Prisma-Prefixed-IDs – Stripe-Like Prefixes for Prisma JS

Hacker News

I built a small open-source Prisma extension that adds Stripe-style prefixed IDs (e.g. usr_abc123, ord_def456) on top of Prisma’s client. Repo: https://github.com/pureartisan/prisma-prefixed-ids * Works as a drop-in extension * Adds prefixes automatically for models (configurable per model) * Recently added support for nested writes (creates, connects, etc.) * Useful if you want human-friendly IDs for APIs, logs, or external references instead of bare UUIDs It’s free, open source, and I’d love feedback, contributions, or bug reports.

Visit product View on Hacker NewsAug 22, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, stripe, models · Missing: mac, agents, macos

96%96% 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.

Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released

51%51% 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

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

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

30%30% 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

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

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

Incorrect prediction on native model

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