The field of artificial intelligence is moving towards autonomous engineering and AI-driven research, with a focus on developing platforms and frameworks that can perform complex tasks without human intervention. Recent developments have shown that AI engineers can be used to design and optimize complex products, such as UAV wings, with high success rates and minimal manual intervention. The use of multi-agent systems and proxy-guided approaches is also becoming increasingly popular, allowing for more efficient and scalable machine learning engineering. Furthermore, the introduction of common task frameworks is enabling the comparison and evaluation of different algorithms and models, driving progress in the field. Noteworthy papers include: Engineering.ai, which presents a platform for teams of AI engineers in computational design, and ArchPilot, which introduces a multi-agent system for machine learning engineering. Accelerating scientific discovery with the common task framework is also a significant contribution, providing a critically enabling technology for the rapid advance of ML/AI algorithms.