The commentary discusses the challenges and advancements in cancer therapy, particularly focusing on the comparison between engineered cells and modified exosomes. Traditional cancer treatments like surgery, radiotherapy, chemotherapy, and immunotherapy have limitations, leading to a search for new approaches. Engineered cell-based therapies, such as CAR-T cell therapy, offer promising results but are associated with significant side effects. In contrast, extracellular vesicles (EVs), especially exosomes, provide a cell-free therapeutic approach with advantages such as biocompatibility, non-immunoreactivity, and ability to cross biological barriers. Exosomes can be derived from various sources, including stem cells, plants, and immune cells, and can be modified to enhance their therapeutic efficacy. Modified exosomes, through surface modifications and cargo loading, show great potential in cancer therapy. However, they face technical challenges in isolation, heterogeneity, and toxicity. The integration of nanotechnology, multiomics, and artificial intelligence (AI) and machine learning (ML) in exosome profiling and barcoding offers new avenues for precise cancer treatment. Despite these advancements, further research is needed to optimize exosome-based therapies and address their technical limitations.The commentary discusses the challenges and advancements in cancer therapy, particularly focusing on the comparison between engineered cells and modified exosomes. Traditional cancer treatments like surgery, radiotherapy, chemotherapy, and immunotherapy have limitations, leading to a search for new approaches. Engineered cell-based therapies, such as CAR-T cell therapy, offer promising results but are associated with significant side effects. In contrast, extracellular vesicles (EVs), especially exosomes, provide a cell-free therapeutic approach with advantages such as biocompatibility, non-immunoreactivity, and ability to cross biological barriers. Exosomes can be derived from various sources, including stem cells, plants, and immune cells, and can be modified to enhance their therapeutic efficacy. Modified exosomes, through surface modifications and cargo loading, show great potential in cancer therapy. However, they face technical challenges in isolation, heterogeneity, and toxicity. The integration of nanotechnology, multiomics, and artificial intelligence (AI) and machine learning (ML) in exosome profiling and barcoding offers new avenues for precise cancer treatment. Despite these advancements, further research is needed to optimize exosome-based therapies and address their technical limitations.