The field of AI-assisted productivity and collaboration is rapidly evolving, with a focus on developing innovative solutions to support effective usage of complex tools and systems. Recent research has explored the potential of large language models (LLMs) to generate high-quality tutorials, facilitate collaborative design of AI agents, and improve conversational information-seeking experiences. Notably, studies have highlighted the importance of technical expertise in successfully leveraging LLMs, and the need for more effective prompting strategies to unlock their full potential. Furthermore, the development of systems like InvisibleMentor and PromptPilot demonstrates the potential for AI to provide personalized support and guidance in workflow optimization and prompt engineering. Overall, the field is moving towards more seamless and intuitive human-AI collaboration, with a focus on empowering users to work more efficiently and effectively. Noteworthy papers include: No More Manual Guides, which presents a framework for automatically generating Excel tutorials, and PromptPilot, which introduces an interactive prompting assistant to improve human-AI collaboration. User Prompting Strategies and ChatGPT Contextual Adaptation Shape Conversational Information-Seeking Experiences is also notable for its insights into user prompting behaviors and ChatGPT's contextual adaptation.