Zero to Hero – A Haskell Puzzle Game

Hacker News

Hi HN. I am a researcher from Monash University. For one of our projects, we made a Haskell puzzle game called Zero to Hero. I invite you to try out the puzzles and share your thoughts (optional). The game contains 10 unique puzzles; each challenges you to implement a seemingly impossible function. You will seek help from a handful of strange-looking helper functions and your own wits. The game starts easy but quickly escalates into madness. The game requires you to be comfortable with basic Haskell syntax to progress. But no other prior knowledge is needed. You can choose to participate in our study or play for fun without any data collection at all. No stress. More details are explained on the landing page. https://zerotohero.fly.dev/ Go ahead and enjoy the puzzles!

Visit product View on Hacker NewsDec 4, 2023

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

69%69% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% 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

16%16% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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