Nature reported work on “Robin,” a multi-agent system designed to automate more of the experimental biology workflow than prior AI tools. The system reportedly integrates literature-search agents with data-analysis agents to generate hypotheses, propose experiments, interpret results, and update subsequent hypotheses in an iterative lab-in-the-loop framework. In a described demonstration for dry age-related macular degeneration, Robin proposed retinal pigment epithelium phagocytosis enhancement as a therapeutic strategy and identified in vitro efficacy for ripasudil and KL001. The work then iterated toward mechanistic RNA-seq follow-ups, including identification of ABCA1 upregulation tied to lipid efflux. The study positions multi-agent autonomy as a step toward faster discovery cycles, with potential implications for target identification and lead optimization where experimental iteration speed is often a bottleneck.