I Built an Open-Source Rig That Measures Multi-Agent Architectures

Learn to build and use an open-source measurement framework for evaluating multi-agent AI architectures in this 37-minute technical video. Discover Brain Cube Agent Labs, a research-based tool that helps determine when multi-agent systems actually outperform single-agent baselines through controlled experimentation. Explore the core methodology of treating single-agent systems as default baselines and measuring performance deltas across different coordination patterns including independent, centralized, decentralized, and hybrid approaches. Master the process of generating paired empirical data, building custom tasks using Claude Code with real finance agent benchmarks, and running comparison and elasticity calibration batches. Navigate the interactive dashboard to visualize scaling dynamics, identify collapse points, and understand when adding more agents provides diminishing returns versus when weaker agents benefit from multi-agent setups. Gain practical insights for production agent development, learning to recognize when multi-agent complexity justifies the coordination costs before committing to architectures that may fail at scale, all built on the Anthropic Agent SDK framework.