As an example of a shared resource, consider a lab in which a central piece of equipment such as an X-ray diffractometer or reactive annealing chamber is used in several distinct workflows. Traditional methods of experiment automation would involve each workflow taking ownership of that equipment during the workflow's runtime. Combining all workflows in a single instance of automation software limits the ability of different workflows to start and stop as dictated by science management and/or equipment maintenance needs. Human researchers address this challenge by creating a system to schedule the requested usage of shared equipment, and the automation analogue is to have the shared equipment operated by a broker whose runtime is independent of all other workflow automation software. This is the central tenet of "Nimble interconnected workflows" as depicted in Fig. , wherein each resource family is controlled by an asynchronous Resource Manager. The runtime independence of Resource Managers and Workflow Orchestrators enables each Orchestrator to maintain focus on a single research workflow while empowering a Science Manager to coordinate efforts across many workflows in any number of physical laboratories.