BACKGROUND: Metagenomic sequencing can potentially transform clinical microbiology by enabling rapid pathogen identification and antimicrobial resistance (AMR) prediction in critically ill patients with bloodstream infections. However, the clinical use of metagenomic sequencing has been constrained by its speed, accuracy, and technical feasibility. Our aim was to develop and evaluate a direct-from-positive blood culture workflow using Oxford Nanopore sequencing that overcomes these limitations and delivers rapid, accurate results. METHODS: In this metagenomic pipeline analysis, 211 positive (130 aerobic and 81 anaerobic) and 62 negative (30 aerobic and 32 anaerobic) randomly selected blood cultures were processed from Oxford University Hospitals for comparing species identification, AMR detection, and time-to-result against standard culture-based diagnostics performed by the hospital's routine microbiology laboratory. Species prediction was performed using Kraken2 with a comprehensive standard database, applying heuristic and random forest classification models. Additionally, we benchmarked AMR classification tools and databases, including ResFinder, CARD, and NCBI AMRFinderPlus. FINDINGS: Across all samples, our method achieved 97% sensitivity and 94% specificity for species identification compared with that of routine culture and matrix-assisted laser desorption ionisation time-of-flight-based diagnostics; both sensitivity and specificity increased to 100% after adjudication of plausible additional infections. We detected 19 additional infections (13 polymicrobial, five previously unidentifiable, and one in a culture-negative sample) and delivered species identification results within 3 h 20 min (IQR 3 h 7 min-3 h 27 min), approximately 10 h earlier than routine diagnostic methods. For the ten most common clinically relevant pathogens, our method yielded AMR results 20 h earlier than current antimicrobial susceptibility testing, with an overall sensitivity of 88% and specificity of 93%. Performance varied by species. For Staphylococcus aureus, the AMR prediction sensitivity was 100% and specificity was 99%, and for Escherichia coli, the prediction sensitivity was 91% and specificity was 94%. INTERPRETATION: These findings show that metagenomic sequencing has the potential to rapidly and comprehensively detect pathogens and AMR in bloodstream infections. Integration into clinical practice could help to close diagnostic gaps, reduce empirical antibiotic use, and enable rapid targeted treatment. Nonetheless, improvements in AMR prediction for some species and drugs, along with further multisite validation, are required before clinical implementation. FUNDING: National Institute for Health Research (NIHR) Oxford Biomedical Research Centre.