A platform to find people to jam on side projects with

Hacker News

I have always found it funny how challenging it can be to find people to jam on side projects with. There are literally entire sub-Reddits where people post looking for someone to work on a project with. That is super inefficient. There are also newsletters for this (also pretty inefficient). Let's Jam is my attempt to solve this. This is NOT a cofounder matching platform. The idea is to connect people with ideas and skills so they can jam on them together. If they end up becoming cofounders, cool, but that is up to them. This is also NOT a place for freelancers to hunt job opportunities. Again, the platform is for people who have an idea or a skill and want to work on something together. How it works: > You either a) find a project and request to jam on it with that person, b) post a project and wait for someone to request to jam on it with you, c) claim an idea and wait for someone to request to jam on it with you. > Once someone requests to jam with you, you'll get an email, and you can vet them via LinkedIn or their past work. If you think they'll be a good fit then accept their request and they'll reach out to you. > That's it. Simple. Any feedback is greatly appreciated!

Visit product View on Hacker NewsMay 24, 2026

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

80%80% 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: ide · 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.

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

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, 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

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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