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How Save-Game Context Compaction Fixes Spec Drift in Multi-Step Coding Agents (-91.9% Input Tokens)
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How Save-Game Context Compaction Fixes Spec Drift in Multi-Step Coding Agents (-91.9% Input Tokens)

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💡 AI Labo Benchmark Series — Experiment E12 (Ranked #6 out of 41 Patterns)

This post is part of our empirical benchmark series testing AI coding agent harness patterns inside network-isolated Proxmox VMs against a hidden 20-case grading suite.

🚀 View All 41 Benchmark Results & Master Ranking

🛡️ Read How Our Proxmox & systemd Anti-Cheating Sandbox Works

Metadata & Experiment Identity

Experiment ID: E12 (Backlog Candidate C008 )

Run ID: e12-20261028-vm216-01

Sandbox Environment: Proxmox Isolated VM VM216 ( ai-e12-216 , 0 NICs, virtio-serial QGA relay, systemd UID separation)

Model: gemini-3.8-flash ( thinkingLevel: LOW )

Pattern Under Test: Save-Game Context Compaction ( /compact at Milestones) — "Unbounded History Accumulation vs. Milestone JSON State Compaction"

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