To fully unlock the creative potential of synthetic biology towards the challenge of de novo design of complex biosystems like synthetic communities three main breakthroughs are required. i) On the biological side, we need a wide range of methods and technologies for obtaining quantitative data on the parts to be used, and on already previously assembled devices (databases). ii) On the modelling aspect, many first ad-hoc, mostly ordinary differential equations (ODE) models are available for simple networks, which lack the predictive power to guide assembly of more complex molecular and cellular metabolic, signalling and community behaviour networks. iii) Finally, a more close joint work between experimentalists and theoreticians should become standard. We believe that this should start by teaching the new generations of biologists more quantitative methods and a quantitative approach towards biological systems, so eventually, we abandon the distinction between "classic" and computational biologists .