The increasing concern about climate change as well as the expected direct environmental economic impacts of global warming will put considerable constraints on the US building sector, which consumes roughly 48% of the total primary energy, making it the biggest single source of CO2 emissions. It is obvious that the battle against climate change can only be won by considering innovative building approaches and consumer behaviors and bringing new, effective low carbon technologies to the building / consumer market. However, the limited time given to mitigate climate change is unforgiving to misled research and / or policy. This is the reason why Lawrence Berkeley National Lab is working on an open source long range Stochastic Lite Building Module (SLBM) to estimate the impact of different policies and consumer behavior on the market penetration of low carbon building technologies. SLBM is designed to be a fast running, user-friendly model that analysts can readily run and modify in its entirety through a visual interface. The tool is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies. It also incorporates consumer preferences and passive building systems as well as interactions between technologies (such as internal heat gains). Furthermore, everything is based on service demand, e.g. a certain temperature or luminous intensity, instead of energy intensities. The core objectives of this paper are to demonstrate the practical approach used, to start a discussion process between relevant stakeholders and to build collaborations.