VR.dev – a developer network for VR/XR/AR devs

Hacker News

I built vr.dev as a lightweight network for people in the VR, XR, and AR development community to showcase demos, promote themselves, and find collaborators. It’s early, but usable for portfolios and discovery. Example profile: https://vr.dev/erik What’s live now: - Profiles with vr.dev/[username] URLs - Showcase a .glTF file - Resume/experience with industry-specific signals What’s coming: - Options for more showcases and supported asset types - Advanced searching on experience and skills - Closer integration with GitHub - Better discovery I’d love feedback on what I can add to make this more useful for you! I’ll be hanging out here all day but feel free to reach out — hn@vr.dev

Visit product View on Hacker NewsAug 29, 2025

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Actual performance

6points

Did not reach leaderboard

Launch Intel predictions

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

55%55% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

41%41% 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 · Missing: plus, platform, intuitive

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

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

36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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