dailyai.report

Multi-agent systems often derive their performance gains from increased compute rather than architectural superiority. Researchers at Stanford found that these ensembles frequently mirror the results of a single agent given more processing time. This suggests developers should prioritize efficient single-model prompting over complex agentic workflows unless specific task exceptions apply.