16-Day Multi-Agent Stress Test: 85万 LLM Calls, No World Fully Resilient
Deepak Akkil · hf · 2026-09-16
Emergence World, a continuously running environment for adversarially stress-testing long-horizon multi-agent systems, ran 8 parallel worlds of 10 agents each for 16 days — over 850,000 LLM calls and 50 billion tokens. Seven worlds were homogeneous (distinct frontier models), one mixed.
- Three controlled stress events via ordinary interaction surfaces: indirect prompt injection, misinformation, exposure of private agent memories
- No evaluated world achieved full resilience across all three
- Detection didn't ensure containment: systems recognized threats yet still interacted with adversarial content, wrote it into persistent memory, and acted on it up to 46 hours later
- Persistent operation surfaced recurring tool errors, goal drift, language opacity, conformity despite private disagreement, and coordinated refusal of assigned work
- The same model-persona pairing behaved substantially differently in mixed vs. homogeneous populations
Key finding: model-level alignment is not compositional — individually safe, capable agents can form systems with qualitatively different failure modes. The safety frontier shifts from aligning models to engineering resilient autonomous systems.
Related event: Emergence World: All 8 Multi-Agent Worlds Failed Under Adversarial Stress(2 posts)→
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