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    "source_story_id": "tmp-lead-agentzip-high-fanout-sandbox-memory",
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    "headline": "The Sandboxes Shared Eight Times More Memory Than Linux Found",
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    "dek": "AgentZip compressed related agent environments against their common template, then hid much of the restore cost inside the model’s waiting time.",
    "summary": "AgentZip compressed related agent environments against their common template, then hid much of the restore cost inside the model’s waiting time.",
    "body_text": "High-fanout agent jobs can open many concurrent sandboxes that begin from one template and follow related trajectories, leaving redundancy that ordinary per-page compression misses. AgentZip compresses against the template and across sandboxes, expands the set of pages considered profitable, prefetches restoration, and schedules expensive work during LLM waits. Across the authors’ training and inference workloads, sandbox-owned memory fell by as much as 8.7×, versus 2.1× for the tested Linux configuration. Execution-aware scheduling and prefetching reduced the slowdown of aggressive compression from as high as 3.1× to 1.40×. These are preprint results on the reported workloads, not a universal capacity guarantee.",
    "why_it_matters": "AgentZip compressed related agent environments against their common template, then hid much of the restore cost inside the model’s waiting time.",
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      "These are preprint results on the reported workloads, not a universal capacity guarantee."
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    "tags": [
      "AI agents",
      "sandboxes",
      "memory compression"
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      "source_id": "source-2026-09-12-001",
      "title": "arXiv preprint 2609.11294",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.11294",
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    "title": "The Sandboxes Shared Eight Times More Memory Than Linux Found",
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