Create Private or Public Tool-Sharing Clubs with Patio

Hacker News

Hey HN I’ve been working on Patio, a platform to make DIY & home improvement more community-driven. Just shipped a new feature: Clubs. Clubs are like little hubs where you and your people can: - Share tools & leftover materials (instead of letting them collect dust) - Lend/borrow in private groups (family, friends, coworkers) or public ones (like a neighborhood tool library) - Pin a location for your club - Share guides, plans, or helpful links The idea: make it easier to share what’s already in your garage and cut down on waste. That half-box of tiles or extra paint? Could be exactly what your neighbor’s looking for. We’re still early, would love your feedback on how this could work best for neighborhoods, families, and organizations. Thanks and have a great day! Julien

Visit product View on Hacker NewsAug 29, 2025

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

72%72% 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: organizations · Missing: supports, reddit linkedin, podcasting

71%71% 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: ide, io · Missing: https docs, excited, just released

44%44% 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: platform · Missing: plus, intuitive, reviews

44%44% 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

39%39% 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

11%11% 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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