The field of 6G network management and automation is witnessing significant advancements, driven by the integration of artificial intelligence (AI), machine learning (ML), and large language models (LLMs). Researchers are exploring innovative approaches to enable intent-driven network management, adaptive wireless body area networks, and agentic open marketplaces for 6G RAN automation. Notably, the use of LLMs is becoming increasingly prevalent, with applications in intent processing, network optimization, and fault detection. The development of agentic systems, such as MX-AI and Agoran, is also gaining traction, enabling autonomous agents to cooperate across the cloud-edge continuum and providing ultra-flexible, stakeholder-centric 6G networks. Some noteworthy papers in this area include: Agoran, an agentic open marketplace that achieved significant gains in throughput, latency, and PRB usage. MX-AI, an agentic observability and control platform that attained human-expert performance in real settings.