Building that site was a fun experiment.
I hope eventually someone has the time and inclination to do it far better than I did. That site was built back when all I had was pure policy nets, with the one key detail being to give the player rank as an input to the net to try to teach the net about how players of different ranks play and how their moves might differ on average, to try to determine some idea of the "rank" of a problem. I haven't revisited this idea since.
In addition to improving the "rank" heuristics, maybe bigger nets and more data could be much better. The nets weren't that large by today's standards. And it was before I started seriously experimenting with how to integrate a net with search to actually produce high-quality evaluations. So the site is relying heavily on just "this was the move the pro or high-dan amateur played" without the ability to back it up with independent AI evaluation - whether to verify the goodness of the move, or even just to show more context to the user and/or give feedback about answers besides the pro move.
I do think it still came out well given the amount of effort it involved and the limitations I had at the time.
And I hope at least a few people have found it useful. A lot of the problems turned out to be good "follow basic instinct" practice (https://senseis.xmp.net/?BasicInstinct) which hopefully can be educational if you're a beginner unfamiliar some of the basic instinct moves in practical open-space situations.
I really like the problems. Thanks, lightvector!