Twelve quick tips for designing AI-driven HPC workflows

Twelve practical tips for designing AI-driven HPC workflows

A preprint from arXiv offers twelve practical guidelines for researchers designing AI and foundation-model-driven workflows on HPC clusters. The guide addresses system-level challenges including containerisation, job arrays, feedback loop mechanics, and I/O optimisation for small files. The work targets the transition from deterministic linear pipelines to adaptive, probabilistic computational environments, with particular emphasis on computational biology use cases.