Reimplementing 40 Multi-Agent LLM Papers Reveals Eight Core Patterns

What I Learned from Reimplementing 40 Multi-Agent LLM Papers

After reimplementing 40 multi-agent LLM papers, I discovered that most complex frameworks boil down to simple loops, aggregation rules, and visibility functions. Key insights include the critical need for independent samples, the power of execution over opinion, and how dynamic team structures outperform static graphs. Ultimately, the entire field can be understood through just eight fundamental algorithmic families.

"Strip away the evaluation sections and the framework advertising, and the median paper’s contribution is: a loop shape, a prompt discipline, and an aggregation rule."