Stress, and more specifically, the lack of appropriate stress management strategies can be a significant burden for many people on a daily basis. In this talk, I introduce the vision from the Pervasive Wellbeing Technology lab to design novel stress management technology to keep people healthy and productive without adding cognitive or behavioral burdens. Our vision is implemented through two main research arms: (1) "sensorless" sensing and (2) opportunistic interventions. Sensorless sensing is a provocative term and approach that focuses on repurposing sensors or devices that already exist in the environment. For example, we can use a computer mouse or a car steering wheel as a sensor of mental stress by simply observing the effects of the arm's muscle tension on the movement of each device. Opportunistic micro interventions aim at theoretically eliminating the barriers for adoption and reach an optimal level of engagement by harvesting micro interventions from the common and daily use of cyber and physical personal spaces. For example, we repurpose popular (top-rated) apps, such as Facebook or Pinterest into micro proxies to well established therapies, such as cognitive reframing, somatic relaxation, positive psychology, etc.; we implement tiny conversations using chatbots to provide focused pieces of advice; or, we can modify a car's seat to deliver slow breathing interventions for commuters. Finally, I will discuss the underlying challenge to further maximize the efficacy and efficiency of these micro interventions. I will discuss the need to develop novel algorithms to deliver the right intervention at the right time. I will present some of the potential intervention opportunities, spaces, and the ideas that we are currently exploring. For example, depending on the user's mental state and schedule, we may want to recommend a funny chatbot conversation with the user to wind down after a difficult day, or perhaps oscillate the hue of a computer monitor or the height of a chair to induce lower or higher breathing rates.