The field of artificial intelligence is shifting towards compound AI systems, which combine multiple models and agents to create more powerful and versatile applications. This trend is driven by the need to integrate large language models into existing enterprise infrastructure and leverage proprietary data and APIs. Researchers are exploring new architectures and tools to support the development of compound AI systems, including novel orchestration mechanisms and visual interfaces for analyzing and debugging agent behavior. Notable advancements include the development of conversational AI systems for human-machine collaboration in machine learning operations and interactive authoring tools for industrial dashboard design prototypes. Noteworthy papers include:

• Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI, which proposes a comprehensive architecture for compound AI systems.
• SeaView: Software Engineering Agent Visual Interface for Enhanced Workflow, which introduces a novel tool for visualizing and inspecting SWE agent output.
• Towards Conversational AI for Human-Machine Collaborative MLOps, which presents a conversational agent system for enhancing human-machine collaboration in MLOps.
• DashChat: Interactive Authoring of Industrial Dashboard Design Prototypes through Conversation with LLM-Powered Agents, which proposes an interactive system for generating industrial dashboard design prototypes from natural language.