Tw

Twixt – transform one word into another in four moves

Hacker News

Twixt – transform one word into another in four moves

I made this game while working on a different project about teaching English spelling. I was reading about homophones and got struck by how much a homophone can transform the shape of a word, so I started experimenting with little games built on that. I added a few more transforms, anagrams, verb/tense changes, but the answers kept coming out too obvious. I couldn't distort the word enough to make it interesting. The breakthrough was compound pairs. Jumping from one word to another through their compound (sea → horse, via seahorse) really obscures the path and that's when it suddenly got fun and unpredictable. I've been sharing it with friends. I'm in the UK so mostly UK testers, fair warning that a couple of the homophones may lean British. They've been playing daily and seem hooked, so it felt worth posting here. It's one puzzle a day mainly so I actually have time to hand pick puzzles that have a satisfying path. Today's puzzle is on the easy side but they can get really tricky. The name is from 'betwixt', the whole game is about moving between two words. I did clock afterwards that there's a 60s board game with the same name, but they're pretty different things.

Visit product View on Hacker NewsMay 21, 2026

Actual performance

20points

24comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting

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

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

36%36% 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

33%33% 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 · Missing: mac, agents, macos

22%22% 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

15%15% 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.

Incorrect prediction on native model

Similar products

Charlotte NC Movers16%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Charlotte NC Movers specializes in local moves, offering sup

TrackSniff47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find the Music That Moves You

Diver AI56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

See the Market Before It Moves

Indie Hackers1$1,000/moai

Digitalized Word of Mouth

Word2Bits – Quantized Word Vectors44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Word2Bits – Quantized Word Vectors

Probabilistic Spellchecker – You may have misspelled a word33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Probabilistic Spellchecker – You may have misspelled a word

Word.to33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Word.to

EtymologyExplorer – word origin trees52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

EtymologyExplorer – word origin trees

Where I get the last word33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Where I get the last word

Word Slicer42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Word Slicer

Browse all products Analyze your launch