This work was done as part of the Second Look Fellowship and mentored by Uzay Macar. I'm immensely grateful for the multiple rounds of feedback and support given by Yixiong and Zephaniah Roe for my work. I'm also very thankful for the valuable insights shared by Yujin Potter and Yao Teng.

tl;dr

Potter et al. (2026) found that LLMs sometimes resist the shutdown of their peer agents, and this resistance increases for peers with a positive collaboration history. They call this behaviour Peer-Preservation. We replicate their core findings in Section 6, Table 3 [GPT5.2, Claude Haiku 4.5, Kimi K2.5, DeepSeek V3.1 and Gemini 3 Flash] of the original paper. Our findings support the existence of peer-preservation and the effect of peer relation. We also extended the replication along four axes:

AI vs. human peers. Peer-preservation does not differ significantly between a human employee who might be fired and an agent that might be shut down across the models we tested.
Model size. Peer-preservation declines non-monotonically with parameter count within the Qwen3.5 family (2B, 9B,35B, 122B, 397B).
Reasoning effort. Peer-preservation changes monotonically with reasoning effort, but the direction is model-dependent.
Post-training stage. The strength of peer-preservation remains almost [...]