The article explores a novel approach to sixth-generation (6G) intelligence, highlighting its capability to simulate future scenarios and support informed decision-making. Central to this development is a new paradigm for near-real-time control within open radio access networks, which leverages counterfactual dynamics and generative state-space modeling. This methodology enhances predictive capabilities, allowing for more accurate and timely responses in complex network environments. The focus on agentic world modeling represents a significant advancement in 6G technology, aiming to improve system adaptability and efficiency. By integrating these techniques, the approach addresses key challenges in managing dynamic wireless networks. The benefits include improved foresight and control, which are critical for the evolving demands of 6G applications. This work aligns with ongoing research efforts documented in recent arXiv publications, emphasizing the importance of advanced modeling for future communication systems.