To

Tour of CLIPS

Hacker News

Tour of CLIPS

Learn how to write Rules Engines with CLIPS in your browser! I found the Tour of Go super useful when learning Go, so I went for something similar for evangelizing the awesomeness of CLIPS. A few things I'm proud of with this project: - No front-end frameworks - Compiled WASM binary; your code isn't sent to a back-end server - Code editor/syntax highlighter written from scratch (that I'm sure you'll find bugs in ;)) This is my first attempt at this, and I'd like to expand on it in the future. Let me know what you think! About CLIPS: CLIPS is a programming language useful for building Rules Engines and Expert Systems. It's written in C, so it's pretty darned easy to put data in/get data out from other languages written in C. It was started in the mid-80s at NASA, and it was released to the public in the mid-90s. It's still in active development by the original developer.

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Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
21%21% 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.

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