Constraints all the way down

Hey 👋 — today's mix leans into making things without hand-crafting every piece: procedurally generated puzzles, code-as-design, and a growing pile of AI reflections both dead serious and delightfully not. Let's get into it.

From constraint models to playable puzzle games

From constraint models to playable puzzle games

A researcher who once generated 434,201 Sudoku instances for a constraint-programming paper has turned that machinery into a whole arcade of puzzles — Sudoku, Nonogram, Queens, Zip, Loopy, Tents, Patches, and more — all produced from constraint models rather than levels somebody sat down and designed by hand. It's a neat inversion: instead of writing a solver for existing puzzles, you write the constraints once and let them spit out infinite, guaranteed-solvable levels across an entire genre. The write-up walks through how the same underlying technique generalizes across such different puzzle shapes, which is the part worth lingering on if you've ever wondered whether puzzle design is really just constraint satisfaction wearing a costume. (via Lobsters discussion)

Introduction to shaders

While we're on the subject of building things from first principles — this is a from-scratch video primer on shaders, useful if GLSL still looks like a wall of noise to you (unverified — no transcript available, just take the HN crowd's word for it). (via HN discussion)

Designs everything in code now

Designs everything in code now

A designer at Cursor describes abandoning traditional design tools entirely, doing interfaces, graphics, and animation straight in code with AI agents doing the typing. The reasoning leans on Bret Victor's old complaint about feedback-loop friction — if code-plus-agent closes that loop faster than Figma does, why keep the middleman around. Whether that holds up outside a company built by and for coders is an open question, but it's a sharp articulation of where the craft might be drifting.

I'm leaving OpenAI to build Jurassic Park

A pitch-perfect spoof of the startup-departure genre, complete with mock "cyberdefense capabilities," sustainability charts, and a straight-faced plan to resurrect dinosaurs as a hedge against misaligned AI. It's silly on its face, but the send-up lands because it's aimed so precisely at the real genre it's mocking. (via Lobsters discussion)

The tokenpocalypse is here: companies are scrambling to stop spending so much on AI

Buried in Simon Willison's linkblog is a small, telling anecdote: at Accenture, the single biggest driver of LLM token spending isn't engineers generating code — it's employees converting PDFs into markdown. Sometimes the most expensive use of a frontier model turns out to be the most mundane one.

Quick hits

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