I found this article a bit disappointing.<p>The link at the bottom doesn’t work.<p>The grids shown do not follow the well-known rules of (American) crosswords: every square is part of two words of three or more letters each.<p>Coming up with a pattern of black squares, and writing good clues, are two parts of making a crossword puzzle that are IMO fun and benefit from a human touch, and are not overly difficult. There are also databases of past clues used in crossword puzzles (eg every NY Times clue ever, and various crossword dictionaries) for reference and possible training. If you don’t care about originality (or copyright) and want quality clues, you can just pull clues from these. If you do care about all those things, you can surface the list of clues used in the past to the human constructor and let them write the final clue. Or you can try to perfect LLM clue-writing. In my experience, LLMs are terrible at clues. Like sometimes if I try to give it feedback about a clue, it will just work the feedback into the clue… it’s a little hard to describe without an example, but basically it doesn’t seem to understand the requirements of a clue and the process of a solver looking at a clue and trying to come up with an answer.<p>Coming up with an interlocking set of fun, high-quality words and phrases is the hard part. I agree that LLM wordlist curation is a great idea, and I started playing around with that once.<p>Beyond that, I don’t think LLMs can help with grid construction, which is a more classic combinatorial problem.