Li

Liz – Collaborative Lisp coding on Discord

Hacker News

Liz – Collaborative Lisp coding on Discord

This is a Discord bot I made, which lets you write and evaluate Lisp code in collaborative sessions on Discord. I wrote it in a short amount of time, partly for learning purposes, but also because I found the idea exciting and it was fun to hack around. I'd be happy to get your feedback, especially on how to improve the deletion mechanism (maybe make deletion sexpr-based?). I've tried to make the README detailed enough so that it's easy to make some changes and run your own version.

Visit product View on Hacker NewsSep 18, 2023

Actual performance

44points

10comments

Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: coding, code · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% 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

34%34% 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

18%18% 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.

Incorrect prediction on native model

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