Non-Custodial Cryptocurrency Payment Gateway

Hacker News

I built this vibe coding (i know i know...i'll run strix on it once I'm finished). Started at 2am this morning its now 7:30pm PST. Less than 24 hours and 57k lines of code written. All TDD using next.js and supabase cloud. ....say what you will but this would have taken an entire team 2 years and 1M+ in funding before roocode/claude opus 4.5 -- cost me around $500 Here's the github. its open source: https://github.com/profullstack/coinpayportal Testers wanted. we have a cli/sdk too at https://www.npmjs.com/package/@profullstack/coinpay Here's the music i vibe coded to: https://open.spotify.com/artist/5uG9Er5qjdNmc5qPELGf0h?si=11... (also created by me with Suno.com) ps: here's a usestrix.com coupon code they gave me to share: chovyfu2025

Visit product View on Hacker NewsNov 27, 2025

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Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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

84%84% 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 · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting

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

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

45%45% 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 · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, cryptocurrency · Missing: web3, chat, make money

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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