A study of 22 tasks and six models reports that changing only the orchestration layer reduced cost, token use, and runtime while maintaining equivalent completion quality.
The study evaluated 22 tasks across six models, changing only the agents’ orchestration layer. This allowed the researchers to examine how that layer could affect results without switching the underlying model.
The authors report lower costs, token use, and execution time, with equivalent completion quality. The available summary gives no reduction figures and insufficient detail to compare specific tasks or configurations.
To apply the idea, treat orchestration as a variable to test: compare configurations on representative tasks and track cost, tokens, runtime, and quality. Check whether results hold in your context; the study does not show that one configuration is best for every use case.
If you use AI to study or implement these practices, avoid sending personal or confidential data unless necessary. Decide what data may be used and review handling policies before running tests.