Breaking up OpenAI might tackle concentration, but bigger leverage is interoperability and transparency across compute, model, and orchestration layers so no single vendor controls agentic LLM workflows. As the field shifts toward multi-agent, distributed agentic AI (including parallel agentic AI), policy should prioritize open agent protocols, auditable sandboxes, and portable evals/policies. That preserves competition while addressing system-level risks (emergent behavior, cascading failures) that arise specifically in agentic AI more than in single-model deployments.
replies(2):