I built a strategic PvP word game where each move is just one letter

Hacker News

When I was in school, my teacher used to play this game to our class. You add one letter turnwise and try to make a word. Later, I tried searching for this game but didn't find the exact match anywhere. The closest was Scrabble, but it was too complicated. So, I decided to build my own. I did make some modifications to make the game more challenging and fun. Back then, we would start with a blank board and also score 2 letter words. Here, the game gets prefilled with random letters so the game becomes more different each time. No scoring for two letter words. The best thing that I added was the combos. If your letter makes 2 or more words, you will get a multiplier for each subsequent word, so the challenge becomes finding a way to score more combos. And I also added daily puzzles where you get 5 boards, and you need to find the best spot and best letter that scores the most. You can share the Wordle-like result to your friends.

Visit product View on Hacker NewsJun 28, 2026

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Did not reach leaderboard

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

65%65% 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.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

47%47% 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

39%39% 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, io · Missing: https docs, excited, just released

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

15%15% predicted probability of success on Product Hunt, 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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