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CodeNearby 2.0

Tinder for developers! Find coding partners & build together

Productivity
Open Source
Developer Tools
GitHub
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Hunted bySubhadip SahaSubhadip Saha

CodeNearby is open-source social network built for developers. Find coding partners by skill, interest, or location, chat real-time, share updates, host virtual meetups, and use AI-Connect to discover collaborators through natural conversation. GitHub-powered profiles, global reach, local focus.

Top comment

Hey Product Hunt! 👋 We're back, **CodeNearby** is relaunching with a fresh UI and a bunch of new features. If you tried us before, this isn't the same app. If you haven't, now's the time. You won't be disappointed. **What's new & what it does:** - 🎨 Rebuilt UI, cleaner, faster, way less clunky - 🔍 Search devs by skill, interest, location - 🤖 AI-Connect, describe who you need in plain English, get matched via GitHub - 💬 Real-time chat to actually talk to them - 📢 Developer feed for sharing updates/snippets - 🎭 Virtual gatherings, polls, events, discussions - 🐙 GitHub-synced profiles, zero manual setup It's fully **open-source**, self-host it, contribute, or just poke around: github.com/subh05sus/codenearby Go have a look and find your dev partner. Feedback, bugs, roasts, all welcome. 🙏

Comment highlights

Interesting concept, but I'd want to understand the mechanics after the match happens, not just the swipe filter. Once two people move as far as sharing a private repo or actually building something together, that's real access - to code, sometimes to production keys further down the line. Is there anything on the platform side once you're paired, like an audit trail of who you matched with and when, or a reporting/blocking mechanism if someone turns out to be untrustworthy after they already have collaborator access? The matching problem gets most of the attention here, but the "then what happens after a bad match" part is the piece that actually protects people.

@subhh Voted for CodeNearby. Fun concept, but matching-style products need the first email to build trust fast, curious how that's handled.

The AI matching is interesting, but I still want to browse profiles myself before reaching out. However, how accurate is the AI when it comes to matches ?

fun idea but the "Tinder for developers" framing makes me wonder about the actual filtering. matching on shared languages/interests is the easy part, the hard part is that half of building something together is figuring out if the other person actually finishes things or ghosts after week one. is there anything in the matching that surfaces track record, like completed projects or a rating from past collabs, or is it purely profile-based for now?

Interesting angle, but its the same dating psychology applies here when it comes to matching, in dating the intrinsic motivation is driven by something more primal, a need for a companion. That driver is too strong which makes the tinder match kind of format works, can that apply to dev where that force (i am strugling with words here) is not exactly that strong so have someone look for fellow coders in the format. just a opinion. curious to know what your finding with any real trials or thoughts on this matter.

Running a dev community, the recurring pain is turning "I need someone who knows X" into an actual intro, so AI-Connect matching from a plain-English ask via GitHub is the piece I would lean on. The thing I would test first: does the match weigh real signal like recent repo activity and languages, or mostly the profile bio and self-declared skills? Getting matched to someone who lists Rust vs someone actually shipping Rust this month is a very different intro.

Can the developer also match with product manager or other roles? That would be cool

Matched with a Python dev two streets over and we ended up pair-programming for three hours. Wild that this actually works offline-style.

The local focus makes this much more interesting. Skills help you find the right person, but proximity and shared interests probably make it far more likely that something actually comes out of the connection.

Finally tried matching with developers in my area and actually chatted with someone working on a similar side project. The swipe format feels a little tinder-ish but it's a clever way to cut through the noise of generic dev forums.

Love the concept of matching devs by proximity and interests. One thing that would really help is adding skill tags and project repos to profiles so you can see what stack someone works in before matching. Right now it's hard to tell if a potential partner actually complements your skill set or if you're going to end up with five frontend devs in a row.

About CodeNearby 2.0 on Product Hunt

Tinder for developers! Find coding partners & build together

CodeNearby 2.0 launched on Product Hunt on July 15th, 2026 and earned 154 upvotes and 13 comments, placing #10 on the daily leaderboard. CodeNearby is open-source social network built for developers. Find coding partners by skill, interest, or location, chat real-time, share updates, host virtual meetups, and use AI-Connect to discover collaborators through natural conversation. GitHub-powered profiles, global reach, local focus.

CodeNearby 2.0 was featured in Productivity (656.2k followers), Open Source (68.6k followers), Developer Tools (515.9k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 260.8k products, making this a competitive space to launch in.

Who hunted CodeNearby 2.0?

CodeNearby 2.0 was hunted by Subhadip Saha. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Want to see how CodeNearby 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.