Vibebin – code and host inside LXC containers on your own VPS/server

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Hi all, I used Opus 4.5 for 99.9% of this project. Take that as you will. https://github.com/jgbrwn/vibebin vibebin is an Incus/LXC-based platform for self-hosting persistent AI coding agent sandboxes with Caddy reverse proxy and direct SSH routing to containers (suitable for VS Code remote ssh). Create and host your vibe-coded apps on a single VPS/server. If anyone wants to test or provide some feedback that would be great. Core functionality works but there's likely to be bugs. My intent for the project was for the tinkerer/hobbyist or even not super technical person to put this on a VPS and start just doing their own thing/experimenting/tinkering/learning etc. I had so much fun working on this project, completely reinvigorated by it tbh. I am just a Linux sysadmin and not a programmer at all (~just~ smart enough to figure stuff out though:) ) and I have to say the excitement and energy that was brought into me working on this project was nothing like I've ever experienced before. It makes me so optimistic about this future that we are either embracing or fending off (depending on your mindset). Thanks for taking a look!

Visit product View on Hacker NewsJan 27, 2026

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

88%88% 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.

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

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

60%60% 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, host · Missing: plus, intuitive, reviews

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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