Prompt Apps – Ready-to-Use Generative AI Apps from Prompt

Hacker News

Even if you're not a Prompt whiz, you can still get top-notch results just like the pros. This Product will handle internally handle boring And Cognitively demanding prompt Engineering. Just pick a service, fill in the keywords, and get the desired result! Open Source , Free , Privacy Friendly , Crowd Source Prompts, No Login Required. You can submit Features( https://prompt-apps.canny.io/feature-requests?sort=top ) and Prompts ( https://prompt-apps.canny.io/prompt-conversion?sort=top )

Visit product View on Hacker NewsApr 8, 2023

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

88%88% 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.

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

42%42% 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 · Strong signals: friendly · Missing: plus, platform, intuitive

29%29% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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