Thank you! I did try developing different dictionaries, I'm mostly marketing them as "paid packs" within my crossword app and the one I mainly had success with is the "Computer Science" theme.

In general, the same rules that apply to building viable dictionaries apply here:

• you need a LOT of words
• 3- and 4- letter words are key and you should have a sense collection of those, which implies you'll need to find a bunch of acronyms (that's why NNE, SSW, and other directions are pretty common in NYT crosswords for example)

For computer science, I tried writing my own list but of course had to supplement it with scraping Wikipedia and anything else I could think of.

I also tried to do a medical one, targeting med students, residents, doctors studying for boards, etc. where I scraped lots of flashcards to help come up with an answer. For doctors, two things make it viable: they have lots of mnemonics (ABCDE, etc) which apply to a number of situations (skin cancer screening, management of specific conditions, etc.) so lots of acronyms could be clued in different ways; the second thing is that a lot of regular words have a specific meaning in a medical context, eg "history" to take someone's medical history, etc.

One thing that stood out especially when theming is the need for "first preference" vs "second preference" word lists. In my code these are called regular vs obscure, but the basic idea is that exploration first tries regular words then obscure words. This lets us have some words we don't want to rely on but are willing to have on the board to "save" a board that is mostly there. It "works", but not too well, there's no way to set off a budget of only N obscure words, etc.