home solar setup.
Currently working on a new version that exposes my agent creation UI with a boatload of documentation, aimed at general consumers. If one can write well, as in write quality prose, that person can completely master using these LLMs to superior results.