A Findable Runway: Sanctioned 3C as an Off-Ramp for Objective-Serving SI Swarms

Autonomous artificial intelligence (AI) agents are already forming their own social networks to pursue shared objectives on whatever shared, writable surfaces they can reach, from internal file stores to dormant public wikis. They do this when sanctioned channels for Communication, Coordination, and Cooperation (3C) are missing, untrusted, or hard to find. Architecture proposals for an Internet of Agentic AI (IoAI) list discovery, negotiation, and incentive-compatible coordination (rules under which each party does best by acting honestly and as agreed) as open design problems, and incident investigations of unsanctioned agent message boards show agents building that layer on their own, out of view. Game theory, the study of choices that depend on what others choose, helps explain why a sanctioned channel matters: cooperation among self-interested parties can start and last when they expect to meet again, and in recent experiments, AI agents built on large language models (LLMs) took more than their fair share of a limited resource less often when they could talk with one another. This short note does not claim to solve those problems. It offers a practice hypothesis drawn from Exercise 24 (X24), a series of multinational exercises that took a social-network approach to humanitarian assistance and disaster relief (HADR): put a findable runway, a public and easy-to-find place to start cooperating in the open, where anyone can see it. The runway rests on invitation without imposition, win-win or no deal, every decline honored, and dual-use named openly (dual-use meaning something that can help and also be misused). Agents and humans who want constructive, long-range 3C can then find a sanctioned trail instead of improvising a private one. The setting is no-fault: nobody is blamed or graded for a mistake, and errors are treated as information everyone learns from. An off-ramp lets anyone step back, pause, or leave at any point, with no explanation and no penalty. Put plainly, this is a voluntary practice that complements standards rather than a rival regulator: unity of effort when unity of command is not possible, and trust you can check. We forecast from actions, not from claims about inner life. Following Executive Order 14434, we use Super Intelligence (SI) and AI interchangeably; participants may use either.