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Antibiotic resistance is a major threat to global health, claiming the lives of millions every year. With a nearly dry antibiotic development pipeline, novel strategies are urgently needed to combat resistant pathogens. One emerging strategy is the use of sequential antibiotic therapy, postulated to reduce the rate at which antibiotic resistance evolves. Here, we use the soft agar gradient evolution (SAGE) system to carry out high-throughput in vitro bacterial evolution against antibiotic pressure. We find that evolution of resistance to the antibiotic chloramphenicol (CHL) severely affects bacterial fitness, slowing the rate at which resistance to the antibiotics nitrofurantoin and streptomycin emerges. In vitro acquisition of compensatory mutations in the CHL-resistant cells markedly improves fitness and nitrofurantoin adaptation rates but fails to restore rates to wild-type levels against streptomycin. Genome sequencing reveals distinct evolutionary paths to resistance in fitness-impaired populations, suggesting resistance trade-offs in favor of mitigation of fitness costs. We show that the speed of bacterial fronts in SAGE plates is a reliable indicator of adaptation rates and evolutionary trajectories to resistance. Identification of antibiotics whose mutational resistance mechanisms confer stable impairments may help clinicians prescribe sequential antibiotic therapies that are less prone to resistance evolution.