GSV – a personal AI computer that unifies your machines

Hacker News

Back in April I left the Agents team at Cloudflare because even though I loved the work, I always had the drive to build the apps rather than the libraries. I felt like nobody was building the ideas that I wanted to exist. My biggest drive was wanting my agents to run fully on “the cloud” yet having them on all my machines at the same time. So I ended up building GSV, fully open source. GSV acts as a cloud computer by having a remote file system and a shell environment and trying very hard to pretend to be something close to Unix. There’s a kernel that handles all the primitive operations, including AI inference and the agent loop. At the same time, your devices (and browser!) can connect your GSV to provide file system and shell access to those same agents too. This allows your agents running on the edge to have access to your local devices. I’ve just released the beta and would love to hear feedback. As of today, it requires a Workers Paid account (~5$/mo) plus your model costs.

Visit product View on Hacker NewsJun 30, 2026

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

97%97% 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.

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: just released, exist, open source · Missing: https docs, excited, lua

75%75% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

43%43% 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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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