FlipJump – I Created a Programming Language

Hacker News

Hi all! I built FlipJump, a programming language with just 1 opcode, yet capable of any computation. It started with thinking of the idea of the minimalistic language, but it's more than that - I had to set up the whole environment for it: I have written a macro-assembler, an interpreter for the binary, and a very extensive standard library. I also written about ~30 programs in it. Also, the standard library is tested. I also wrote an esolangs page: https://esolangs.org/wiki/FlipJump Tell me what you think!

Visit product View on Hacker NewsFeb 19, 2023

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, 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

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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