Understanding how microbial traits affect the evolution and functioning of microbial communities is fundamental for improving the management of harmful microorganisms, while promoting those that are beneficial. Decades of evolutionary ecology research has focused on examining microbial cooperation, diversity, productivity and virulence but with one crucial limitation. The traits under consideration, such as public-good production and resistance to antibiotics or predation, are often assumed to act in isolation. Yet, in reality multiple traits frequently interact, which can lead to unexpected and undesired outcomes for the health of macroorganisms and ecosystem functioning. This is because many predictions generated in a single-trait context aimed at promoting diversity, reducing virulence or controlling antibiotic resistance can fail for systems where multiple traits interact. In this talk I will provide examples of this phenomenon and argue that synthetic microbial communities and multi-trait mathematical models are powerful tools for managing the beneficial and detrimental impact of microbial communities.