Show HN: What sandboxing an AI coding agent in a VM costs
← Back to Velo Workspaces Benchmark What Sandboxing an AI Coding Agent in a VM Actually Costs on Apple Silicon I benchmarked the same sandboxing architecture against two different inference engines and got two different answers about what it costs under load. Here's why they disagree, and why I'm showing you both instead of picking the one that sounds better. The problem Most people running an AI coding agent locally give it a subprocess or exec() call with full access to their filesystem, network, and credentials.
- ▪← Back to Velo Workspaces Benchmark What Sandboxing an AI Coding Agent in a VM Actually Costs on Apple Silicon I benchmarked the same sandboxing architecture against two different inference engines and got two different answers about what i
- ▪Here's why they disagree, and why I'm showing you both instead of picking the one that sounds better.
- ▪The problem Most people running an AI coding agent locally give it a subprocess or exec() call with full access to their filesystem, network, and credentials.
2 outlets in our directory ran this story, first to last over 21 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
Hacker News (AI / LLM) files mainly under ai. We currently carry 5,321 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Velo Workspaces |
| Canonical URL | https://www.veloworkspaces.com/blog/vm-sandboxing-cost/ |
| Publication time | Thu, 17 Sep 2026 12:57:34 +0000 |
| Retrieval time | 2026-09-17T13:03:45.004Z |
| Last seen | 2026-09-17T13:03:45.004Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | _wIHNb91_sG1 · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
← Back to Velo Workspaces Benchmark What Sandboxing an AI Coding Agent in a VM Actually Costs on Apple Silicon I benchmarked the same sandboxing architecture against two different inference engines and got two different answers about what it costs under load. Both are real. Here's why they disagree, and why I'm showing you both instead of picking the one that sounds better. The problem Most people running an AI coding agent locally give it a subprocess or exec() call with full access to their filesystem, network, and credentials. Docker's own engineering blog has documented real incidents from exactly this. Indirect prompt injection makes it worse — a hostile instruction hidden in a file the agent reads can trigger commands with your full permissions, not just the ones you typed.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Velo Workspaces.
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