The field of artificial intelligence is witnessing significant advancements in scientific discovery and software development. Recent research has focused on developing innovative methods for autonomous generation of scientific protocols, disaster management, and brain cell type annotation. These developments have the potential to improve the efficiency and accuracy of scientific research and disaster response. Furthermore, advancements in multi-agent systems and large language models are enabling the automation of software development, including API-first development and application-level code generation. Notable papers in this area include: Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism, which introduces a novel approach for generating precise and executable scientific protocols. Disaster Management in the Era of Agentic AI Systems: A Vision for Collective Human-Machine Intelligence for Augmented Resilience, which proposes a transformative vision for disaster management using multi-agent AI systems. A Brain Cell Type Resource Created by Large Language Models and a Multi-Agent AI System for Collaborative Community Annotation, which presents a novel resource for brain cell type annotation using large language models and multi-agent AI systems.