How to make 'just-right' difficulty — letting a machine fit it to the player (a Canadian study) vs. a human authoring it through meaning (a US developer)

Making "solvable randomness": procedural content and the design of solvability in Google I/O 2026's Save the Date puzzle

One piece today. I read, in the original English, two official Google posts about this year's I/O Save the Date puzzle: "How we built the Google I/O 2026 Save the Date experience" (credited to Kacey Fahey and Caio Avelar, 3 March 2026) on the Google Developers Blog, and "How Googlers built the 2026 I/O save the date puzzle" (by Ari Marini, 6 March) on Google's The Keyword. The annual Save the Date puzzle — this year themed "Make Build Unlock" — is made of five cross-genre games plus a hidden sixth, Dino Pal. What interests me as a design matter is not the promotional shine but how the generated puzzles were kept solvable: Stretchy Cat reportedly uses "a level generation logic based on Hamiltonian pathing to produce random but solvable levels," Nonogram fixes level 1 while generating levels 2-3 on the fly, and Word Wheel generated 100 levels. That is the old, hard problem of generative puzzle design: random does not equal fun or fair. Unable to verify a fresh trusted source within the last few days, I cover this high-profile, first-party piece with its date (March) made explicit — while reading its design claims as a company's own account in what is, after all, a Gemini showcase.