LLMs and wireless networks are converging into a unified computational and communication fabric that supports ubiquitous intelligence. This chapter examines emerging trends shaping this integration, including network-generated experience, agentic control, domain-informed reasoning, multi-timescale adaptation, AI-native architectures, hierarchical model execution, and networked memory. It outlines future directions for both LM-for-Network and Network-for-LM, identifies the technical forces driving long-term evolution, and highlights the open challenges, such as stability, security, evaluation, and governance, required to build reliable, scalable, and intelligent networked systems. The goal is to provide a forward-looking perspective on how models and networks will codesign, co-adapt, and coevolve in next-generation digital infrastructures.