The field of human-AI collaboration is rapidly advancing, with a focus on developing autonomous systems that can orchestrate complex workflows and facilitate collaboration between humans and AI agents. Researchers are exploring new approaches to workflow management, including the use of Partially Observable Stochastic Games and multi-objective optimization techniques. The development of open, community-driven standards for AI-powered systems is also a key area of research, with efforts underway to create standards for AI bill of materials and software package data exchange. Noteworthy papers in this area include: Orchestrating Human-AI Teams: The Manager Agent as a Unifying Research Challenge, which proposes a research vision for autonomous agentic systems that orchestrate collaboration within dynamic human-AI teams. Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which envisions agile, robust ecosystems built through socio-technical co-design. Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development, which explores how AI can enhance traditional requirements engineering practices. Exploring Human-AI Collaboration Using Mental Models of Early Adopters of Multi-Agent Generative AI Tools, which investigates how early adopters conceptualize multi-agent Gen AI tools and human-AI collaboration mechanisms.