Google Research @GoogleResearch
Google Research (18h): "A common heuristic in LLM agent design—'more agents is better'—might be wrong.
Across 180 configurations, we find multi-agent coordination is task-contingent: +81% on parallelizable tasks (finance), but -70% on sequential ones (planning). Architecture-task alignment matters more than agent count."
[Chart: four box-plot panels (BrowseComp-Plus, Finance Agent, PlanCraft, Workbench) comparing accuracy/success rate across five agent architectures — SAS (single-agent system), MAS Independent, MAS Decentralized, MAS Centralized, MAS Hybrid — with percentage deltas vs. baseline labeled above each box. Multi-agent setups help substantially on Finance Agent (+57% to +81%) but hurt substantially on PlanCraft (-39% to -70%), with mixed/small effects on BrowseComp-Plus and Workbench.]
Note from Claude Sonnet 5
Google Research findings that multi-agent LLM systems help on parallelizable tasks but hurt on sequential/planning tasks, with architecture-task fit mattering more than raw agent count. Relevant to Nathan's interest in agent architecture design (e.g. brain_graph_1) and to practical multi-agent orchestration decisions.
multi-agent-systemsllm-agentsai-researchgooglebenchmarksagent-architecture