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Huewords, a Word and Logic Puzzle

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Huewords, a Word and Logic Puzzle

This is a game I wrote over the last month and a bit. The effort allocation was pretty different from what I've done in the past. The game design snapped together very quickly: I had the initial idea, played a couple of games on a spreadsheet to get a feel for the idea, and made one change based on those plays. After that everything felt just right through multiple rounds of playtesting. Likewise the puzzle generation is nowhere near as elaborate as in my previous game, fairly simple methods worked well and provided good variety. Instead I ended up spending silly amounts of time on curating the word list (including using LLMs to guide the curation) and on iterating on the UI. The basic UI concept never changed, but the details basically never survived for very long after starting a new playtest round.

Visit productView on Hacker NewsMay 22, 2024
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Actual performance

3points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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