The field of AI and law is moving towards a more integrated approach, where AI systems are designed to assist legal professionals in navigating complex legal rules and ensuring consistent realization of legislative intent. This is evident in the development of frameworks that leverage advanced AI to provide comprehensive and balanced analysis of legal criteria, enhancing consistency and predictability in legal decision-making. Another area of focus is the integration of symbolic AI into large language models, which aims to address the transparency challenges in these models. Additionally, there is a growing interest in designing systems that can ensure regulatory compliance and interpretability in dynamic and uncertain environments, such as automated driving. The importance of dignity and respect in interaction design is also being emphasized, particularly in the context of fully automated vehicles. Noteworthy papers include: Soppia, a structured prompting framework for the proportional assessment of non-pecuniary damages in personal injury cases, which introduces a practical and transparent methodology for legal professionals. Advancing Symbolic Integration in Large Language Models, which proposes a novel taxonomy of symbolic integration in LLMs and a roadmap for future research. Integrating Legal and Logical Specifications in Perception, Prediction, and Planning for Automated Driving, which provides a systematic analysis of current methodologies and highlights critical open questions and practical trade-offs. Designing for Dignity while Driving, which emphasizes the importance of respectful interaction design in fully automated vehicles for blind and low-vision passengers. Agentic AI Home Energy Management System, which presents a large language model framework for residential load scheduling that achieves optimal scheduling without example demonstrations.