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PawnPush, daily chess bots with unique personalities and play styles

Hacker News

PawnPush, daily chess bots with unique personalities and play styles

Hi all, I set up PawnPush as a way to have a fun daily chess challenge kind of like Wordle or the other NYT games. Maybe I'm in the minority, I often enjoy playing character-based chess bots more than live games because finding time to play focused and uninterrupted is difficult and stressful with work and kids. I've beat all the chess.com bots (at least the ones I can beat at my level), so I was out of challengers. But just playing an engine that plays the same each time and destroys me is boring. So I tried to come up with a way to have different characters to play against each day. I set up the site so there's a new chess bot to play each day at midnight with a unique name, personality and play style. Based on their backstory, they'll use different openings, prefer different pieces, get flustered more or less, and stuff like that. Plus, I get to have the fun of coming up with dumb ideas for new characters. It was a fun little project to put together. Let me know if anyone else is into this kind of thing.

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: plus · Missing: platform, intuitive, reviews
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, open · Missing: mac, agents, macos
41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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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