Antimatter – Match the opposites (Mahjong solitaire mechanic)

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I love word association games. Here's a playable wordplay game where you match opposite word tiles. After playtesting a lot of mechanics, I think opposites play really nicely with Mahjong solitaire. The current generation of frontier LLMs can't make puzzles that get much more interesting than hot-vs-big-vs-fast. New inferences keep circling a small pool of concepts unless the prompting has a way to get the LLM into new territories of language. Puzzlemaking needs graph traversals. I made 20 levels algorithmically because I work with a huge semantic graph with over 100M edges, built from manual lexicography and millions of LLM inferences (various models). I keep exploring what can emerge from this graph. The puzzles are randomly selected; reload to see others. The front-end was built with Claude Code. Maybe someday I'll make this into a mobile game, increase the complexity and peril. If you are a gamedev, feel free to dissect it and borrow any parts.

Visit product View on Hacker NewsMar 24, 2026

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, new · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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