An author–reviewer loop matched a multi-agent workflow on MCFM Fortran-to-C++ translation at about one-third the cost per file
The work proposes collaborative human–AI agentic workflows in which domain experts write the specification and plan and agents write code under a deterministic orchestration pattern, with each stage ending in a numerical comparison against reference code and human approval; across fourteen experiments on translating MCFM from Fortran to C++, a simple author–reviewer loop with enforced limits settled a comparable number of files to a multi-agent workflow at about one-third the cost per file.