Ag
AgentSafe – per-task micro-VM sandbox for AI agents (Go)
Hacker NewsAgentSafe – per-task micro-VM sandbox for AI agents (Go)
I was tinkering with AI agents for some time and made some utilities for myself for safe and fast execution. While chatting, I figured I can open source it. Spent some time cleaning and vibe coding some extensions for it. Here the results from real execution on M1 mac: VM Boot Times: /tmp/vm_final_1.log:VM Boot Time: 0s (Target: <200ms) /tmp/vm_final_2.log:VM Boot Time: 1ms (Target: <200ms) /tmp/vm_final_3.log:VM Boot Time: 0s (Target: <200ms)
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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, agent · Missing: macos, cursor, claude92%92% 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 · Missing: supports, reddit linkedin, podcasting63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency44%44% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released37%37% 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 · Missing: mobile apps, ios, personal32%32% 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, revenue22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive19%19% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Correct prediction on native model
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