Lisp in Five Days

Hacker News

Lisp in Five Days

Hi HN! I kept hearing about Lisp and why it was special but didn't have a great place to start. I wanted something self-contained that helped me develop intuition rather than fluency. My hope is this is helpful for casual programmers, professionals from other fields who interact with code, or engineers who haven't had much exposure to interpreters or compilers. Hope this helps anyone else who's curious about getting a sense of Lisp and what makes it special with a limited time investment! Feedback or other cool Lisp things welcome :)

Visit product View on Hacker NewsApr 1, 2022

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Actual performance

9points

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

59%59% 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 · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

22%22% 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

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.

Correct prediction on native model

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