and are two of the most common coinfecting bacteria in human infections, including the cystic fibrosis (CF) lung. There is emerging evidence that coinfection with these microbes enhances disease severity and antimicrobial tolerance through direct interactions. However, one of the challenges to studying microbial interactions relevant to human infection is the lack of experimental models with the versatility to investigate complex interaction dynamics while maintaining biological relevance. Here, we developed a model based on an medium that mimics human CF lung secretions (synthetic CF sputum medium [SCFM2]) and allows time-resolved assessment of fitness and community spatial structure at the micrometer scale. Our results reveal that and coexist as spatially structured communities in SCFM2 under static growth conditions, with enriched at a distance of 3.5 μm from Multispecies aggregates were rare, and aggregate (biofilm) sizes resembled those in human CF sputum. Elimination of 's ability to produce the antistaphylococcal small molecule HQNO (2-heptyl-4-hydroxyquinoline -oxide) had no effect on bacterial fitness but altered the spatial structure of the community by increasing the distance of from to 7.6 μm. Lastly, we show that coculture with sensitizes to killing by the antibiotic tobramycin compared to monoculture growth despite HQNO enhancing tolerance during coculture. Our findings reveal that SCFM2 is a powerful model for studying and and that HQNO alters biogeography and antibiotic susceptibility without affecting fitness. Many human infections result from the action of multispecies bacterial communities. Within these communities, bacteria have been proposed to directly interact via physical and chemical means, resulting in increased disease and antimicrobial tolerance. One of the challenges to studying multispecies infections is the lack of robust, infection-relevant model systems with the ability to study these interactions through time with micrometer-scale precision. Here, we developed a versatile model for studying the interactions between and , two bacteria that commonly coexist in human infections. Using this model along with high-resolution, single-cell microscopy, we showed that and form communities that are spatially structured at the micrometer scale, controlled in part by the production of an antimicrobial by In addition, we provide evidence that this antimicrobial enhances tolerance to an aminoglycoside antibiotic only during coculture.