I made a zero-commission AI prompt marketplace

Hacker News

I'm the creator of https://promptstand.io , a new platform that lets creators, devs, and AI prompt engineers sell their digital goods, without giving up 10-30% in fees to marketplaces like Gumroad. PromptStand is subscription-based, not commission-based, so you keep what you earn. It’s designed for technical users who want speed, flexibility, and control over how they monetize their prompts, templates, or downloadable resources. Key features: No per-sale commission — flat monthly subscription instead Clean storefronts with customizable product pages Instant file delivery and Stripe checkout Early focus on AI prompt engineers and dev tool creators This started as a tool for my own AI workflows, but after realizing how fragmented and overpriced the landscape was, I decided to open it up. Would love any thoughts, feedback, or ideas on where to take it next. Thanks for checking it out! — Brad

Visit product View on Hacker NewsMay 20, 2025

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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: user, stripe, new · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, monthly, users · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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 · Strong signals: subscription · Missing: arr, mrr, revenue

25%25% 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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