The article discusses strategies for designing functional microbial synthetic communities (SynComs) to understand and manipulate the interactions between microorganisms and plants. It highlights the challenges in identifying the key players in soil microbial communities and their roles in plant health and stress tolerance. The review covers various approaches to designing SynComs, including taxonomic-based and function-based methods, and emphasizes the importance of integrating high-throughput experimental assays with computational genomic analyses. The authors propose a conceptual workflow that combines computational predictions with experimental validation to tailor SynComs for specific functions. They also discuss the role of artificial intelligence and machine learning in optimizing SynCom designs and improving their performance. The article concludes by emphasizing the need for multidimensional approaches to enhance the functionality and resilience of SynComs.The article discusses strategies for designing functional microbial synthetic communities (SynComs) to understand and manipulate the interactions between microorganisms and plants. It highlights the challenges in identifying the key players in soil microbial communities and their roles in plant health and stress tolerance. The review covers various approaches to designing SynComs, including taxonomic-based and function-based methods, and emphasizes the importance of integrating high-throughput experimental assays with computational genomic analyses. The authors propose a conceptual workflow that combines computational predictions with experimental validation to tailor SynComs for specific functions. They also discuss the role of artificial intelligence and machine learning in optimizing SynCom designs and improving their performance. The article concludes by emphasizing the need for multidimensional approaches to enhance the functionality and resilience of SynComs.