SWYM - Share what you make

Hacker News

Hi guys, I launched a two-day app at a Hacker News London meetup last year. It's called SWYM: Share What You Make. Check it out here - http://swym.me The idea is simple and in a way inspired from Show HN posts. Every time someone posts something cool here, someone asks how did you make it? So Swym provides a simple way to share the tools and people you built your projects with. I put it on the shelf after presenting it last year, but it's one of those things that kept coming back at me. So, I decided to bring it back to life. Here's the full back story - http://swym.me/story If there's enough interest, I may also add a store component where you could sell what you make too. Please share your stuff and tell me what you think. Thanks! PS I put it on here yesterday; it went on to the homepage for a few minutes but disappeared soon. So I'm reposting it in case more people are interested.

Visit product View on Hacker NewsFeb 11, 2012

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

74%74% 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.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide · Missing: https docs, excited, just released

54%54% 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: soon · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · 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

22%22% 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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