The Phoebus toolkit continues to evolve as a modern, extensible platform for control system user applications and middle-layer services. As the next generation of the Eclipse-based Control System Studio, Phoebus retains the familiar, integrated toolset experience while replacing the Eclipse RCP framework with a modular architecture built on standard Java technologies and JavaFX. This transition simplifies maintenance and extensibility while providing foundational building blocks for modern applications and scalable services. Recent efforts have focused on strengthening infrastructure and streamlining deployment, including updates to support recent Java LTS releases; modernization of the Middle-layer services to use newer Kafka and Spring Boot versions; and improved documentation. Middle-layer services—offering alarm management, save/restore, channel finder, and logbooks—continue to evolve, with emphasis on simplifying configuration, improving scalability, and aligning with modern web standards and containerized workflows. The Phoebus collaboration now includes contributors from dozens of facilities worldwide, many of them first-time participants. Alongside technical progress, the project has prioritized a sustainable, inclusive collaboration model to support future developers and users. This paper outlines the current status, community efforts, and future directions of the Phoebus ecosystem.

As the Relativistic Heavy Ion Collider (RHIC) completes its final physics run in 2025, design activities for the future Electron Ion Collider (EIC) that will probe the building blocks of nuclear physics for decades to come have made critical advances.  Recent improvements including a new Electron Injector System and updated Low Energy Cooler for electron-based cooling of hadron beams will be described.  Advancements in the planning and demonstration activities for accelerator controls elements such as the Common Platform front-end computer designs and related infrastructure, EPICS-based software infrastructure, bridging tools to controls for legacy systems required to support hadron injector systems, and networking and computing infrastructure designs will be highlighted.  Our analysis of potential scope of AI/ML integration with controls for the EIC accelerator and detector systems will be introduced.

The Electron-Ion Collider (EIC) will succeed the current Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. For over two decades, RHIC and its injectors have relied on a homegrown Accelerator Device Object (ADO)-based control system, which has provided a reliable and efficient operational framework. However, the EIC’s requirements—such as a greater number of subsystems, higher uptime, increased data rates, and other factors—demand significant enhancements. Advances in both hardware and software technologies since the RHIC era have expanded the range of available options, each with its own set of benefits and challenges. In response, the EIC plans to deploy state-of-the-art technologies to meet these elevated demands, favoring open-source and community-driven solutions wherever feasible. This talk will focus on the control software and the technology choices under consideration and the strategies being adopted for the EIC.

Facilities relying on collaboratively developed software projects, like the Experimental Physics and Industrial Control System (EPICS), often face challenges in ensuring consistent skill levels and efficient onboarding of staff. This paper introduces a new framework for creating reproducible pre-configured virtual machine (VM) environments, specifically designed for hands-on EPICS training. A key benefit of this framework is its ability to establish shared, reusable, general training modules. Such shared resources are highly valuable for collaborations, as they provide a standardized platform for skill development, reduce redundant training efforts, cultivate a common understanding of EPICS mechanisms, and ultimately strengthen collective knowledge within and across institutions.

The Electron-Ion Collider (EIC) will succeed the current Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. For over two decades, RHIC and its injectors have relied on a homegrown Accelerator Device Object (ADO)-based control system, which has provided a reliable and efficient operational framework. However, the EIC’s requirements—such as a greater number of subsystems, higher uptime, increased data rates, and other factors—demand significant enhancements. Advances in both hardware and software technologies since the RHIC era have expanded the range of available options, each with its own set of benefits and challenges. In response, the EIC plans to deploy state-of-the-art technologies to meet these elevated demands, favoring open-source and community-driven solutions wherever feasible. This talk will focus on the control software and the technology choices under consideration and the strategies being adopted for the EIC.

Facilities relying on collaboratively developed software projects, like the Experimental Physics and Industrial Control System (EPICS), often face challenges in ensuring consistent skill levels and efficient onboarding of staff. This paper introduces a new framework for creating reproducible pre-configured virtual machine (VM) environments, specifically designed for hands-on EPICS training. A key benefit of this framework is its ability to establish shared, reusable, general training modules. Such shared resources are highly valuable for collaborations, as they provide a standardized platform for skill development, reduce redundant training efforts, cultivate a common understanding of EPICS mechanisms, and ultimately strengthen collective knowledge within and across institutions.