I

I made prompts creation an easy process with ArtisMind

Hacker News

I made prompts creation an easy process with ArtisMind

Hey HN, I’m a new solopreneur, and this is one of my first public launches. While building AI products, I kept running into the same issue - spending endless hours crafting prompts, fixing broken outputs, and worrying about security. I realized that writing prompts manually wasn’t scalable or safe. So I built ArtisMind - a tool that helps you engineer prompts, not just write them. It generates clear requirements, builds structured prompts using multiple AI models, tests them for quality and security, and even lets you add context files for better accuracy. Now I use it daily for my projects, and it’s saving me tons of time and frustration. It started as a small fix for my own pain - but I hope it helps others too. Would love your feedback, Sebastian

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
89%89% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
57%57% 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
42%42% 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
32%32% 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.
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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