[ematth]

Hey Brian, I really enjoyed reading your work on the Pips game! I found myself applying a similar backtracking algorithm to my Pythonic solution (https://github.com/ematth/pips). I focused on finding a single solution for each puzzle as opposed to all possible solutions. For hard puzzles with longer run times, I found that running multiple processes, each with the domino list shuffled, gets the solve time down to <15 seconds.

[brianberns]

Thanks! I'm glad to see I'm not the only one who went down this rabbit hole. :)

I considered parallelizing my solution as well, but the problem is that it only gives a linear speedup, while the problem space increases exponentially. I decided to focus on pruning the search tree instead, and that seemed to work pretty well (after much thinking).

[prb]

It's getting crowded down here in the rabbithole... One more to peek at: https://github.com/prb/pips-solver/blob/main/README.md

[tzs]

  Last updated 2025-10-27.
  [...]

  The puzzles with the most solutions are:


  • 2025-09-15 hard: 2,764,800 solutions
  • 2025-10-05 hard: 344 solutions
  • 2025-09-30 hard: 110 solutions
  • 2025-09-04 hard: 86 solutions
  • 2025-08-23 hard: 80 solutions

Hah...it's like the NYT was just waiting for you to update so they could immediately release a puzzle that makes your list out of date. 2025-10-28 hard has 166 724 solutions.

[munchler]

That's great! Your experience with the 2025-09-15 and 2025-10-14 puzzles was very similar to mine, I think. I'm impressed that you were able to get AI models to solve this game effectively. I coded it the old-fashioned way myself, mostly, with occasional help from Gemini Pro.

[prb]

I did write the spec first — data model, algorithm, etc. That may have helped the agents get traction.