Comment by bsenftner

Of course, what I do with the data using an LLM is separate and can be complex. I have written my own prompting framework I call "method actor promoting" that has two layers: first I tell the LLM that it is a method actor, using the formal terms method actors use. This creates an impersonating LLM that goes further, goes deeper in the impersonation than just a plain LLM. Then I tell that "method actor" the role they are playing is a subject matter expert in whatever it is that the user is trying to do. Then communicating with that LLM Agent requires the user to actually treat them as if the are that expert, and when interacting with them using the terms and language that expert would expect when discussing their professional vocation.

My prompts are larger than most, but my replies from the LLMs tends to be very high quality.

I've also written what I call "chatbotBot" a chatbot that will conversationally gleam from the user a new agent they need, and then chatbotBot writes that new agent, or modifies an existing agent to suit, and then integrates that into the system for immediate use. Then there's "agent morphing" where an agent can have their knowledge and skills morphed to another set of knowledge and skills - which is very useful for some of the more complex agents (the spreadsheet agents) that have complex prompts and are difficult to modify.

You can check this out for yourself at https://midombot.com/b1/home I'm building in public, more or less, with little to no fanfare. What you see was all hand coded by my, except for the word processor and spreadsheet tools, which as I've describe above, I've heavily modified. I do not use AI coding tools, I find they do not help. But I do have multiple coding 'bots I've written that I converse with all the time about the strategy of coding.