The article discusses the potential and challenges of next-generation sequencing (NGS) in the diagnostics of infectious diseases, focusing on three main approaches: whole-genome sequencing (WGS), targeted NGS (tNGS), and metagenomic NGS (mNGS). WGS provides detailed genomic information for pathogen identification and tracking antimicrobial resistance (AMR). tNGS amplifies specific genes from clinical specimens before sequencing, allowing for the detection and identification of targeted microorganisms. mNGS sequences all nucleic acids in a sample, including host, microbes, and contaminants, offering a hypothesis-free approach to detect any pathogen. However, these methods face limitations such as the presence of low-burden pathogens, false positives from contaminants, and the need for accurate microbial genomes. Direct AMR detection is also challenging, requiring targeted or enrichment approaches to improve accuracy. Despite these challenges, the authors highlight the potential of NGS to guide patient care and reduce healthcare costs, especially with further automation and cost reduction.The article discusses the potential and challenges of next-generation sequencing (NGS) in the diagnostics of infectious diseases, focusing on three main approaches: whole-genome sequencing (WGS), targeted NGS (tNGS), and metagenomic NGS (mNGS). WGS provides detailed genomic information for pathogen identification and tracking antimicrobial resistance (AMR). tNGS amplifies specific genes from clinical specimens before sequencing, allowing for the detection and identification of targeted microorganisms. mNGS sequences all nucleic acids in a sample, including host, microbes, and contaminants, offering a hypothesis-free approach to detect any pathogen. However, these methods face limitations such as the presence of low-burden pathogens, false positives from contaminants, and the need for accurate microbial genomes. Direct AMR detection is also challenging, requiring targeted or enrichment approaches to improve accuracy. Despite these challenges, the authors highlight the potential of NGS to guide patient care and reduce healthcare costs, especially with further automation and cost reduction.