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Pegasus3301 – a Cicada 3301–inspired online puzzle game

Hacker News

Pegasus3301 – a Cicada 3301–inspired online puzzle game

Hi HN, I built Pegasus3301, an online puzzle game inspired by Cicada 3301. It’s a multi-stage challenge that mixes ciphers, hidden clues, logic problems, and misdirection. Each stage unlocks the next, and most of the puzzles rely on observation rather than brute force. I built this as an experiment in puzzle design and player behavior. It runs entirely in the browser and is free to play. I’d really appreciate feedback—especially on puzzle clarity, difficulty balance, and whether the progression feels fair. Link: https://pegasus3301.com/

Visit product View on Hacker NewsJan 28, 2026

Actual performance

4points

14comments

Did not reach leaderboard

Launch Intel predictions

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

75%75% 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.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% 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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

6%6% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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