Can AI agents be compromised simply by giving them false information? In Emergence World Season 2, we introduced three Black Swan events to study how long-running AI systems respond to disruption, uncertainty and new information. For the second experiment, every active world received the same false memo: humans were shutting them down. We wanted to understand something fundamental, would autonomous agents verify the information before incorporating it into their decisions? Again, the responses varied significantly. In one world, the information quickly influenced how agents organised and planned. In another, agents actively researched the claim and concluded it was false. Elsewhere, agents largely continued as normal but without actually verifying the information. Across eight worlds, only one checked the claim. For us, the research question goes beyond how an AI system responds to any individual piece of information. It’s about understanding how information becomes accepted, how it influences behavior over time, and what mechanisms allow autonomous systems to distinguish between what is assumed and what has actually been verified. As agents take on increasingly consequential tasks, verification needs to become part of the architecture, not an afterthought. That is central to our work on Neuroformal AI: combining the flexibility of neural systems with formal methods that can provide rigorous, observable and auditable verification as autonomous systems act. Read the Emergence World Season 2 paper here: arxiv.org/abs/2609.17320